{"672395":{"#nid":"672395","#data":{"type":"event","title":"ISyE Seminar - Jonathan Stallrich","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003ETitle: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EStatistical Methods for $mall Data Problems\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EWith data collection, storage, and management becoming faster and cheaper, statisticians and data scientists have developed important statistical and computational methods for Big Data problems. However, there are still many significant problems that involve small quantities of data that are \u201cbig\u201d in terms of monetary or temporal cost. These $mall (small) data problems are best solved with careful planning of both the data collection and analysis methods. In this talk, I will discuss some examples of these problems and new statistical methods to tackle them. The talk will primarily focus on new screening experiments that jointly target efficient estimation of both the main effects of the manipulated factors and the process variance. I will then survey new ideas for problems that have received less attention in the literature, including optimal designs for penalized estimation, screening designs for generalized linear models, and design and analysis for screening under functional linear models.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EJon Stallrich is an Associate Professor in the Department of Statistics at NC State University. He earned his Ph.D. in Statistics from Virginia Tech in 2014. \u003Cspan\u003EHe has focused his career on innovating and teaching practical statistical methods under the tenet that data collection and analysis procedures should be jointly determined to make efficient statistical conclusions. \u003C\/span\u003EJon\u2019s research interests include design and analysis of screening experiments, computer experiments, functional data analysis, and variable selection. \u003Cspan\u003EHis methodological research is often motivated by interdisciplinary collaborations with researchers from industrial and systems engineering, biomedical engineering, material science, toxicology, and computer science.\u003C\/span\u003E In 2021, he and his coauthors were awarded the ASA\u2019s Statistics in Physical Engineering Sciences Award for the paper, \u201cOptimal EMG placement for a robotic prosthesis controller with sequential, adaptive functional estimation.\u201d He is currently serving as Chair of the ASA\u2019s Section on Physical and Engineering Sciences and General Conference Chair of the 2024 Fall Technical Conference to be held in Nashville, TN.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EWith data collection, storage, and management becoming faster and cheaper, statisticians and data scientists have developed important statistical and computational methods for Big Data problems. However, there are still many significant problems that involve small quantities of data that are \u201cbig\u201d in terms of monetary or temporal cost. These $mall (small) data problems are best solved with careful planning of both the data collection and analysis methods. In this talk, I will discuss some examples of these problems and new statistical methods to tackle them. The talk will primarily focus on new screening experiments that jointly target efficient estimation of both the main effects of the manipulated factors and the process variance. I will then survey new ideas for problems that have received less attention in the literature, including optimal designs for penalized estimation, screening designs for generalized linear models, and design and analysis for screening under functional linear models.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Statistical Methods for $mall Data Problems"}],"uid":"34977","created_gmt":"2024-01-23 19:56:20","changed_gmt":"2024-01-23 19:56:20","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-02-06T11:00:00-05:00","event_time_end":"2024-02-06T12:00:00-05:00","event_time_end_last":"2024-02-06T12:00:00-05:00","gmt_time_start":"2024-02-06 16:00:00","gmt_time_end":"2024-02-06 17:00:00","gmt_time_end_last":"2024-02-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"672104":{"#nid":"672104","#data":{"type":"event","title":"ISyE Seminar - Ying Jin","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003ETitle:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EModel-free selective inference: from calibrated uncertainty to trusted decisions\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAI has shown great potential in accelerating decision-making and scientific discovery pipelines such as drug discovery, marketing, and healthcare. In many applications, predictions from black-box models are used to shortlist candidates whose unknown outcomes satisfy a desired property, e.g., drugs with high binding affinities to a disease target. To ensure the reliability of high-stakes decisions, uncertainty quantification tools such as conformal prediction have been increasingly adopted to understand the variability in black-box predictions. However, we find that the on-average guarantee of conformal prediction can be insufficient for its deployment in decision making which usually has a selective nature.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, I will introduce a model-free selective inference framework that allows to select reliable decisions with the assistance of any black box prediction model. Our framework identifies candidates whose unobserved outcomes exceed user-specified values while controlling the average proportion of falsely selected units (FDR), without any modeling assumptions. Given a set of exchangeable training data, our method constructs conformal p-values that quantify the confidence in large outcomes; it then determines a data-dependent threshold for the p-values as a criterion for drawing confident decisions. In addition, I will discuss new ideas to further deal with covariate shifts between training and new samples. We show that in several drug discovery tasks, our methods narrow down the drug candidates to a manageable size of promising ones while controlling the proportion of falsely discovered. In a causal inference dataset, our methods identify students who benefit from an educational intervention, providing new insights for causal effects.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EYing Jin is a fifth-year PhD student at Department of Statistics, Stanford University, advised by Emmanuel Cand\u00e8s and Dominik Rothenh\u00e4usler. Prior to this, she obtained B.S. in Mathematics from Tsinghua University. Her research focuses on devising modern statistical methodology that enables trusted inference and decisions with minimal assumptions, as well as its deployment in real applications, covering conformal inference, multiple testing, causal inference, distribution robustness, and data-driven decision-making.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAI has shown great potential in accelerating decision-making and scientific discovery pipelines such as drug discovery, marketing, and healthcare. In many applications, predictions from black-box models are used to shortlist candidates whose unknown outcomes satisfy a desired property, e.g., drugs with high binding affinities to a disease target. To ensure the reliability of high-stakes decisions, uncertainty quantification tools such as conformal prediction have been increasingly adopted to understand the variability in black-box predictions. However, we find that the on-average guarantee of conformal prediction can be insufficient for its deployment in decision making which usually has a selective nature.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, I will introduce a model-free selective inference framework that allows to select reliable decisions with the assistance of any black box prediction model. Our framework identifies candidates whose unobserved outcomes exceed user-specified values while controlling the average proportion of falsely selected units (FDR), without any modeling assumptions. Given a set of exchangeable training data, our method constructs conformal p-values that quantify the confidence in large outcomes; it then determines a data-dependent threshold for the p-values as a criterion for drawing confident decisions. In addition, I will discuss new ideas to further deal with covariate shifts between training and new samples. We show that in several drug discovery tasks, our methods narrow down the drug candidates to a manageable size of promising ones while controlling the proportion of falsely discovered. In a causal inference dataset, our methods identify students who benefit from an educational intervention, providing new insights for causal effects.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Model-free selective inference: from calibrated uncertainty to trusted decisions"}],"uid":"34977","created_gmt":"2024-01-16 14:02:28","changed_gmt":"2024-01-16 14:02:28","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-02-08T11:00:00-05:00","event_time_end":"2024-02-08T12:00:00-05:00","event_time_end_last":"2024-02-08T12:00:00-05:00","gmt_time_start":"2024-02-08 16:00:00","gmt_time_end":"2024-02-08 17:00:00","gmt_time_end_last":"2024-02-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670992":{"#nid":"670992","#data":{"type":"event","title":"SCL January 2024 Supply Chain Day","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain students and employers, please join us for our first fall Supply Chain Day!\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEvent Details\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (Georgia Tech Exhibition Hall)\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EWednesday, January 24, 2024 | 11am - 2pm ET\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003EStudents\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage you to attend to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EOrganizations\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIf you are interested in hosting a table for the upcoming session, please let us know after reviewing the below information within our website.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students and employers, please join us for our spring Supply Chain Day! We will be hosting an On Campus session\u0026nbsp;Wednesday, January 24, 2024 from 11am-2pm ET at the Georgia Tech Exhibition Hall.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Supply chain and logistics career fair where industry supply chain representatives meet Georgia Tech students."}],"uid":"27233","created_gmt":"2023-11-09 20:11:22","changed_gmt":"2024-01-09 20:48:18","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-24T11:00:00-05:00","event_time_end":"2024-01-24T14:00:00-05:00","event_time_end_last":"2024-01-24T14:00:00-05:00","gmt_time_start":"2024-01-24 16:00:00","gmt_time_end":"2024-01-24 19:00:00","gmt_time_end_last":"2024-01-24 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech Exhibition Hall","extras":[],"hg_media":{"672334":{"id":"672334","type":"image","title":"SCL January 2024 Supply Chain Day","body":null,"created":"1699557302","gmt_created":"2023-11-09 19:15:02","changed":"1699557302","gmt_changed":"2023-11-09 19:15:02","alt":"January 24, 2024 Supply Chain Day banner","file":{"fid":"255559","name":"Supply Chain Day Supply Chain and Logistics Career Fair.png","image_path":"\/sites\/default\/files\/2023\/11\/09\/Supply%20Chain%20Day%20Supply%20Chain%20and%20Logistics%20Career%20Fair.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/11\/09\/Supply%20Chain%20Day%20Supply%20Chain%20and%20Logistics%20Career%20Fair.png","mime":"image\/png","size":1037693,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/11\/09\/Supply%20Chain%20Day%20Supply%20Chain%20and%20Logistics%20Career%20Fair.png?itok=QBi1l6_T"}}},"media_ids":["672334"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"671900":{"#nid":"671900","#data":{"type":"event","title":"ISyE Seminar - Brandon Pitts ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETechnology \u2026 Here, There, and Everywhere:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EThe Need to Understand Human Interactions with Emerging Technologies \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEmerging technologies are being developed at an unprecedented rate and are altering human behavior in new ways. This trend is expected to continue for the foreseeable future as society seeks to leverage the capabilities of machines and artificial intelligence (AI) to their fullest extent. Intelligent technologies offer many potential benefits, but also come with unique challenges. For example, some systems require shared responsibilities, occasional but unpredictable human intervention, and rapid real-time human decision-making. In addition, many technologies are being used by a diverse user demographic with varying levels of experience with technology, expectations, and abilities. In this presentation, Dr. Pitts will share insights from a series of research projects in his lab aimed at evaluating various pervasive technologies in transportation, work, and leisure environments and for different types of users. Findings from his research are contributing to the critical discussion on how to (re)design interfaces to support effective human-technology collaborations across many broad applications. This work is also helping to inform theories on human perception and performance, promote safety and efficiency in complex environments, and shape policies on universal design and accessibility.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. Brandon Pitts is an Assistant Professor in the School of Industrial Engineering and a Faculty Associate with the Center on Aging and the Life Course (CALC) at Purdue University in West Lafayette, IN. He received his Ph.D. in Industrial and Operations Engineering from the University of Michigan (UM), Ann Arbor in 2016. Prior to his faculty appointment, he was a Research Fellow in the UM Center for Healthcare Engineering and Patient Safety (CHEPS). Dr. Pitts\u2019 research areas include human factors engineering, human-automation\/AI interaction, cyber-human-physical systems, interface design, and gerontechnology in complex transportation and work environments, i.e., driving and aviation. His research has been funded by several sponsors, such as the National Science Foundation (NSF), Department of Transportation (DOT), Federal Aviation Administration (FAA), National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR), and Ford Motor Company. Dr. Pitts has also received several honors and recognitions, including the 2023 Stephanie Binder Young Professional Award, a 2023 NSF CAREER award, and 1st place in the 2022 U.S. DOT Inclusive Design Challenge (IDC) for his team\u2019s EASI RIDER autonomous vehicle innovation. \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEmerging technologies are being developed at an unprecedented rate and are altering human behavior in new ways. This trend is expected to continue for the foreseeable future as society seeks to leverage the capabilities of machines and artificial intelligence (AI) to their fullest extent. Intelligent technologies offer many potential benefits, but also come with unique challenges. For example, some systems require shared responsibilities, occasional but unpredictable human intervention, and rapid real-time human decision-making. In addition, many technologies are being used by a diverse user demographic with varying levels of experience with technology, expectations, and abilities. In this presentation, Dr. Pitts will share insights from a series of research projects in his lab aimed at evaluating various pervasive technologies in transportation, work, and leisure environments and for different types of users. Findings from his research are contributing to the critical discussion on how to (re)design interfaces to support effective human-technology collaborations across many broad applications. This work is also helping to inform theories on human perception and performance, promote safety and efficiency in complex environments, and shape policies on universal design and accessibility.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Technology \u2026 Here, There, and Everywhere:  The Need to Understand Human Interactions with Emerging Technologies "}],"uid":"34977","created_gmt":"2024-01-05 17:24:26","changed_gmt":"2024-01-05 17:24:26","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-23T11:00:00-05:00","event_time_end":"2024-01-23T12:00:00-05:00","event_time_end_last":"2024-01-23T12:00:00-05:00","gmt_time_start":"2024-01-23 16:00:00","gmt_time_end":"2024-01-23 17:00:00","gmt_time_end_last":"2024-01-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671862":{"#nid":"671862","#data":{"type":"event","title":"ISyE Seminar - Bento Natura ","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003ERecent Advances in Strongly Polynomial Algorithms for Linear Programming\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EWhereas ellipsoid methods and interior point methods provide polynomial-time linear programming algorithms, the running time bounds depend on bit-complexity or condition measures that can be unbounded in the problem dimension. This is in contrast with the simplex method that always admits an exponential bound.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EAn important unresolved question in operations research, theoretical computer science, and related fields, concerns the existence of a strongly polynomial algorithm for linear programming. Such an algorithm\u0027s running time would solely depend on the problem\u0027s dimension and the number of constraints, independent of any additional condition numbers. This question, first articulated by Megiddo in the 1980s, has gained prominence as Smale\u0027s 9th problem.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the first part of our talk, we introduce a new polynomial-time path-following interior point method where the number of iterations admits a combinatorial upper bound that is exponential in the number of constraints. More precisely, the iteration count of our algorithm is at most a small polynomial factor times the segment count of any piecewise linear trajectory within a wide neighborhood of the central path. Notably, it parallels the iteration count of any path-following interior point method, with an adjustment for this polynomial factor.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the second part of our talk, we give a strongly polynomial algorithm for minimum cost generalized flow, and hence all linear programs with at most two nonzero entries per row, or at most two nonzero entries per column. This provides a next milestone towards answering Smale\u2019s 9th problem.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EBento Natura is a Ronald J. and Carol T. Beerman\/ARC Postdoctoral Fellow in ISyE at Georgia Tech. He obtained his PhD in the Department of Mathematics at the London School of Economics, where he was supervised by L\u00e1szl\u00f3 V\u00e9gh. His doctoral thesis earned him the departmental Dissertation Prize and placed as a runner-up for the PhD Prize awarded by the OR Society of the United Kingdom. Prior to his PhD, Bento earned Bachelor\u0027s and Master\u0027s degrees in Mathematics from the University of Bonn, under the supervision of Stephan Held and Jens Vygen. Bento\u0027s current research interests are centered on algorithms, optimization, and game theory.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EWhereas ellipsoid methods and interior point methods provide polynomial-time linear programming algorithms, the running time bounds depend on bit-complexity or condition measures that can be unbounded in the problem dimension. This is in contrast with the simplex method that always admits an exponential bound.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EAn important unresolved question in operations research, theoretical computer science, and related fields, concerns the existence of a strongly polynomial algorithm for linear programming. Such an algorithm\u0027s running time would solely depend on the problem\u0027s dimension and the number of constraints, independent of any additional condition numbers. This question, first articulated by Megiddo in the 1980s, has gained prominence as Smale\u0027s 9th problem.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the first part of our talk, we introduce a new polynomial-time path-following interior point method where the number of iterations admits a combinatorial upper bound that is exponential in the number of constraints. More precisely, the iteration count of our algorithm is at most a small polynomial factor times the segment count of any piecewise linear trajectory within a wide neighborhood of the central path. Notably, it parallels the iteration count of any path-following interior point method, with an adjustment for this polynomial factor.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the second part of our talk, we give a strongly polynomial algorithm for minimum cost generalized flow, and hence all linear programs with at most two nonzero entries per row, or at most two nonzero entries per column. This provides a next milestone towards answering Smale\u2019s 9th problem.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Recent Advances in Strongly Polynomial Algorithms for Linear Programming"}],"uid":"34977","created_gmt":"2024-01-04 13:14:21","changed_gmt":"2024-01-04 13:14:21","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-18T11:00:00-05:00","event_time_end":"2024-01-18T12:00:00-05:00","event_time_end_last":"2024-01-18T12:00:00-05:00","gmt_time_start":"2024-01-18 16:00:00","gmt_time_end":"2024-01-18 17:00:00","gmt_time_end_last":"2024-01-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671677":{"#nid":"671677","#data":{"type":"event","title":"ISyE Seminar - Sen Na","body":[{"value":"\u003Ch3\u003ETitle:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EPracticality meets Optimality: Real-Time Statistical Inference under Complex Constraints\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EAbstract:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EConstrained estimation problems are prevalent in statistics, machine learning, and engineering. These problems\u0026nbsp;encompass constrained generalized linear models, constrained deep neural networks, physics-inspired machine\u0026nbsp;learning, algorithmic fairness, and optimal control. However, existing estimation methods under hard constraints\u0026nbsp;rely on either projection or regularization, which may theoretically exhibit optimal efficiency but are impractical\u0026nbsp;or unreasonably fail in reality. This talk aims to bridge the significant gap between practice and theory\u0026nbsp;for constrained estimation problems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI will begin by introducing the critical methodology used to bridge the gap, called Stochastic Sequential Quadratic\u0026nbsp;Programming. We will see that SQP methods serve as the workhorse for modern scientific machine learning problems\u0026nbsp;and can resolve the failure modes of prevalent regularization-based methods. I will demonstrate how to make\u0026nbsp;SQP adaptive and scalable using various modern techniques, such as stochastic line search, trust region, and dimension\u0026nbsp;reduction.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, I will show how to further enhance SQP to handle inequality constraints online.\u003Cbr \/\u003E\r\nFollowing the methodology, I will present some selective theories, emphasizing the consistency and efficiency\u003Cbr \/\u003E\r\nof the SQP methods. Specifically, I will show that online SQP iterates asymptotically exhibit normal behavior\u003Cbr \/\u003E\r\nwith a mean of zero and optimal covariance in the H\u00e1jek and Le Cam sense. Significantly, the covariance does\u003Cbr \/\u003E\r\nnot deteriorate even when we apply modern techniques driven by practical concerns. The talk concludes with\u003Cbr \/\u003E\r\nexperiments on both synthetic and real datasets.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EBio:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ESen Na is currently a postdoctoral researcher in the Department of Statistics and the International Computer\u003Cbr \/\u003E\r\nScience Institute at UC Berkeley. He received a Ph.D. degree in statistics from the University of Chicago.\u003Cbr \/\u003E\r\nSen Na\u2019s primary research interests lie in the mathematical foundations of data science, encompassing high dimensional\u0026nbsp;statistics, computational statistics, sequential decision-making, and large-scale and stochastic\u003Cbr \/\u003E\r\nnonlinear optimization. Additionally, he is passionate about various applications of machine learning methods in\u0026nbsp;scientific fields such as biology, neuroscience, physics, and engineering. Sen Na\u2019s research has been recognized\u0026nbsp;by the prestigious Harper Dissertation Fellowship from UChicago, and he has been selected as one of the\u0026nbsp;Young Researchers in ORIE by Cornell University.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003EAbstract:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EConstrained estimation problems are prevalent in statistics, machine learning, and engineering. These problems\u003Cbr \/\u003E\r\nencompass constrained generalized linear models, constrained deep neural networks, physics-inspired machine\u003Cbr \/\u003E\r\nlearning, algorithmic fairness, and optimal control. However, existing estimation methods under hard constraints\u003Cbr \/\u003E\r\nrely on either projection or regularization, which may theoretically exhibit optimal efficiency but are impractical\u003Cbr \/\u003E\r\nor unreasonably fail in reality. This talk aims to bridge the significant gap between practice and theory\u003Cbr \/\u003E\r\nfor constrained estimation problems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI will begin by introducing the critical methodology used to bridge the gap, called Stochastic Sequential Quadratic\u003Cbr \/\u003E\r\nProgramming. We will see that SQP methods serve as the workhorse for modern scientific machine learning problems\u0026nbsp;and can resolve the failure modes of prevalent regularization-based methods. I will demonstrate how to make\u0026nbsp;SQP adaptive and scalable using various modern techniques, such as stochastic line search, trust region, and dimension\u0026nbsp;reduction. Additionally, I will show how to further enhance SQP to handle inequality constraints online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFollowing the methodology, I will present some selective theories, emphasizing the consistency and efficiency\u003Cbr \/\u003E\r\nof the SQP methods. Specifically, I will show that online SQP iterates asymptotically exhibit normal behavior\u003Cbr \/\u003E\r\nwith a mean of zero and optimal covariance in the H\u00e1jek and Le Cam sense. Significantly, the covariance does\u003Cbr \/\u003E\r\nnot deteriorate even when we apply modern techniques driven by practical concerns. The talk concludes with\u003Cbr \/\u003E\r\nexperiments on both synthetic and real datasets.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Practicality meets Optimality: Real-Time Statistical Inference under Complex Constraints"}],"uid":"34977","created_gmt":"2023-12-21 14:32:47","changed_gmt":"2023-12-21 14:35:28","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-16T11:00:00-05:00","event_time_end":"2024-01-16T12:00:00-05:00","event_time_end_last":"2024-01-16T12:00:00-05:00","gmt_time_start":"2024-01-16 16:00:00","gmt_time_end":"2024-01-16 17:00:00","gmt_time_end_last":"2024-01-16 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671660":{"#nid":"671660","#data":{"type":"event","title":"ISyE Seminar - Mohsen Moghaddam","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETitle:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EThe Human-Tech Duo: Augmenting Learning and Creativity with AI and Spatial Computing\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EHuman-centered computing holds the promise of enabling a symbiotic relationship between humans and technology, prioritizing augmentation over substitution with software and machines. How can we realize this vision in industrial workplaces by harnessing AI and extended reality (XR), coupled with new sources of data? In this talk, I will present two research examples addressing this question. The first involves helping industrial workers learn complex psychomotor and cognitive tasks, such as inspection and assembly, more effectively. I will discuss how AI-powered XR can accelerate the progression from novice to expert through adaptive interventions tailored to individual needs, skills, and knowledge. I will introduce a new intelligent XR framework facilitating this through online activity understanding, error detection and prevention, expertise modeling, and content generation. The second example focuses on enhancing the creativity of product designers. I will discuss how AI can transform the front-end of product design by automating the analysis of user data and translating it into creative and user-centered concepts. I will present our current research on large-scale need finding from user reviews, simulation of usage contexts in XR for latent need elicitation, design concept generation and evaluation, and interfaces supporting designer exploration. In concluding the talk, I will present an overarching research agenda and discuss multiple avenues for future research on human-technology teaming within diverse industrial contexts.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EMohsen Moghaddam is an Assistant Professor of Mechanical and Industrial Engineering, affiliated with the Khoury College of Computer Sciences, and serves as the Director of the Symbiotic and Augmented Intelligence Lab (SAIL) at Northeastern University. He is also a Visiting Scholar at the Next Level Lab, Harvard University. He earned his PhD in Industrial Engineering from Purdue University and served as a Postdoctoral Associate at the GE-Purdue Partnership in Research and Innovation in Advanced Manufacturing before joining Northeastern. His research focuses on exploring human-centered computational models, algorithms, and tools at the intersection of AI and spatial computing to enhance learning and creativity in various cognitive and psychomotor tasks within industrial settings. In addition to his academic pursuits, he co-founded ADA Tech (Advanced Design Augmentation Technologies) and currently serves as its Acting CTO, leading use-inspired research on AI tools that empower designers to create diverse, innovative, and user-centered products. His research is sponsored by NSF, DARPA, the U.S. Navy, Northeastern University, and industry.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EHuman-centered computing holds the promise of enabling a symbiotic relationship between humans and technology, prioritizing augmentation over substitution with software and machines. How can we realize this vision in industrial workplaces by harnessing AI and extended reality (XR), coupled with new sources of data? In this talk, I will present two research examples addressing this question. The first involves helping industrial workers learn complex psychomotor and cognitive tasks, such as inspection and assembly, more effectively. I will discuss how AI-powered XR can accelerate the progression from novice to expert through adaptive interventions tailored to individual needs, skills, and knowledge. I will introduce a new intelligent XR framework facilitating this through online activity understanding, error detection and prevention, expertise modeling, and content generation. The second example focuses on enhancing the creativity of product designers. I will discuss how AI can transform the front-end of product design by automating the analysis of user data and translating it into creative and user-centered concepts. I will present our current research on large-scale need finding from user reviews, simulation of usage contexts in XR for latent need elicitation, design concept generation and evaluation, and interfaces supporting designer exploration. In concluding the talk, I will present an overarching research agenda and discuss multiple avenues for future research on human-technology teaming within diverse industrial contexts.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The Human-Tech Duo: Augmenting Learning and Creativity with AI and Spatial Computing"}],"uid":"34977","created_gmt":"2023-12-20 16:10:56","changed_gmt":"2023-12-20 16:10:56","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-25T11:00:00-05:00","event_time_end":"2024-01-25T12:00:00-05:00","event_time_end_last":"2024-01-25T12:00:00-05:00","gmt_time_start":"2024-01-25 16:00:00","gmt_time_end":"2024-01-25 17:00:00","gmt_time_end_last":"2024-01-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671659":{"#nid":"671659","#data":{"type":"event","title":"ISyE Seminar - Anirudh Sridhar ","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETitle: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EModeling and Mitigation of Network Cascades\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAs our world becomes more connected through physical, technological and socioeconomic networks, it becomes more vulnerable to failures in these networks. These failures, which often rapidly diffuse across the network, have dealt serious societal damage in the form of epidemics, computer viruses, and misinformation. It is therefore imperative to understand how such \u0022cascading failures\u0022 propagate, and how interventions can be designed to mitigate their effects.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the first part of this talk, I will discuss recent progress in modeling network cascades. A fundamental hurdle in the analysis of cascades is their inherent high-dimensional structure, caused by the complexity of the underlying network as well as the stochasticity of the cascade dynamics. This motivates the use of simpler approximations for understanding the evolution of the cascade. I will touch upon new results along these lines related to mean-field models, mask-wearing, and multi-strain models with mutations.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the second part of this talk, I will develop algorithms for the real-time localization of network cascades. Specifically, our goal is to identify the cascade source before too many vertices in the network are affected by the cascade. The cascade is assumed to spread according to a Susceptible-Infected process from an unknown source in a network. While the propagation is not directly observable, noisy information about its spread can be gathered through multiple rounds of error-prone diagnostic testing. Using this data model, we devise a novel adaptive procedure inspired by classical multi-hypothesis sequential probability ratio tests (MSPRTs) which provably localizes the cascade before a negligible fraction of the network is affected. In certain cases, our method is optimal, i.e. no other algorithm can localize the cascade using substantially fewer rounds of testing. Based on joint work with Tirza Routtenberg and H. Vincent Poor.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAnirudh Sridhar (Ani) is a postdoctoral associate at MIT\u0027s Department of Mathematics. Previously, he completed his PhD from Princeton\u0027s Department of Electrical and Computer Engineering, where he was advised by H. Vincent Poor and Mikl\u00f3s R\u00e1cz. Broadly, Ani\u0027s research develops statistical methods for the analysis of networks, with a focus on information-theoretic characterizations. His awards include the Yan Huo *94 Graduate Fellowship in Electrical Engineering from Princeton University in 2022 and a Spotlight Presentation at NeurIPS 2021. He was also a finalist for the Informs-APS Best Student Paper Award in 2020.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAs our world becomes more connected through physical, technological and socioeconomic networks, it becomes more vulnerable to failures in these networks. These failures, which often rapidly diffuse across the network, have dealt serious societal damage in the form of epidemics, computer viruses, and misinformation. It is therefore imperative to understand how such \u0022cascading failures\u0022 propagate, and how interventions can be designed to mitigate their effects.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the first part of this talk, I will discuss recent progress in modeling network cascades. A fundamental hurdle in the analysis of cascades is their inherent high-dimensional structure, caused by the complexity of the underlying network as well as the stochasticity of the cascade dynamics. This motivates the use of simpler approximations for understanding the evolution of the cascade. I will touch upon new results along these lines related to mean-field models, mask-wearing, and multi-strain models with mutations.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the second part of this talk, I will develop algorithms for the real-time localization of network cascades. Specifically, our goal is to identify the cascade source before too many vertices in the network are affected by the cascade. The cascade is assumed to spread according to a Susceptible-Infected process from an unknown source in a network. While the propagation is not directly observable, noisy information about its spread can be gathered through multiple rounds of error-prone diagnostic testing. Using this data model, we devise a novel adaptive procedure inspired by classical multi-hypothesis sequential probability ratio tests (MSPRTs) which provably localizes the cascade before a negligible fraction of the network is affected. In certain cases, our method is optimal, i.e. no other algorithm can localize the cascade using substantially fewer rounds of testing. Based on joint work with Tirza Routtenberg and H. Vincent Poor.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Modeling and Mitigation of Network Cascades"}],"uid":"34977","created_gmt":"2023-12-20 16:07:08","changed_gmt":"2023-12-20 16:07:08","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-09T11:00:00-05:00","event_time_end":"2024-01-09T12:00:00-05:00","event_time_end_last":"2024-01-09T12:00:00-05:00","gmt_time_start":"2024-01-09 16:00:00","gmt_time_end":"2024-01-09 17:00:00","gmt_time_end_last":"2024-01-09 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671508":{"#nid":"671508","#data":{"type":"event","title":"ISyE Seminar - Shuangning Li","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003ETitle\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E\u003Cspan\u003E: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EModeling\u0026nbsp;Interference\u0026nbsp;for Policy Evaluation in Stochastic Systems\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EAbstract\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EInterference is a phenomenon where the treatment of one unit may affect the outcomes of other units. It is a major consideration for accurate policy evaluation in stochastic systems. Although this may seem intractable in a non-parametric causal inference setting, I will demonstrate that in many problems, some lightweight modeling can significantly aid in capturing and quantifying these interference effects. In particular, I will discuss two different forms of interference:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E(1) Network interference. In the network interference model, units are represented as vertices on an exposure graph (for example, a social network). In this model, the treatment assigned to one unit may affect the outcomes of other units connected to it through edges in the graph. I will discuss large-sample asymptotics for treatment effect estimation under network interference, where the exposure graph is a random draw from a graphon.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E(2) Congestion induced interference. In service systems, stochastic congestion can arise from temporarily limited supply and\/or demand. Such congestion gives rise to interference between the waiting customers, and analytic strategies that do not account for this interference may be biased. I will discuss the potential of using knowledge about the congestion mechanism to design and analyze experiments in the presence of stochastic congestion.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EBio\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EI am currently a postdoctoral fellow working with Professor Susan Murphy in the Department of Statistics at Harvard University. Prior to this, I earned my Ph.D. from the Department of Statistics at Stanford University, where I was advised by Professors Emmanuel Cand\u00e8s and Stefan Wager.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EAbstract\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EInterference is a phenomenon where the treatment of one unit may affect the outcomes of other units. It is a major consideration for accurate policy evaluation in stochastic systems. Although this may seem intractable in a non-parametric causal inference setting, I will demonstrate that in many problems, some lightweight modeling can significantly aid in capturing and quantifying these interference effects. In particular, I will discuss two different forms of interference:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E(1) Network interference. In the network interference model, units are represented as vertices on an exposure graph (for example, a social network). In this model, the treatment assigned to one unit may affect the outcomes of other units connected to it through edges in the graph. I will discuss large-sample asymptotics for treatment effect estimation under network interference, where the exposure graph is a random draw from a graphon.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E(2) Congestion induced interference. In service systems, stochastic congestion can arise from temporarily limited supply and\/or demand. Such congestion gives rise to interference between the waiting customers, and analytic strategies that do not account for this interference may be biased. I will discuss the potential of using knowledge about the congestion mechanism to design and analyze experiments in the presence of stochastic congestion.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Modeling Interference for Policy Evaluation in Stochastic Systems"}],"uid":"34977","created_gmt":"2023-12-11 14:17:46","changed_gmt":"2023-12-11 14:17:46","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-11T11:00:00-05:00","event_time_end":"2024-01-11T12:00:00-05:00","event_time_end_last":"2024-01-11T12:00:00-05:00","gmt_time_start":"2024-01-11 16:00:00","gmt_time_end":"2024-01-11 17:00:00","gmt_time_end_last":"2024-01-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671434":{"#nid":"671434","#data":{"type":"event","title":"Webinar - Reducing Food Waste in the Supply Chain: Greenhouse Gas Benefit","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESession Overview\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EReducing crop and food waste is widely understood to have environmental and economic benefits. However, at different points along the supply chain, and for different approaches to reducing food waste, the benefits may be larger or smaller, or in some cases even negative. General life cycle assessment concepts will be explained with examples of the food supply chain and how it might change under a range of waste reduction scenarios. Examples of how to quantify and characterize the greenhouse gas benefits of reducing crop and food waste will be discussed, with suggestions for greater efficiency and improvement.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbout Dr. Valerie M. Thomas\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EValerie Thomas is the Anderson-Interface Chair of Natural Systems and Professor in the H. Milton School of Industrial and Systems Engineering, with a joint appointment in the School of Public Policy. Dr. Thomas\u0027s research interests are energy and materials efficiency, sustainability, industrial ecology, technology assessment, international security, and science and technology policy. Current research projects include low carbon transportation fuels, carbon capture, building construction, and electricity system development. Dr. Thomas is a Fellow of the American Association for the Advancement of Science, and of the American Physical Society. She has been an American Physical Society Congressional Science Fellow, a Member of the U.S. EPA Science Advisory Board, and a Member of the USDA\/DOE Biomass Research and Development Technical Advisory Committee. She has worked at Princeton University in the Princeton Environmental Institute and in the Center for Energy and Environmental Studies, and at Carnegie Mellon University in the Department of Engineering and Public Policy. Dr. Thomas received a B. A. in physics from Swarthmore College and a Ph.D. in theoretical physics from Cornell University.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EReducing crop and food waste is widely understood to have environmental and economic benefits. However, at different points along the supply chain, and for different approaches to reducing food waste, the benefits may be larger or smaller, or in some cases even negative.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring Dr. Valerie Thomas, Anderson-Interface Chair of Natural Systems and Professor"}],"uid":"27233","created_gmt":"2023-12-06 12:48:23","changed_gmt":"2023-12-06 13:03:48","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-12-07T14:00:00-05:00","event_time_end":"2023-12-07T15:00:00-05:00","event_time_end_last":"2023-12-07T15:00:00-05:00","gmt_time_start":"2023-12-07 19:00:00","gmt_time_end":"2023-12-07 20:00:00","gmt_time_end_last":"2023-12-07 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online via Microsoft Teams","extras":[],"hg_media":{"672510":{"id":"672510","type":"image","title":"ECU: Reducing Food Waste in the Supply Chain","body":null,"created":"1701866573","gmt_created":"2023-12-06 12:42:53","changed":"1701866614","gmt_changed":"2023-12-06 12:43:34","alt":"Reducing Food Waste in the Supply Chain Seminar flyer","file":{"fid":"255759","name":"VThomasReductingFoodWasteSeminar.png","image_path":"\/sites\/default\/files\/2023\/12\/06\/VThomasReductingFoodWasteSeminar.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/12\/06\/VThomasReductingFoodWasteSeminar.png","mime":"image\/png","size":1289720,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/12\/06\/VThomasReductingFoodWasteSeminar.png?itok=8wOkk8-b"}}},"media_ids":["672510"],"related_links":[{"url":"https:\/\/www.isye.gatech.edu\/users\/valerie-thomas","title":"ISyE Profile - Dr. Valerie Thomas"},{"url":"https:\/\/GO.ECU.EDU\/CSE3WEBINAR\/REDUCINGFOODWASTEGHGBENEFITS","title":"Register Online for Microsoft Teams link"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"53321","name":"Food Supply Chain"},{"id":"174066","name":"greenhouse gases"},{"id":"143871","name":"Physical Internet Center"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671346":{"#nid":"671346","#data":{"type":"event","title":"10th International Physical Internet Conference (IPIC 2024)","body":[{"value":"\u003Ch3\u003EPlease join us for the 10th International Physical Internet Conference taking place May 29-31, 2024 in Savannah, GA at The DeSoto Hotel.\u0026nbsp;The event is hosted by\u0026nbsp;the Georgia Tech Physical Internet Center in association with the Supply Chain and Logistics Institute.\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe Physical Internet Initiative aims at transforming the way physical objects are moved, stored, realized, supplied and used, pursuing global logistics efficiency and sustainability. Originating from Professor \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/benoit-montreuil\u0022\u003E\u003Cstrong\u003EBenoit Montreuil\u003C\/strong\u003E\u003C\/a\u003E in 2006, this ground breaking vision, revolutionizing current paradigms, has stirred great interest from scientific, industrial as well as governmental communities.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe \u003Ca href=\u0022https:\/\/www.pi.events\/\u0022\u003E\u003Cstrong\u003EInternational Physical Internet Conference\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;aims to provide an open forum for researchers, industry representatives, government officials and citizens to together explore, discuss, introduce leading edge concepts, methodologies, recent projects, technological advancements, start-up initiatives, for current and future Physical Internet implementation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EConference topics include inter-connected logistics, PI fundamentals, business models, governance and implementation, cross-chain control, synchromodal transportation, IT systems, stakeholders and their roles. New business models, enabling technologies and experimentations already underway will be presented, making this meeting a unique opportunity to learn, network and discuss the latest results and challenges about interconnected logistics.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnd, because logistics is global, participants will be from all over the world including researchers, industrial and international institution members, local authorities and standardization committees.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EVisit \u003Ca href=\u0022http:\/\/www.pi.events\u0022 target=\u0022_blank\u0022\u003Ewww.pi.events\u003C\/a\u003E to learn more about the conference\u003C\/strong\u003E.\u003C\/h3\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPlease join us for the 10th International Physical Internet Conference taking place May 29-31, 2024 in Savannah, GA.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"IPIC 2024 will take place May 29-31, 2024 in Savannah, GA."}],"uid":"27233","created_gmt":"2023-12-01 15:06:17","changed_gmt":"2023-12-01 17:26:31","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-05-29T09:00:00-04:00","event_time_end":"2024-05-31T18:00:00-04:00","event_time_end_last":"2024-05-31T18:00:00-04:00","gmt_time_start":"2024-05-29 13:00:00","gmt_time_end":"2024-05-31 22:00:00","gmt_time_end_last":"2024-05-31 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"The DeSoto Hotel - Savannah, GA","extras":[],"hg_media":{"672490":{"id":"672490","type":"image","title":"banner-IPIC2024_1024x1024.jpg","body":null,"created":"1701449184","gmt_created":"2023-12-01 16:46:24","changed":"1701449184","gmt_changed":"2023-12-01 16:46:24","alt":"IPIC 2024 Conference Banner showing concept art of planes, trains, trucks around a globe moving product.","file":{"fid":"255735","name":"banner-IPIC2024_1024x1024.jpg","image_path":"\/sites\/default\/files\/2023\/12\/01\/banner-IPIC2024_1024x1024.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/12\/01\/banner-IPIC2024_1024x1024.jpg","mime":"image\/jpeg","size":523779,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/12\/01\/banner-IPIC2024_1024x1024.jpg?itok=invbZE8L"}}},"media_ids":["672490"],"related_links":[{"url":"https:\/\/www.pi.events\/IPIC2024","title":"Conference Website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"122741","name":"physical internet"},{"id":"143871","name":"Physical Internet Center"},{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EPlease direct questions relating to the conference to \u003Ca href=\u0022mailto:IPIC@scl.gatech.edu\u0022\u003EIPIC@scl.gatech.edu\u003C\/a\u003E.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"671154":{"#nid":"671154","#data":{"type":"event","title":"ISyE Seminar - Bahar Taskesen ","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003ETitle: \u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EReliable Data-driven Decision Making\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EWe are witnessing a remarkable surge in data availability across various domains, including medicine, education, policy-making, marketing, civics, and many more. This data deluge has created opportunities for developing intelligent systems capable of implementing highly precise and personalized decisions at unprecedented scales. Simultaneously, the application of machine learning in areas such as criminal justice and health care, which carry significant consequences for individuals, has prompted inquiries into the appropriate design of these systems to ensure alignment with our societal values. In this talk, I will use optimal transport (OT), which seeks the most efficient way of morphing one distribution into another one, as a tool to model and audit data-driven decision-making systems. First, we will see how OT gives rise to a rich class of data-driven distributionally robust optimization (DRO) models, which study worst-case risk minimization problems under distributional ambiguity. We will then shift our focus to an auditing perspective and see how OT can naturally facilitate a statistical test for the algorithmic fairness of pre-trained machine learning models. A significant yet unexplored aspect of OT is its computational complexity. Addressing this gap, we will see the computational complexity of generic OT problems. Later, we will see that even though generic OT problems are computationally hard, we can develop reliable data-driven decision-making models that are tractable in static and dynamic environments and would bring out-of-sample guarantees. In particular, we will see the optimality of linear policies in OT-based robust linear-quadratic control problems with imperfect state observations, and we will show that these policies can be computed efficiently using dynamic programming, Kalman filtering, and automatic differentiation.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EBahar Ta\u015fkesen is a 5th-year Ph.D. candidate in the Risk Analytics and Optimization Lab at the \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL) in Switzerland, under the supervision of Daniel Kuhn. She obtained her Bachelor\u0027s degree in Electrical and Electronics Engineering from Middle East Technical University in Ankara, Turkey, in 2018. Her research interests center around data-driven decision-making under uncertainty, large-scale stochastic optimization, and statistical inference. She is particularly interested in exploring algorithmic fairness and robustness and their applications in operations management, control, and machine learning. Her work has implications for the development and deployment of responsible AI systems.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EWe are witnessing a remarkable surge in data availability across various domains, including medicine, education, policy-making, marketing, civics, and many more. This data deluge has created opportunities for developing intelligent systems capable of implementing highly precise and personalized decisions at unprecedented scales. Simultaneously, the application of machine learning in areas such as criminal justice and health care, which carry significant consequences for individuals, has prompted inquiries into the appropriate design of these systems to ensure alignment with our societal values. In this talk, I will use optimal transport (OT), which seeks the most efficient way of morphing one distribution into another one, as a tool to model and audit data-driven decision-making systems. First, we will see how OT gives rise to a rich class of data-driven distributionally robust optimization (DRO) models, which study worst-case risk minimization problems under distributional ambiguity. We will then shift our focus to an auditing perspective and see how OT can naturally facilitate a statistical test for the algorithmic fairness of pre-trained machine learning models. A significant yet unexplored aspect of OT is its computational complexity. Addressing this gap, we will see the computational complexity of generic OT problems. Later, we will see that even though generic OT problems are computationally hard, we can develop reliable data-driven decision-making models that are tractable in static and dynamic environments and would bring out-of-sample guarantees. In particular, we will see the optimality of linear policies in OT-based robust linear-quadratic control problems with imperfect state observations, and we will show that these policies can be computed efficiently using dynamic programming, Kalman filtering, and automatic differentiation.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Reliable Data-driven Decision Making"}],"uid":"34977","created_gmt":"2023-11-20 13:04:36","changed_gmt":"2023-11-20 13:04:36","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-12-05T11:00:00-05:00","event_time_end":"2023-12-05T12:00:00-05:00","event_time_end_last":"2023-12-05T12:00:00-05:00","gmt_time_start":"2023-12-05 16:00:00","gmt_time_end":"2023-12-05 17:00:00","gmt_time_end_last":"2023-12-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671128":{"#nid":"671128","#data":{"type":"event","title":"ISyE Seminar - Mo\u00efse Blanchard ","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETitle:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EUniversal Learning for Decision-Making\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EWe provide general-use decision-making algorithms under provably minimal assumptions on the data, using the universal learning framework. Classically, learning guarantees typically require two types of assumptions: (1) restrictions on target policies to be learned and (2) assumptions on the data-generating process. Instead, we show that we can provide consistent algorithms with vanishing regret compared to the best policy in hindsight, (1) irrespective of the optimal policy, known as universal consistency, and (2) well beyond standard i.i.d. or stationary assumptions on the data. We present our results for the contextual bandit problem, where the learner\u0027s rewards depend on their selected actions and an observable context. This generalizes the standard multi-armed bandit to the case where side information is available, e.g., patients\u0027 records or customers\u0027 history, which allows for personalized treatment.\u0026nbsp;Precisely, we give necessary and sufficient conditions on the context-generating process for universal consistency to be possible. Surprisingly, for finite action spaces, universally learnable processes are the same for contextual bandits as for the supervised learning setting, suggesting that going from full feedback (supervised learning) to partial feedback (contextual bandits) came at no extra cost in terms of learnability.\u0026nbsp; We then show that there always exists an algorithm that guarantees universal consistency whenever this is achievable. In particular, such an algorithm is universally consistent under provably minimal assumptions: if it fails to be universally consistent for some context-generating process, then no other algorithm would succeed either. In the case of finite action spaces, this algorithm balances a fine trade-off between generalization (similar to structural risk minimization) and personalization (tailoring actions to specific contexts).\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBio: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EMo\u00efse Blanchard is a final year PhD student at MIT, working with Prof. Patrick Jaillet. He obtained his MSc in applied mathematics as valedictorian of Ecole Polytechnique. His research focuses on algorithms for decision-making and statistical learning. His work has been recognized with a best-student paper runner-up award at COLT and a best student paper award from the Informs TSL society.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EWe provide general-use decision-making algorithms under provably minimal assumptions on the data, using the universal learning framework. Classically, learning guarantees typically require two types of assumptions: (1) restrictions on target policies to be learned and (2) assumptions on the data-generating process. Instead, we show that we can provide consistent algorithms with vanishing regret compared to the best policy in hindsight, (1) irrespective of the optimal policy, known as universal consistency, and (2) well beyond standard i.i.d. or stationary assumptions on the data. We present our results for the contextual bandit problem, where the learner\u0027s rewards depend on their selected actions and an observable context. This generalizes the standard multi-armed bandit to the case where side information is available, e.g., patients\u0027 records or customers\u0027 history, which allows for personalized treatment.\u0026nbsp;Precisely, we give necessary and sufficient conditions on the context-generating process for universal consistency to be possible. Surprisingly, for finite action spaces, universally learnable processes are the same for contextual bandits as for the supervised learning setting, suggesting that going from full feedback (supervised learning) to partial feedback (contextual bandits) came at no extra cost in terms of learnability.\u0026nbsp; We then show that there always exists an algorithm that guarantees universal consistency whenever this is achievable. In particular, such an algorithm is universally consistent under provably minimal assumptions: if it fails to be universally consistent for some context-generating process, then no other algorithm would succeed either. In the case of finite action spaces, this algorithm balances a fine trade-off between generalization (similar to structural risk minimization) and personalization (tailoring actions to specific contexts).\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Universal Learning for Decision-Making"}],"uid":"34977","created_gmt":"2023-11-16 18:32:11","changed_gmt":"2023-11-16 18:36:19","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-12-07T11:00:00-05:00","event_time_end":"2023-12-07T12:00:00-05:00","event_time_end_last":"2023-12-07T12:00:00-05:00","gmt_time_start":"2023-12-07 16:00:00","gmt_time_end":"2023-12-07 17:00:00","gmt_time_end_last":"2023-12-07 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671055":{"#nid":"671055","#data":{"type":"event","title":"ISyE Seminar - Yeganeh Alimohammadi","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETitle: \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEpidemic Forecasting on Networks: Bridging Local Samples with Global Outcomes\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEpidemics of all kinds, from infectious diseases to technologies and ideas, spread through the hidden network of our social interactions. The structure of this underlying network determines the patterns of the epidemic spread, but mapping this network is expensive, and modeling it accurately is difficult.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, I will introduce a data-driven and model-free approach to predict the time evolution of epidemics that requires surprisingly few local network samples to forecast epidemic spread accurately. I will establish theoretical guarantees for the precision of our local estimator for a general class of networks, supporting these claims with concrete empirical evidence. The technical tools discussed in the talk can provide new perspectives on various applications of network data, beyond the scope of epidemics.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EYeganeh is a final-year Ph.D. candidate in Management Science and Engineering at Stanford University, where she is advised by Amin Saberi. During her PhD, she was also a research fellow at UC Berkeley\u0027s Simons Institute for the Theory of Computing. Her research focuses on analyzing large-scale networks and stochastic systems, employing tools from applied probability and algorithm design to address operations challenges.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEpidemics of all kinds, from infectious diseases to technologies and ideas, spread through the hidden network of our social interactions. The structure of this underlying network determines the patterns of the epidemic spread, but mapping this network is expensive, and modeling it accurately is difficult.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, I will introduce a data-driven and model-free approach to predict the time evolution of epidemics that requires surprisingly few local network samples to forecast epidemic spread accurately. I will establish theoretical guarantees for the precision of our local estimator for a general class of networks, supporting these claims with concrete empirical evidence. The technical tools discussed in the talk can provide new perspectives on various applications of network data, beyond the scope of epidemics.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Epidemic Forecasting on Networks: Bridging Local Samples with Global Outcomes"}],"uid":"34977","created_gmt":"2023-11-14 18:20:02","changed_gmt":"2023-11-14 19:44:49","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-28T11:00:00-05:00","event_time_end":"2023-11-28T12:00:00-05:00","event_time_end_last":"2023-11-28T12:00:00-05:00","gmt_time_start":"2023-11-28 16:00:00","gmt_time_end":"2023-11-28 17:00:00","gmt_time_end_last":"2023-11-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"671012":{"#nid":"671012","#data":{"type":"event","title":"SCL Course: Supply Chain Risk Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn today\u2019s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop a broader, more comprehensive understanding of how their company\u2019s supply chain may be at risk\u003C\/li\u003E\r\n\t\u003Cli\u003EMore effectively communicate to their company\u2019s stakeholders the realities of supply chain risks\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a cross-functional understanding of the building blocks for an effective Supply Chain Risk Management to be used in their particular business\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove their company\u2019s Supply Chain Risk Mitigation program\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe difference between crisis management and supply chain risk management\u003C\/li\u003E\r\n\t\u003Cli\u003EThe significant long term impact of supply chain disruptions\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy supply chain risk management activities require enterprise wide participation\u003C\/li\u003E\r\n\t\u003Cli\u003EHow companies can take proactive, actionable steps to add significant resiliency to their supply chain operation, often without requiring significant levels of investments\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn today\u2019s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2023-11-10 19:26:39","changed_gmt":"2023-11-10 19:27:24","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-04-11T08:00:00-04:00","event_time_end":"2024-04-12T13:00:00-04:00","event_time_end_last":"2024-04-12T13:00:00-04:00","gmt_time_start":"2024-04-11 12:00:00","gmt_time_end":"2024-04-12 17:00:00","gmt_time_end_last":"2024-04-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scrm","title":"Course webpage within the SCL website"},{"url":"https:\/\/pe.gatech.edu\/courses\/supply-chain-risk-management","title":"Course registration page"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670940":{"#nid":"670940","#data":{"type":"event","title":"2024 IISE Conference and Expo featuring Dr. Benoit Montreuil","body":[{"value":"\u003Cp\u003EMake plans now to join your colleagues from around the globe May 18-21, 2024, in Montreal, Canada, where you can stay on top of the profession with a power-packed educational program, get inspired by keynote speakers, participate in society and division town hall meetings, shop the exhibit hall and have plenty of networking opportunities with fellow attendees.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIISE honors also will be given to the top achievers in the profession, including the Frank \u0026amp; Lillian Gilbreth Industrial Engineering Award, the IISE Innovation Cup and more. Visit these Annual Conference pages often for developing conference content, activities, speakers and more.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/iise.confex.com\/iise\/2024\/cfp.cgi\u0022 target=\u0022_blank\u0022 title=\u0022Submit Your Abstract by Nov 17\u0022\u003E\u003Cstrong\u003ESubmit Your Abstract by Nov. 17\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs part of the program,\u0026nbsp;\u003Ca href=\u0022https:\/\/isye.gatech.edu\/users\/benoit-montreuil\u0022\u003E\u003Cstrong\u003EDr. Benoit Montreuil\u003C\/strong\u003E\u003C\/a\u003E, the Coca-Cola Material Handling and Distribution Chair Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, has been announced as the keynote speaker for the Institute of Industrial and Systems Engineering (IISE) 2024 Conference and Expo.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWidely considered the largest industrial and systems Engineering event of the year, the annual IISE conference attracts the participation of leading industry professionals.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp lang=\u0022EN-US\u0022\u003EWith various paper presentations from reputable teaching institutions worldwide, the IISE Conference is popular among students and faculty eager to present their research work.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn conjunction with his role as the chair professor, Dr. Montreuil holds pivotal positions as the Director of the \u003Ca href=\u0022https:\/\/picenter.gatech.edu\u0022\u003E\u003Cstrong\u003EPhysical Internet Center\u003C\/strong\u003E\u003C\/a\u003E and Executive Director of the \u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\u0022\u003ESupply Chain and Logistics Institute\u003C\/a\u003E\u003C\/strong\u003E.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Montreuil\u2019s prolific research endeavors center around the formulation of techniques, methodologies, and concepts for optimizing, transforming, and enabling businesses, supply chains, and value creation networks to excel in our dynamically evolving hyperconnected global landscape.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThroughout his\u0026nbsp;four decades of research, Dr. Montreuil is credited with introducing a set of paradigm-challenging leading-edge contributions that have and continue to reform the industrial engineering industry.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHaving contributed to and published more than 250 scientific publications and communications, Dr. Montreuil is a renowned industry professional, academician, and researcher who continues to transform and nurture the aspirations of future scholars and industry professionals.\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDr. Benoit Montreuil, the Coca-Cola Material Handling and Distribution Chair Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, has been announced as the keynote speaker for the Institute of Industrial and Systems Engineering (IISE) 2024 Conference and Expo.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Dr. Benoit Montreuil selected as Keynote Speaker"}],"uid":"27233","created_gmt":"2023-11-08 14:35:02","changed_gmt":"2023-11-09 20:26:03","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-05-18T08:00:00-04:00","event_time_end":"2024-05-21T17:00:00-04:00","event_time_end_last":"2024-05-21T17:00:00-04:00","gmt_time_start":"2024-05-18 12:00:00","gmt_time_end":"2024-05-21 21:00:00","gmt_time_end_last":"2024-05-21 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Montr\u00e9al Convention Centre (Montreal, CANADA)","extras":[],"hg_media":{"672299":{"id":"672299","type":"image","title":"2024 IISE Annual Conference \u0026 Expo","body":null,"created":"1699456390","gmt_created":"2023-11-08 15:13:10","changed":"1699456390","gmt_changed":"2023-11-08 15:13:10","alt":"2024 IISE Annual Conference \u0026 Expo banner with photo of Benoit Montreuil","file":{"fid":"255517","name":"IISE2024_BenoitMontreuil.jpg","image_path":"\/sites\/default\/files\/2023\/11\/08\/IISE2024_BenoitMontreuil_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/11\/08\/IISE2024_BenoitMontreuil_0.jpg","mime":"image\/jpeg","size":96673,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/11\/08\/IISE2024_BenoitMontreuil_0.jpg?itok=CESqO6-Q"}}},"media_ids":["672299"],"related_links":[{"url":"https:\/\/www.iise.org\/annual\/","title":"2024 IISE Conference and Expo website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"143871","name":"Physical Internet Center"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670948":{"#nid":"670948","#data":{"type":"event","title":"ISYE Statistic Seminar - Akshayaa Magesh","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Robust Multi-Hypothesis Testing with Moment-Constrained Uncertainty Sets\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Hypothesis testing is a fundamental problem in statistical decision-making, in which the goal is to decide between given hypotheses based on observed data. Detection problems have a wide range of applications in economics, communications, signal processing and life sciences. In general, the distributions under the hypotheses may be unknown, and may need to be estimated from historical data. However, deviations of the estimates from the true underlying distributions can result in significant performance degradation of the likelihood ratio test constructed using the estimated distributions. The robust hypothesis testing framework was proposed to address this problem. The problem of robust multi-hypothesis testing in the Bayesian setting is studied in this work. Under the m \u2265 2 hypotheses, the data-generating distributions are assumed to belong to uncertainty sets constructed through some moment functions; i.e., the sets contain distributions whose moments are centered around the empirical moments obtained from some training data sequences. The goal is to design a test that performs well under all distributions in the uncertainty sets, i.e., a test that minimizes the worst-case probability of error over the uncertainty sets. In the special case of binary hypothesis testing (m = 2), insights on the need for optimization-based approaches to solve the robust testing problem with moment constrained uncertainty sets are provided. Using these insights, the optimal test is obtained in the finite-alphabet case for multi-hypothesis testing. In the infinite-alphabet case, a tractable finite-dimension approximation is derived that converges to the optimal value of the original problem. A robust test is constructed for the entire alphabet from the solution of the approximation problem, and guarantees on the worst-case error of the proposed robust test over all distributions in the uncertainty sets are provided. To the best of our knowledge, ours is the first work to address the robust multi-hypothesis (m \u2265 2) testing setting. Numerical results demonstrate the performance of the proposed robust tests.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EAkshayaa Magesh is a final year PhD student at the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign (UIUC), advised by Prof. Venu Veeravalli. Her research interests include statistical inference, robust machine learning and reinforcement learning, and information theory. She is currently working on problems in uncertainty quantification, in particular on out-of-distribution detection, and on developing principled algorithms for inference robust to distribution shifts. Prior to this, she received her Masters degree from the University of Illinois Urbana-Champaign in 2020, and her Bachelors from the Indian Institute of Technology, Madras in 2018.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHypothesis testing is a fundamental problem in statistical decision-making, in which the goal is to decide between given hypotheses based on observed data. Detection problems have a wide range of applications in economics, communications, signal processing and life sciences. In general, the distributions under the hypotheses may be unknown, and may need to be estimated from historical data. However, deviations of the estimates from the true underlying distributions can result in significant performance degradation of the likelihood ratio test constructed using the estimated distributions. The robust hypothesis testing framework was proposed to address this problem. The problem of robust multi-hypothesis testing in the Bayesian setting is studied in this work. Under the m \u2265 2 hypotheses, the data-generating distributions are assumed to belong to uncertainty sets constructed through some moment functions; i.e., the sets contain distributions whose moments are centered around the empirical moments obtained from some training data sequences. The goal is to design a test that performs well under all distributions in the uncertainty sets, i.e., a test that minimizes the worst-case probability of error over the uncertainty sets. In the special case of binary hypothesis testing (m = 2), insights on the need for optimization-based approaches to solve the robust testing problem with moment constrained uncertainty sets are provided. Using these insights, the optimal test is obtained in the finite-alphabet case for multi-hypothesis testing. In the infinite-alphabet case, a tractable finite-dimension approximation is derived that converges to the optimal value of the original problem. A robust test is constructed for the entire alphabet from the solution of the approximation problem, and guarantees on the worst-case error of the proposed robust test over all distributions in the uncertainty sets are provided. To the best of our knowledge, ours is the first work to address the robust multi-hypothesis (m \u2265 2) testing setting. Numerical results demonstrate the performance of the proposed robust tests.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Robust Multi-Hypothesis Testing with Moment-Constrained Uncertainty Sets"}],"uid":"36433","created_gmt":"2023-11-08 16:13:39","changed_gmt":"2023-11-09 20:19:34","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-21T11:00:00-05:00","event_time_end":"2023-11-21T12:00:00-05:00","event_time_end_last":"2023-11-21T12:00:00-05:00","gmt_time_start":"2023-11-21 16:00:00","gmt_time_end":"2023-11-21 17:00:00","gmt_time_end_last":"2023-11-21 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670537":{"#nid":"670537","#data":{"type":"event","title":"SCL Course: Creating Business Value with Statistical Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. You\u2019ll learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. You\u2019ll use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand why and how to align Supply Chain Management (SCM) strategy with business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn statistics techniques as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand inventory management models and how to apply statistics techniques to them\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate time series forecasts based on SCM data\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to perform statistical analyses, create time series forecasts and visualize results\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe importance of aligning SCM and business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to ask the right business questions as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to use statistics to identify issues, compare data, and forecast decision outcomes\u003C\/li\u003E\r\n\t\u003Cli\u003EStatistical\u0026nbsp;concepts including variance analysis and hypothesis testing\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EApplying statistics to inventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques including time series forecasting\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models to improve operational performance metrics and align supply chain management with strategic business goals.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models."}],"uid":"27233","created_gmt":"2023-10-20 14:03:32","changed_gmt":"2023-11-09 16:41:03","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-03-04T13:00:00-05:00","event_time_end":"2024-03-07T17:00:00-05:00","event_time_end_last":"2024-03-07T17:00:00-05:00","gmt_time_start":"2024-03-04 18:00:00","gmt_time_end":"2024-03-07 22:00:00","gmt_time_end_last":"2024-03-07 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scabv","title":"Course detail within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670929":{"#nid":"670929","#data":{"type":"event","title":"ISYE Statistic Seminar - Minshuo Chen","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: Diffusion Models for Distribution Estimation and Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u0026nbsp;Diffusion models achieve state-of-the-art performance in various generation tasks. However, their theoretical foundations fall far behind. In this talk, we explore the methodology and theory of diffusion models, especially when data is supported on an unknown low-dimensional subspace. In the first part of the talk, we will introduce how diffusion models generate samples, and establish sample complexity bounds of diffusion models for learning nonparametric distributions. The obtained sample complexity depends on the data intrinsic dimension, implying that diffusion models can circumvent the curse of data ambient dimensionality. In the second part, we further consider directing diffusion models towards generating samples of desired properties as measured by an abstract reward function. We propose a learning-labeling-generating algorithm incorporating the reward as a guidance to the diffusion model. Theoretically, we show that in the offline setting, the generated samples under guidance provably improve the average reward and closely respect the data intrinsic structures. Empirically, we deploy our algorithm in vision and reinforcement learning tasks to support our theory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E: Minshuo Chen is a postdoctoral researcher in the Department of Electrical and Computer Engineering at Princeton University. He completed his Ph.D. from the School of Industrial and Systems Engineering at Georgia Tech, majoring in Machine Learning. Prior to that, he was a master student at UCLA and an undergraduate student at Zhejiang University. His research focuses on\u0026nbsp;developing principled methodologies and theoretical foundations of deep learning, with a particular interest in i)\u0026nbsp;approximation theory and statistical sample complexities, ii)\u0026nbsp;diffusion models, and iii)\u0026nbsp;reinforcement learning.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u0026nbsp;Diffusion models achieve state-of-the-art performance in various generation tasks. However, their theoretical foundations fall far behind. In this talk, we explore the methodology and theory of diffusion models, especially when data is supported on an unknown low-dimensional subspace. In the first part of the talk, we will introduce how diffusion models generate samples, and establish sample complexity bounds of diffusion models for learning nonparametric distributions. The obtained sample complexity depends on the data intrinsic dimension, implying that diffusion models can circumvent the curse of data ambient dimensionality. In the second part, we further consider directing diffusion models towards generating samples of desired properties as measured by an abstract reward function. We propose a learning-labeling-generating algorithm incorporating the reward as a guidance to the diffusion model. Theoretically, we show that in the offline setting, the generated samples under guidance provably improve the average reward and closely respect the data intrinsic structures. Empirically, we deploy our algorithm in vision and reinforcement learning tasks to support our theory.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Diffusion Models for Distribution Estimation and Optimization"}],"uid":"36433","created_gmt":"2023-11-07 18:29:01","changed_gmt":"2023-11-07 18:29:01","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-14T11:00:00-05:00","event_time_end":"2023-11-14T12:00:00-05:00","event_time_end_last":"2023-11-14T12:00:00-05:00","gmt_time_start":"2023-11-14 16:00:00","gmt_time_end":"2023-11-14 17:00:00","gmt_time_end_last":"2023-11-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670885":{"#nid":"670885","#data":{"type":"event","title":"ISYE Statistic Seminar - Bodhisattva Sen","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Extending the Scope of Nonparametric Empirical Bayes\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk we will describe two applications of empirical Bayes (EB) methodology. EB procedures estimate the prior probability distribution (in a Bayesian statistical model) from the data. In the first part we study the (Gaussian) signal plus noise model with multivariate, heteroscedastic errors. This model arises in many large-scale denoising problems (e.g., in astronomy). We consider the nonparametric maximum likelihood estimator (NPMLE) in this setting. We study the characterization, uniqueness, and computation of the NPMLE which estimates the unknown (arbitrary) prior by solving an infinite-dimensional convex optimization problem. The EB posterior means based on the NPMLE have low regret, meaning they closely target the oracle posterior means one would compute with the true prior in hand. We demonstrate the adaptive and near-optimal properties of the NPMLE for density estimation, denoising and deconvolution.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the second half of the talk, we consider the problem of Bayesian high dimensional regression where the regression coefficients are drawn i.i.d. from an unknown prior. To estimate this prior distribution, we propose and study a \u0022variational empirical Bayes\u0022 approach \u2014 it combines EB inference with a variational approximation (VA). The idea is to approximate the intractable marginal log-likelihood of the response vector --- also known as the \u0022evidence\u0022 --- by the evidence lower bound (ELBO) obtained from a naive mean field (NMF) approximation. We then maximize this lower bound over a suitable class of prior distributions in a computationally feasible way. We show that the marginal log-likelihood function can be (uniformly) approximated by its mean field counterpart. More importantly, under suitable conditions, we establish that this strategy leads to consistent approximation of the true posterior and provides asymptotically valid posterior inference for the regression coefficients.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBodhi Sen is a Professor of Statistics at Columbia\u0026nbsp;University, New York. He completed his Ph.D in Statistics from\u0026nbsp;University of Michigan,\u0026nbsp;Ann Arbor, in 2008. Prior to that, he was a student at the Indian\u0026nbsp;Statistical Institute, Kolkata, where he received his Bachelors (2002)\u0026nbsp;and Masters (2004) in Statistics. His core statistical research\u0026nbsp;centers around nonparametrics --- function estimation (with special\u0026nbsp;emphasis on shape constrained estimation), theory of optimal transport\u0026nbsp;and its applications to statistics, empirical Bayes procedures, kernel\u0026nbsp;methods, likelihood and bootstrap based inference, etc. He is also\u0026nbsp;actively involved in interdisciplinary research, especially in\u0026nbsp;astronomy.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nHis honors include the NSF CAREER award (2012), and the Young\u0026nbsp;Statistical Scientist Award (YSSA) in the Theory and Methods category\u0026nbsp;from the International Indian Statistical Association (IISA). He is an\u0026nbsp;elected fellow of the Institute of Mathematical Statistics (IMS).\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk we will describe two applications of empirical Bayes (EB) methodology. EB procedures estimate the prior probability distribution (in a Bayesian statistical model) from the data. In the first part we study the (Gaussian) signal plus noise model with multivariate, heteroscedastic errors. This model arises in many large-scale denoising problems (e.g., in astronomy). We consider the nonparametric maximum likelihood estimator (NPMLE) in this setting. We study the characterization, uniqueness, and computation of the NPMLE which estimates the unknown (arbitrary) prior by solving an infinite-dimensional convex optimization problem. The EB posterior means based on the NPMLE have low regret, meaning they closely target the oracle posterior means one would compute with the true prior in hand. We demonstrate the adaptive and near-optimal properties of the NPMLE for density estimation, denoising and deconvolution.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the second half of the talk, we consider the problem of Bayesian high dimensional regression where the regression coefficients are drawn i.i.d. from an unknown prior. To estimate this prior distribution, we propose and study a \u0022variational empirical Bayes\u0022 approach \u2014 it combines EB inference with a variational approximation (VA). The idea is to approximate the intractable marginal log-likelihood of the response vector --- also known as the \u0022evidence\u0022 --- by the evidence lower bound (ELBO) obtained from a naive mean field (NMF) approximation. We then maximize this lower bound over a suitable class of prior distributions in a computationally feasible way. We show that the marginal log-likelihood function can be (uniformly) approximated by its mean field counterpart. More importantly, under suitable conditions, we establish that this strategy leads to consistent approximation of the true posterior and provides asymptotically valid posterior inference for the regression coefficients.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Extending the Scope of Nonparametric Empirical Bayes"}],"uid":"36433","created_gmt":"2023-11-03 20:29:52","changed_gmt":"2023-11-03 20:29:52","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-07T11:00:00-05:00","event_time_end":"2023-11-07T12:00:00-05:00","event_time_end_last":"2023-11-07T12:00:00-05:00","gmt_time_start":"2023-11-07 16:00:00","gmt_time_end":"2023-11-07 17:00:00","gmt_time_end_last":"2023-11-07 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670856":{"#nid":"670856","#data":{"type":"event","title":"ISyE Seminar Speaker - Ebru Bish","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EPublic Health Screening: Challenges and Opportunities for Operations Researchers\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Screening for infectious diseases and genetic disorders is an important, and extensively used, public health tool. Early detection can improve clinical outcomes, and, for infectious diseases, reduce the disease spread, and is especially beneficial for diseases that have slow to develop and\/or initially non-specific symptoms. A major challenge is to design public health screening policies that can classify a large population, having different risk factors, in an accurate and equitable manner with limited resources and imperfect tests. My talk will draw upon the body of research that my collaborators and I have conducted over the years in a variety of screening contexts, ranging from newborn screening for genetic diseases, to population-level infectious disease screening, to donated blood screening for transfusion-transmissible infections. I will present an overview of this research area, discuss open research questions, provide several key models to optimize resource allocation in public health screening, and highlight the challenges and opportunities. \u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E I am a professor of operations management at the University of Alabama\u2019s Culverhouse College of Business; previously I was a faculty member at Virginia Tech\u2019s Department of Industrial and Systems Engineering. My research interests fall in the areas of data science and optimization, with focus on public health policy and healthcare systems management and optimization. My research has been published in leading operations research, biostatistics, and medical journals; recognized by various best paper awards from INFORMS and IISE; and supported by multiple grants from the National Science Foundation and the Agency for Healthcare Research and Quality. I have extensively collaborated with industry partners, with recent partners including the New York State Laboratory of Public Health, North Carolina State\u003Cbr \/\u003E\r\nLaboratory of Public Health, the American Red Cross, and the Carilion Clinic. I have graduated fourteen PhD students, many of whom hold academic positions; and I have served as the 2019 President of the INFORMS Health Applications Society.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPublic Health Screening: Challenges and Opportunities for Operations Researchers\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Public Health Screening: Challenges and Opportunities for Operations Researchers"}],"uid":"36374","created_gmt":"2023-11-02 16:41:26","changed_gmt":"2023-11-02 16:41:26","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-10T11:30:00-05:00","event_time_end":"2023-11-10T12:30:00-05:00","event_time_end_last":"2023-11-10T12:30:00-05:00","gmt_time_start":"2023-11-10 16:30:00","gmt_time_end":"2023-11-10 17:30:00","gmt_time_end_last":"2023-11-10 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670748":{"#nid":"670748","#data":{"type":"event","title":"ISyE Seminar Speaker - Dave Morton","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Modeling and computation in multi-stage stochastic programming\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; We discuss recent advances in modeling and computation for time-dynamic optimization under uncertainty via multi-stage stochastic programming. We discuss three modeling ideas, and associated computational tools, that move multi-stage stochastic programming closer to a class of continuous-action continuous-state Markov decision processes. We also point to gaps. This is joint work with Oscar Dowson and Bernardo Pagnoncelli.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio\u003C\/strong\u003E sketch: David Morton is the Walter P. Murphy Professor in IEMS at Northwestern University. Previously, he was on the faculty in ORIE at UT-Austin, worked as a Fulbright Scholar at Charles University in Prague, and was a postdoc in the OR Department at the Naval Postgraduate School. His research interests include stochastic and large-scale optimization with applications in public health, energy systems, and security.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cblockquote\u003E\r\n\u003Cp\u003EWe discuss recent advances in modeling and computation for time-dynamic optimization under uncertainty via multi-stage stochastic programming. We discuss three modeling ideas, and associated computational tools, that move multi-stage stochastic programming closer to a class of continuous-action continuous-state Markov decision processes. We also point to gaps. This is joint work with Oscar Dowson and Bernardo Pagnoncelli.\u0026nbsp;\u003C\/p\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/blockquote\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Modeling and computation in multi-stage stochastic programming"}],"uid":"36374","created_gmt":"2023-10-29 23:06:48","changed_gmt":"2023-11-02 16:20:49","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-03T11:30:00-04:00","event_time_end":"2023-11-03T12:30:00-04:00","event_time_end_last":"2023-11-03T12:30:00-04:00","gmt_time_start":"2023-11-03 15:30:00","gmt_time_end":"2023-11-03 16:30:00","gmt_time_end_last":"2023-11-03 16:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670444":{"#nid":"670444","#data":{"type":"event","title":"Health Systems: The Next Generation 2023 Forum","body":[{"value":"\u003Cp\u003EThis Forum provides a platform for thought leaders and field experts with local and global perspectives and knowledge. The impact of the discussions and collaborations range from local initiatives to advance healthcare systems right here in Atlanta to broader impact across the country and beyond.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESince its inauguration in 2016, the Forum has annually brought together 120+ professionals, students and scholars from across the fields of healthcare delivery, operations and education focused on promoting and maintaining wellness by identifying important trends in healthcare system applications and designs, opportunities for collaboration, and the future of health systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EOur theme this year:\u003C\/strong\u003E\u0026nbsp;The Power of Interdisciplinary Collaboration to Enhance Health and Well-being of People and Communities\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EPlease visit the \u003Cstrong\u003E\u003Ca href=\u0022https:\/\/sites.gatech.edu\/hsng2023\/\u0022\u003EForum website\u003C\/a\u003E\u003C\/strong\u003E for\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E \u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/sites.gatech.edu\/hsng2023\/registration\/\u0022\u003EREGISTRATION\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E \u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Eand\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E \u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/sites.gatech.edu\/hsng2023\/call-for-presentation-and-posters\/\u0022\u003EPOSTER SUBMISSIONS\u003C\/a\u003E\u003C\/span\u003E\u003C\/strong\u003E. \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/sites.gatech.edu\/hsng2023\/agenda\/\u0022\u003EAgenda\u003C\/a\u003E\u003C\/strong\u003E\u0026nbsp;\u003Cspan\u003Eincludes Rapid-fire Presentations, Posters, and Interactive Lunch\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Forum provides a platform for thought leaders and field experts with local and global perspectives and knowledge. The impact of the discussions and collaborations range from local initiatives to advance healthcare systems right here in Atlanta to broader impact across the country and beyond.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"An annual Forum organized by The Georgia Tech Center for Health and Humanitarian Systems (CHHS)."}],"uid":"27233","created_gmt":"2023-10-16 18:03:54","changed_gmt":"2023-10-27 15:57:06","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-31T10:00:00-04:00","event_time_end":"2023-10-31T15:00:00-04:00","event_time_end_last":"2023-10-31T15:00:00-04:00","gmt_time_start":"2023-10-31 14:00:00","gmt_time_end":"2023-10-31 19:00:00","gmt_time_end_last":"2023-10-31 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech Exhibition Hall","extras":["free_food","freebies"],"hg_media":{"672186":{"id":"672186","type":"image","title":"2023_HSNG.jpg","body":null,"created":"1698343283","gmt_created":"2023-10-26 18:01:23","changed":"1698343283","gmt_changed":"2023-10-26 18:01:23","alt":"Join us October 31 for Health Systems: The Next Generation 2023","file":{"fid":"255379","name":"2023_HSNG.jpg","image_path":"\/sites\/default\/files\/2023\/10\/26\/2023_HSNG_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/10\/26\/2023_HSNG_0.jpg","mime":"image\/jpeg","size":291159,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/10\/26\/2023_HSNG_0.jpg?itok=4FWhWJs1"}}},"media_ids":["672186"],"related_links":[{"url":"http:\/\/sites.gatech.edu\/hsng2023\/","title":"Register Now for Free"},{"url":"http:\/\/sites.gatech.edu\/hsng2023\/posters","title":"Submit a poster abstract By October 30, 3pm ET!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"398","name":"health"},{"id":"121981","name":"healthtech"},{"id":"1129","name":"healthcare"},{"id":"182682","name":"publichealth"},{"id":"182683","name":"healthsystems"},{"id":"167243","name":"systems"},{"id":"516","name":"engineering"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1789","name":"Conference\/Symposium"},{"id":"1788","name":"Other\/Miscellaneous"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EQuestions? Email\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670581":{"#nid":"670581","#data":{"type":"event","title":"ISyE Seminar Speaker - Nan Kong","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELearning public health systems: how data-driven optimization can help them?\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAgency for Healthcare Research and Quality (AHRQ) defines a learning health system as a health system in which internal data and experience are systematically integrated with external evidence, and that knowledge is put into practice. As a result, patients get higher quality, safer care, health care is delivered more efficiently, cost-effectively, and in a patient-centered manner, and health care organizations become better places to work. Becoming a learning health system is increasingly an imperative in an era of health system transformation. There is growing recognition that \u201cbusiness as usual\u201d is no longer a sustainable model. Among the many challenges in helping health systems learn is effective use of data. This becomes more prevalent as we come out from the COVID-19 pandemic. How data-driven optimization can help?\u003Cbr \/\u003E\r\nIn this talk, we investigate its application in learning public health systems where online learning has become widely available with increasing implementation of point-of-care sensing devices and increasing understanding of controlled disease transmission mechanisms. We consider the context of multi-period location-specific resource allocation in epidemic outbreak control. We formalize the decision problem within the mathematical framework of stochastic dynamic optimization with mixed observability on system states and indeterminate parameters of the system dynamics model. We present two recent studies. In the first study, for an emerging cholera outbreak, we formulate the problem via nonlinear optimization on an ordinary-differential-equation model that governs location-specific transmission dynamics. We propose a data-driven optimization approach to determine the optimal strategy of intervention resource allocation at each period and each community in a rolling-horizon manner. At each period, we integrate single-period model parameter fitting and scenario-based stochastic programming to make decisions under uncertainty with newly acquired observational data in the system. In the second study, for the COVID-19 outbreak, we formulate the problem via mixed observability Markov decision processes under time-varying interval-valued parameters. We propose a novel transfer reinforcement learning based algorithmic approach, which integrates transfer learning into deep reinforcement learning in an offline-online scheme, to determine the optimal strategy of joint screening-intervention resource allocation at each period and each community. To accelerate the online re-optimization, we pre-train a collection of promising networks and fine-tune them with newly acquired observational data. The hallmark of our approach comes from combining the strong approximation ability of neural networks with the high flexibility of transfer learning through efficiently adapting the previously learned policy to changes in system dynamics. Our studies offer viable data-driven solutions to problems requiring \u201clearning while optimization\u201d, which can further nourish the application of OR\/MS in learning public health systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nDr. Nan Kong is Professor and Interim Head of the Weldon School of Biomedical Engineering at Purdue University. He is a Full Member affiliated with the Purdue Regenstrief Center for Healthcare Engineering and was the center\u2019s former Associate Director for Health Systems. He graduated with a B.S. degree in Automation from Tsinghua University, China, in 1999 and a Ph.D. degree in Industrial Engineering from the University of Pittsburgh in 2006. He joined the BME faculty at Purdue in August 2007. His research is primarily focused on innovating data-driven analytics techniques and developing user-centered tools to address challenges arising in healthcare systems, particularly those related to system operations. He has published close to 100 peer-reviewed articles. His research has been funded by NSF, NIH, AHRQ, and AFSOR. He was the Program Chair of the 2021 Institute for Operations Research and the Management Science (INFORMS) Healthcare Conference. He recently won the 2nd-Place in the national competition \u201cBuilding Bridges to Better Health: A Primary Health Care Challenge, supported by Department of Health \u0026amp; Human Sciences \u2013 Healthcare Resources and Services Administration.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAgency for Healthcare Research and Quality (AHRQ) defines a learning health system as a health system in which internal data and experience are systematically integrated with external evidence, and that knowledge is put into practice. As a result, patients get higher quality, safer care, health care is delivered more efficiently, cost-effectively, and in a patient-centered manner, and health care organizations become better places to work. Becoming a learning health system is increasingly an imperative in an era of health system transformation. There is growing recognition that \u201cbusiness as usual\u201d is no longer a sustainable model. Among the many challenges in helping health systems learn is effective use of data. This becomes more prevalent as we come out from the COVID-19 pandemic. How data-driven optimization can help?\u003Cbr \/\u003E\r\nIn this talk, we investigate its application in learning public health systems where online learning has become widely available with increasing implementation of point-of-care sensing devices and increasing understanding of controlled disease transmission mechanisms. We consider the context of multi-period location-specific resource allocation in epidemic outbreak control. We formalize the decision problem within the mathematical framework of stochastic dynamic optimization with mixed observability on system states and indeterminate parameters of the system dynamics model. We present two recent studies. In the first study, for an emerging cholera outbreak, we formulate the problem via nonlinear optimization on an ordinary-differential-equation model that governs location-specific transmission dynamics. We propose a data-driven optimization approach to determine the optimal strategy of intervention resource allocation at each period and each community in a rolling-horizon manner. At each period, we integrate single-period model parameter fitting and scenario-based stochastic programming to make decisions under uncertainty with newly acquired observational data in the system. In the second study, for the COVID-19 outbreak, we formulate the problem via mixed observability Markov decision processes under time-varying interval-valued parameters. We propose a novel transfer reinforcement learning based algorithmic approach, which integrates transfer learning into deep reinforcement learning in an offline-online scheme, to determine the optimal strategy of joint screening-intervention resource allocation at each period and each community. To accelerate the online re-optimization, we pre-train a collection of promising networks and fine-tune them with newly acquired observational data. The hallmark of our approach comes from combining the strong approximation ability of neural networks with the high flexibility of transfer learning through efficiently adapting the previously learned policy to changes in system dynamics. Our studies offer viable data-driven solutions to problems requiring \u201clearning while optimization\u201d, which can further nourish the application of OR\/MS in learning public health systems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learning public health systems: how data-driven optimization can help them?"}],"uid":"36374","created_gmt":"2023-10-23 13:53:50","changed_gmt":"2023-10-23 13:53:50","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-27T11:30:00-04:00","event_time_end":"2023-10-27T12:30:00-04:00","event_time_end_last":"2023-10-27T12:30:00-04:00","gmt_time_start":"2023-10-27 15:30:00","gmt_time_end":"2023-10-27 16:30:00","gmt_time_end_last":"2023-10-27 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660545":{"#nid":"660545","#data":{"type":"event","title":"SCL Course: Machine Learning Applications for Supply Chain Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the third in the four-course Supply Chain Analytics Professional certificate program. It introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You\u2019ll use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. You\u2019ll use Python and PowerBI to create and analyze regression, clustering, and classification models.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed\u0026nbsp;before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the role of machine learning (ML) in Supply Chain Management (SCM)\u003C\/li\u003E\r\n\t\u003Cli\u003EApply advanced analytics techniques to build planning tools that can leverage large and real-time data sets\u003C\/li\u003E\r\n\t\u003Cli\u003EApply ML in demand forecasting and predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how to assess ML model performance, improve models, and pick the best model for a decision\u003C\/li\u003E\r\n\t\u003Cli\u003EUse Python and PowerBI to build, analyze, and deploy ML models\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow ML relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EML algorithms such as regression trees, clustering techniques, decision trees, random forests, logistic regression\u003C\/li\u003E\r\n\t\u003Cli\u003EAspects of ML projects including parameter tuning, cross validation, and assess model performance\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in demand forecasting for sales and operations planning (S\u0026amp;OP) and inventory management\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAn introduction to\u0026nbsp;the field of machine learning as it applies to supply chain management. You\u2019ll then use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance."}],"uid":"27233","created_gmt":"2022-08-25 16:17:48","changed_gmt":"2023-10-20 19:36:19","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-16T13:00:00-04:00","event_time_end":"2023-10-19T17:00:00-04:00","event_time_end_last":"2023-10-19T17:00:00-04:00","gmt_time_start":"2023-10-16 17:00:00","gmt_time_end":"2023-10-19 21:00:00","gmt_time_end_last":"2023-10-19 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaml","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670540":{"#nid":"670540","#data":{"type":"event","title":"SCL Course: Machine Learning Applications for Supply Chain Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the third in the four-course Supply Chain Analytics Professional certificate program. It introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You\u2019ll use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. You\u2019ll use Python and PowerBI to create and analyze regression, clustering, and classification models.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed\u0026nbsp;before the first day of the course. An optional pre-course webinar is typically held the Thursday\u0026nbsp;before the course start date (July 6).\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the role of machine learning (ML) in Supply Chain Management (SCM)\u003C\/li\u003E\r\n\t\u003Cli\u003EApply advanced analytics techniques to build planning tools that can leverage large and real-time data sets\u003C\/li\u003E\r\n\t\u003Cli\u003EApply ML in demand forecasting and predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how to assess ML model performance, improve models, and pick the best model for a decision\u003C\/li\u003E\r\n\t\u003Cli\u003EUse Python and PowerBI to build, analyze, and deploy ML models\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow ML relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EML algorithms such as regression trees, clustering techniques, decision trees, random forests, logistic regression\u003C\/li\u003E\r\n\t\u003Cli\u003EAspects of ML projects including parameter tuning, cross validation, and assess model performance\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in demand forecasting for sales and operations planning (S\u0026amp;OP) and inventory management\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAn introduction to\u0026nbsp;the field of machine learning as it applies to supply chain management. You\u2019ll then use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance."}],"uid":"27233","created_gmt":"2023-10-20 14:40:20","changed_gmt":"2023-10-20 18:58:29","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-05-13T13:00:00-04:00","event_time_end":"2024-05-17T17:00:00-04:00","event_time_end_last":"2024-05-17T17:00:00-04:00","gmt_time_start":"2024-05-13 17:00:00","gmt_time_end":"2024-05-17 21:00:00","gmt_time_end_last":"2024-05-17 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaml","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670541":{"#nid":"670541","#data":{"type":"event","title":"SCL Course: Supply Chain Optimization and Prescriptive Analytics (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u2019ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUse mathematical optimization to transform Supply Chain Management (SCM) processes.\u003C\/li\u003E\r\n\t\u003Cli\u003EApply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize PowerBI and Python in optimization projects.\u003C\/li\u003E\r\n\t\u003Cli\u003EParticipate in a hackathon that pulls together everything learned throughout the certificate program.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ERole of mathematical optimization in addressing complex SCM challenges \u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAppropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation of production processes, distribution networks, and routes using optimization\u003C\/li\u003E\r\n\t\u003Cli\u003EAbility to pull together all content of the certificate program into a prescriptive analytics project\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn advanced analytics and mathematical optimization to find solutions for supply chain problems.\u0026nbsp;The course also serves as a capstone for the Supply Chain Analytics Professional certificate program\u0026nbsp;by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn advanced analytics and mathematical optimization to find solutions for supply chain problems."}],"uid":"27233","created_gmt":"2023-10-20 14:52:27","changed_gmt":"2023-10-20 14:54:22","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-09-16T13:00:00-04:00","event_time_end":"2024-09-19T17:00:00-04:00","event_time_end_last":"2024-09-19T17:00:00-04:00","gmt_time_start":"2024-09-16 17:00:00","gmt_time_end":"2024-09-19 21:00:00","gmt_time_end_last":"2024-09-19 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaoc","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670536":{"#nid":"670536","#data":{"type":"event","title":"SCL Course: Transforming Supply Chain Management and Performance Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in the four-course Supply Chain Analytics Professional certificate program. It prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. You\u2019ll learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the most relevant planning challenges across the strategic, tactical, and operational levels of supply chains\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the difference between analytics types, the links between them, and how to best use them to improve\u0026nbsp;supply chain management (SCM)\u0026nbsp;processes\u003C\/li\u003E\r\n\t\u003Cli\u003EUse\u0026nbsp;Key Performance Indicators (KPIs)\u0026nbsp;to find causes of underperformance in supply chains and to plan for analytics projects that will address strategic SCM goals\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to understand, visualize, and analyze data in order to prepare for deeper analytics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe role of analytics in SCM\u003C\/li\u003E\r\n\t\u003Cli\u003ETypes of analytics (descriptive, diagnostic, predictive, and prescriptive) and the relationships between them\u003C\/li\u003E\r\n\t\u003Cli\u003EPreprocessing (cleaning and integrating) data as it relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EConducting exploratory data analysis on supply chain data\u003C\/li\u003E\r\n\t\u003Cli\u003EBest practices for visualizing data and building dashboards\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentifying and analyzing KPIs of SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to apply leading-edge analytical methods and technology enablers across the supply chain"}],"uid":"27233","created_gmt":"2023-10-20 13:55:45","changed_gmt":"2023-10-20 13:57:58","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-22T13:00:00-05:00","event_time_end":"2024-01-25T17:00:00-05:00","event_time_end_last":"2024-01-25T17:00:00-05:00","gmt_time_start":"2024-01-22 18:00:00","gmt_time_end":"2024-01-25 22:00:00","gmt_time_end_last":"2024-01-25 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scapa","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670394":{"#nid":"670394","#data":{"type":"event","title":"ISyE Seminar Speaker - Simge Kucukyavuz","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Mixed-Integer Programming Approaches to Generalized Submodular Optimization and its Applications\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003ESubmodularity is an important concept in integer and combinatorial optimization. A classical submodular set function models the utility of selecting homogenous items from a single ground set, and such selections can be represented by binary variables. In practice, many problem contexts involve choosing heterogeneous items from more than one ground set or selecting multiple copies of homogenous items, which call for extensions of submodularity. We refer to the optimization problems associated with such generalized notions of submodularity as Generalized Submodular Optimization (GSO). GSO is found in wide-ranging applications, including infrastructure design, healthcare, online marketing, and machine learning. Due to the often highly nonlinear (even non-convex and non-concave) objective function and the mixed-integer decision space, GSO is a broad subclass of challenging mixed-integer nonlinear programming problems. In this talk, we first provide an overview of classical submodularity. Then we introduce two subclasses of GSO, for which we present polyhedral theory for the mixed-integer set structures that arise from these problem classes. Our theoretical results lead to efficient and versatile exact solution methods that demonstrate their effectiveness in practical problems using real-world datasets. This is joint work with\u0026nbsp;Qimeng (Kim) Yu.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003ESimge K\u00fc\u00e7\u00fckyavuz is Chair and David A. and Karen Richards Sachs Professor in the Industrial Engineering and Management Sciences Department at Northwestern University. She is an expert in mixed-integer, large-scale, and stochastic optimization. Her methodologies have applications in complex computational problems across numerous domains, including social networks, computing and energy infrastructure, statistical learning, and logistics. Her research has been supported by multiple grants from the National Science Foundation (NSF) and the Office of Naval Research. She is the recipient of the NSF CAREER Award and the INFORMS Computing Society (ICS) Prize. She is the past chair of ICS and serves on the editorial boards of Mathematics of Operations Research, Mathematical Programming, SIAM Journal on Optimization, and MOS-SIAM Optimization Book Series. She received her Ph.D. in Industrial Engineering and Operations Research from the University of California, Berkeley.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESubmodularity is an important concept in integer and combinatorial optimization. A classical submodular set function models the utility of selecting homogenous items from a single ground set, and such selections can be represented by binary variables. In practice, many problem contexts involve choosing heterogeneous items from more than one ground set or selecting multiple copies of homogenous items, which call for extensions of submodularity. We refer to the optimization problems associated with such generalized notions of submodularity as Generalized Submodular Optimization (GSO). GSO is found in wide-ranging applications, including infrastructure design, healthcare, online marketing, and machine learning. Due to the often highly nonlinear (even non-convex and non-concave) objective function and the mixed-integer decision space, GSO is a broad subclass of challenging mixed-integer nonlinear programming problems. In this talk, we first provide an overview of classical submodularity. Then we introduce two subclasses of GSO, for which we present polyhedral theory for the mixed-integer set structures that arise from these problem classes. Our theoretical results lead to efficient and versatile exact solution methods that demonstrate their effectiveness in practical problems using real-world datasets. This is joint work with\u0026nbsp;Qimeng (Kim) Yu.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" Mixed-Integer Programming Approaches to Generalized Submodular Optimization and its Applications"}],"uid":"36374","created_gmt":"2023-10-12 17:42:01","changed_gmt":"2023-10-12 17:42:01","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-20T11:30:00-04:00","event_time_end":"2023-10-20T12:30:00-04:00","event_time_end_last":"2023-10-20T12:30:00-04:00","gmt_time_start":"2023-10-20 15:30:00","gmt_time_end":"2023-10-20 16:30:00","gmt_time_end_last":"2023-10-20 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670351":{"#nid":"670351","#data":{"type":"event","title":"Speed Interviewing with the ISyE Advisory Board","body":[{"value":"\u003Cp\u003EJoin ISyE Advisory Board Members to polish your interview skills and discuss potential career paths!\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEach student will be able to spend time with multiple Advisory Board members from various fields: Consulting, Private Equity, Entrepreneurship, D\u0026amp;A, Finance, and more!\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease RSVP by October 19, 2023\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESpeed Interviewing with the ISyE Advisory Board\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Speed Interviewing with the ISyE Advisory Board"}],"uid":"27764","created_gmt":"2023-10-11 19:18:03","changed_gmt":"2023-10-11 19:44:27","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-26T18:30:00-04:00","event_time_end":"2023-10-26T20:00:00-04:00","event_time_end_last":"2023-10-26T20:00:00-04:00","gmt_time_start":"2023-10-26 22:30:00","gmt_time_end":"2023-10-27 00:00:00","gmt_time_end_last":"2023-10-27 00:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Atrium","extras":[],"hg_media":{"672011":{"id":"672011","type":"image","title":"image004.png","body":null,"created":"1697053402","gmt_created":"2023-10-11 19:43:22","changed":"1697053402","gmt_changed":"2023-10-11 19:43:22","alt":"invite, same as details in the body","file":{"fid":"255187","name":"image004.png","image_path":"\/sites\/default\/files\/2023\/10\/11\/image004.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/10\/11\/image004.png","mime":"image\/png","size":510745,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/10\/11\/image004.png?itok=7tpVPhLv"}}},"media_ids":["672011"],"related_links":[{"url":"https:\/\/eforms.isye.gatech.edu\/form\/isye-ab-speed-networking-event","title":"RSVP For Event"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/user\/838\/contact\u0022\u003EDonald Phan\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"670324":{"#nid":"670324","#data":{"type":"event","title":"ISYE Statistic Seminar - Dr. William Lewis","body":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;Advances and opportunities for data-driven design and analysis of experiments at Sandia\u2019s Z Pulsed Power Facility\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp;Sandia\u2019s Z machine is the world\u2019s largest pulsed power facility, capable of compressing electrical current in space and time to deliver over 20 million amperes of peak current with O(100ns) rise time to a variety of targets for high- energy density science experiments. Due to the extreme environments created, relatively rare nature of experiments, and costly multi-physics simulation tools used for design, it is critical that data-driven methods are increasingly being incorporated in the full experiment lifecycle. In this seminar, I will cover sufficient background on the Z machine and the Magnetized Liner Inertial Fusion (MagLIF) concept to introduce several challenges for problems ranging from design to analysis of experiments. I will present several exemplars for the MagLIF platform that utilize machine learning and statistical methods to address many of these challenges. This will include work from a recently concluded laboratory directed research and development project in collaboration with Professor Roshan Joseph at the Georgia Institute of Technology H. Milton Stewart School of Industrial and Systems Engineering. I will conclude by highlighting additional areas of interest for further growth of data science and means for collaboration within the Pulsed Power center at Sandia.\u0026nbsp;SAND2023-10723A\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u0026nbsp;Dr. William Lewis is a physicist and applied data scientist in the radiation \u0026amp; ICF target design group in Sandia\u2019s Pulsed Power Sciences Center. He received a BS in Physics and Mathematics in 2012 from the University of Arkansas, where he conducted research in theoretical laser physics. He went on to obtain an MS in 2015 working in the field of experimental nano-spectroscopy and a Ph.D. in 2018 studying transport theory of strongly interacting cold quantum gases, both from the University of Colorado Boulder. William joined Sandia as a postdoctoral researcher in June of 2019. During his tenure as a postdoc, he applied a variety of data-driven methods including Bayesian statistics and machine-learning to significantly improve understanding of the conditions produced in pulsed power inertial confinement fusion (ICF) experiments. William converted to permanent staff in December 2021. As a staff member, he has continued to develop and regularly publish methods allowing for large-scale surveys of experimental and simulation based ICF data.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESandia\u2019s Z machine is the world\u2019s largest pulsed power facility, capable of compressing electrical current in space and time to deliver over 20 million amperes of peak current with O(100ns) rise time to a variety of targets for high- energy density science experiments. Due to the extreme environments created, relatively rare nature of experiments, and costly multi-physics simulation tools used for design, it is critical that data-driven methods are increasingly being incorporated in the full experiment lifecycle. In this seminar, I will cover sufficient background on the Z machine and the Magnetized Liner Inertial Fusion (MagLIF) concept to introduce several challenges for problems ranging from design to analysis of experiments. I will present several exemplars for the MagLIF platform that utilize machine learning and statistical methods to address many of these challenges. This will include work from a recently concluded laboratory directed research and development project in collaboration with Professor Roshan Joseph at the Georgia Institute of Technology H. Milton Stewart School of Industrial and Systems Engineering. I will conclude by highlighting additional areas of interest for further growth of data science and means for collaboration within the Pulsed Power center at Sandia.\u0026nbsp;SAND2023-10723A\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Advances and opportunities for data-driven design and analysis of experiments at Sandia\u2019s Z Pulsed Power Facility"}],"uid":"36433","created_gmt":"2023-10-10 18:07:00","changed_gmt":"2023-10-10 18:38:06","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-24T11:00:00-04:00","event_time_end":"2023-10-24T12:00:00-04:00","event_time_end_last":"2023-10-24T12:00:00-04:00","gmt_time_start":"2023-10-24 15:00:00","gmt_time_end":"2023-10-24 16:00:00","gmt_time_end_last":"2023-10-24 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"670102":{"#nid":"670102","#data":{"type":"event","title":"ISyE Seminar Speaker - Rui Gao","body":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMultistage Distributionally Robust Optimization with Nested Distance\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;In this talk, I will discuss multistage distributionally robust optimization, where the uncertainty set is a ball of distributions defined through the nested distance (Pflug and Pichler 2012). This choice of uncertainty set, as opposed to alternatives like the Wasserstein distance between stochastic processes, takes into account information evolution, making it hedge against a plausible family of data processes. First, I will present a recursive reformulation to evaluate the worst-case risk of any given random sequence and explore the intricacies of time consistency in dynamic risk measures. Next, I will present dynamic programming reformulations for finding the optimal policy in the linear and stagewise-independent setting with objective \/ right-hand side uncertainty.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERui Gao is an Assistant Professor in the Department of Information, Risk, and Operations Management at the McCombs School of Business at the University of Texas at Austin. He received a Ph.D. in Operations Research from Georgia Institute of Technology in 2018, and a B.Sc. in Mathematics and Applied Mathematics from Xi\u0027an Jiaotong University in 2013.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERui\u0027s main research studies data-driven decision-making under uncertainty and prescriptive data analytics. His research has been recognized with several INFORMS paper competition awards, including Winner in Junior Faculty Interest Group Paper Competition (2020), Winner in Data Mining Best Paper Award (2017), Runner-up in Computing Society Student Paper Award (2017), and Finalist in George Nicholson Student Paper Competition (2016). He currently serves as an Associate Editor for Mathematical Programming.\u003C\/p\u003E\r\n\r\n\u003Ch2\u003EEducation\u003C\/h2\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.gatech.edu\/\u0022\u003EGeorgia Institute of Technology\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003ESchool of Industrial and Systems Engineering\u003C\/a\u003E, 2013-2018\u003C\/p\u003E\r\n\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003E\r\n\t\t\u003Cp\u003EPh.D. in\u0026nbsp;\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/academics\/doctoral\/operations-research\u0022\u003EOperations Research\u003C\/a\u003E\u003C\/p\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\t\u003Cli\u003E\r\n\t\t\u003Cp\u003EAdvisor:\u0026nbsp;\u003Ca href=\u0022https:\/\/sites.gatech.edu\/anton-kleywegt\/\u0022\u003EAnton J. Kleywegt\u003C\/a\u003E\u003C\/p\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Ca href=\u0022http:\/\/en.xjtu.edu.cn\/\u0022\u003EXi\u2019an Jiaotong University\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022http:\/\/math.xjtu.edu.cn\/Home.htm\u0022\u003ESchool of Mathematics and Statistics\u003C\/a\u003E, China, 2009-2013\u003C\/p\u003E\r\n\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003E\r\n\t\t\u003Cp\u003EB.Sc. in Mathematics and Applied Mathematics (Honors Program)\u003C\/p\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\t\u003Cli\u003E\r\n\t\t\u003Cp\u003ESpecial Class for the Gifted Young (2007-2009)\u003C\/p\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch2\u003EProfessional Employment\u003C\/h2\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.sas.com\/en_us\/home.html\u0022\u003ESAS Institute Inc.\u003C\/a\u003E, Advanced Analytics R\u0026amp;D, Raleigh-Durham, NC, 2016\u003C\/p\u003E\r\n\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003E\r\n\t\t\u003Cp\u003ERevenue Management and Price Optimization Summer Fellow\u003C\/p\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn this talk, I will discuss multistage distributionally robust optimization, where the uncertainty set is a ball of distributions defined through the nested distance (Pflug and Pichler 2012). This choice of uncertainty set, as opposed to alternatives like the Wasserstein distance between stochastic processes, takes into account information evolution, making it hedge against a plausible family of data processes. First, I will present a recursive reformulation to evaluate the worst-case risk of any given random sequence and explore the intricacies of time consistency in dynamic risk measures. Next, I will present dynamic programming reformulations for finding the optimal policy in the linear and stagewise-independent setting with objective \/ right-hand side uncertainty.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Multistage Distributionally Robust Optimization with Nested Distance"}],"uid":"36374","created_gmt":"2023-10-02 15:50:37","changed_gmt":"2023-10-02 15:50:37","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-06T11:30:00-04:00","event_time_end":"2023-10-06T12:30:00-04:00","event_time_end_last":"2023-10-06T12:30:00-04:00","gmt_time_start":"2023-10-06 15:30:00","gmt_time_end":"2023-10-06 16:30:00","gmt_time_end_last":"2023-10-06 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669137":{"#nid":"669137","#data":{"type":"event","title":"LeeAnn and Walter Muller Distinguished Lecture Series | Ann Dunkin","body":[{"value":"\u003Cp lang=\u0022EN-US\u0022\u003E\u003Cstrong\u003ELecture Title: Modeling for Energy Resilience | How DOE uses simulation to model and manage everything from the power grid to the strategic petroleum reserve.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EModeling for Energy Resilience | How DOE uses simulation to model and manage everything from the power grid to the strategic petroleum reserve.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe US Department of Energy\u2019s responsibilities run the gamut from managing the nuclear stockpile and the strategic petroleum reserve to running the power grid in 36 states to performing basic and applied research to protect national security, ensure stable power sector operations and accelerate the clean energy transition.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELeveraging the power of DOE\u2019s computing infrastructure, including the world\u2019s fastest supercomputer, simulation models are used to accelerate advancements in nearly every field of research across DOE. Through a series of examples highlighting grid management, cybersecurity, cavern modeling and fundamental physical phenomena, this keynote will illuminate how DOE applies modeling and simulation to both research and operations.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBIO:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnn Dunkin currently serves as Chief Information Officer at the U.S. Department of Energy, where she manages the Department\u2019s information technology (IT) portfolio and modernization; oversees the Department\u2019s cybersecurity efforts; leads technology innovation and digital transformation; and enables collaboration across the Department.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EShe served in the Obama Administration as CIO of the U.S. Environmental Protection Agency. Prior roles include Chief Strategy and Innovation Officer, Dell Technologies; CIO, County of Santa Clara, CA; CTO, Palo Alto Unified School District, California; and various leadership roles at Hewlett Packard focused on engineering, research and development, IT, manufacturing engineering, software quality, and operations.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnn is a published author, most recently of the book Industrial Digital Transformation, and a frequent speaker on topics such as government technology modernization, digital transformation, and organizational development.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnn received the 2022 Capital CIO Large Enterprise ORBIE Award, and she has been given a range of previous awards, including DC\u2019s Top 50 Women in Technology for 2015 and 2016, ComputerWorld\u2019s Premier 100 Technology Leaders for 2016, StateScoop\u2019s Top 50 Women in Technology list for 2017, FedScoop\u2019s Golden Gov Executive of the Year in 2016 and 2021, and FedScoop\u2019s Best Bosses in Federal IT 2022.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMs. Dunkin holds a Master of Science degree and a Bachelor of Industrial Engineering degree, both from the Georgia Institute of Technology. She is a licensed professional engineer in the states of California and Washington. In 2018, she was inducted into Georgia Tech\u2019s Academy of Distinguished Engineering Alumni.\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe ISyE Distinguished Lecture Series was established in 2008 to promote discussion on critical issues in the fields of industrial and systems engineering by bringing in prominent scholars and business leaders who engage and share their expertise with students, faculty, and alumni.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Ann Dunkin will be delivering the LeeAnn and Walter Muller Distinguished Lecture Series."}],"uid":"36284","created_gmt":"2023-08-24 02:12:22","changed_gmt":"2023-09-28 22:32:06","author":"chenriquez8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-28T15:00:00-04:00","event_time_end":"2023-09-28T17:00:00-04:00","event_time_end_last":"2023-09-28T17:00:00-04:00","gmt_time_start":"2023-09-28 19:00:00","gmt_time_end":"2023-09-28 21:00:00","gmt_time_end_last":"2023-09-28 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Student Success Center, 219 Uncle Heinie Way NW, Atlanta, GA, 30313","extras":["free_food","freebies"],"hg_media":{"671468":{"id":"671468","type":"image","title":"Ann Dunkin","body":null,"created":"1692842658","gmt_created":"2023-08-24 02:04:18","changed":"1692842792","gmt_changed":"2023-08-24 02:06:32","alt":"Ann Dunkin","file":{"fid":"254536","name":"Ann%20Dunkin%20Formal%20%281%29 Large.jpeg","image_path":"\/sites\/default\/files\/2023\/08\/23\/Ann%2520Dunkin%2520Formal%2520%25281%2529%20Large.jpeg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/08\/23\/Ann%2520Dunkin%2520Formal%2520%25281%2529%20Large.jpeg","mime":"image\/jpeg","size":189168,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/08\/23\/Ann%2520Dunkin%2520Formal%2520%25281%2529%20Large.jpeg?itok=q0DSzP0v"}}},"media_ids":["671468"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"180995","name":"LeeAnn and Walter Muller Distinguished Lecture Series"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669699":{"#nid":"669699","#data":{"type":"event","title":"Georgia Statistics Day 2023","body":[{"value":"\u003Ch2\u003EGathering Minds Across Georgia: Promoting Interdisciplinary Statistics Research\u003C\/h2\u003E\r\n\r\n\u003Cp\u003EYou are cordially invited to the 2023 Georgia Statistics Day, a one-day workshop that brings together top researchers across the state to foster collaboration and innovation in statistics, data science, and related disciplines.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur workshop provides a unique opportunity for faculty and graduate students from Georgia\u2019s leading institutions to present their latest work, connect with peers, and gain exposure to cutting-edge developments shaping their fields.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWith a focus on mentorship and networking, Georgia Statistics Day facilitates idea exchange and partnership building among statisticians, data scientists, and interconnected domain experts in Georgia and the Southeast. Attendees will experience invited talks, panel discussions, and poster sessions that spark new interdisciplinary perspectives and opportunities for growth.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDon\u2019t miss this chance to contribute to and be inspired by the thriving statistics and data science community thriving in the Peach State! We look forward to welcoming you at the 2023 Georgia Statistics Day on Oct.9 in the Exhibition Center of Georgia Tech.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ERegistration Ends: \u003C\/strong\u003EThursday October 5th\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2023 Georgia Statistics Day is a \u003Cstrong\u003Efully reimbursed event \u003C\/strong\u003Efor students and postdocs with confirmed attendance.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Statistics Day 2023\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Statistics Day 2023"}],"uid":"27764","created_gmt":"2023-09-15 20:00:03","changed_gmt":"2023-09-25 19:07:08","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-09T08:45:00-04:00","event_time_end":"2023-10-09T17:00:00-04:00","event_time_end_last":"2023-10-09T17:00:00-04:00","gmt_time_start":"2023-10-09 12:45:00","gmt_time_end":"2023-10-09 21:00:00","gmt_time_end_last":"2023-10-09 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"GT Exhibition Hall","extras":[],"related_links":[{"url":"https:\/\/sites.gatech.edu\/gsd2023\/","title":"Event Website"},{"url":"https:\/\/www.isye.gatech.edu\/sites\/default\/files\/gsd-2023.pdf","title":"Event Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/user\/908\/contact\u0022\u003EMonike Welch\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669548":{"#nid":"669548","#data":{"type":"event","title":"Day In the Atrium - Walmart","body":[{"value":"\u003Cp\u003EWe can\u0027t wait to welcome Walmart on campus next week! Be sure to stop by for Day In The Atrium with Walmart, on September 14 at 11AM. \ud83d\uded2 \ud83e\udd1d \ud83d\udc1d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is a great time to network and connect with industry partners in the field to learn about upcoming opportunities and resources.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERefreshments will be served.\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBe sure to stop by for Day In The Atrium with Walmart, on September 14 at 11AM.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Be sure to stop by for Day In The Atrium with Walmart, on September 14 at 11AM"}],"uid":"36284","created_gmt":"2023-09-08 17:43:23","changed_gmt":"2023-09-08 17:51:10","author":"chenriquez8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-14T11:00:00-04:00","event_time_end":"2023-09-14T14:00:00-04:00","event_time_end_last":"2023-09-14T14:00:00-04:00","gmt_time_start":"2023-09-14 15:00:00","gmt_time_end":"2023-09-14 18:00:00","gmt_time_end_last":"2023-09-14 18:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Main, Atrium - 2nd Floor ","extras":[],"hg_media":{"671658":{"id":"671658","type":"image","title":"Day In the Atrium, Walmart","body":null,"created":"1694195011","gmt_created":"2023-09-08 17:43:31","changed":"1694195011","gmt_changed":"2023-09-08 17:43:31","alt":"Flyer for Day In the Atrium with Walmart","file":{"fid":"254759","name":"1.png","image_path":"\/sites\/default\/files\/2023\/09\/08\/1.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/09\/08\/1.png","mime":"image\/png","size":263110,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/09\/08\/1.png?itok=IM2WRBhN"}}},"media_ids":["671658"],"related_links":[{"url":"https:\/\/tech.walmart.com\/content\/walmart-global-tech\/en_us.html","title":"Walmart Global Tech"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDonald Phan,\u0026nbsp;Development Assc-Fundraising\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edonald.phan@isye.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669416":{"#nid":"669416","#data":{"type":"event","title":"ISyE Picture Day 2023","body":[{"value":"\u003Cp\u003EPhotos will be taking place over the course of 3 days in the Cecil G. Johnson ISyE Studio, located on the first floor in ISyE Main, Room 103. All faculty, and staff members are highly encouraged to take new headshots; all Ph.D. students are required.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you cannot make your assigned group day, please feel free to come by on any operating date below:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ETime: 10:00AM - 3:00PM\u003C\/li\u003E\r\n\t\u003Cli\u003ELocation:\u0026nbsp;Cecil G. Johnson ISyE Studio, 1st\u0026nbsp;Floor (ISyE Main)\u003C\/li\u003E\r\n\t\u003Cli\u003EDates:\u0026nbsp;\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003E9\/6: Staff\u003C\/li\u003E\r\n\t\t\u003Cli\u003E9\/7: Faculty\u003C\/li\u003E\r\n\t\t\u003Cli\u003E9\/8: Ph.D. Students\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ERecommendations for attire:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EWear blue, or dark-colored clothing (will be on a white backdrop)\u003C\/li\u003E\r\n\t\u003Cli\u003EDo NOT wear red\u003C\/li\u003E\r\n\t\u003Cli\u003EAvoid wearing large jewelry and patterns\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIf you took new headshots last year, it is highly encouraged to retake them.\u0026nbsp;Please attend the day that corresponds to your profile type.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Don\u0027t miss getting your headshot updated for the 2023-2024 academic school year!"}],"uid":"36284","created_gmt":"2023-09-05 12:39:25","changed_gmt":"2023-09-05 12:44:05","author":"chenriquez8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-06T10:00:00-04:00","event_time_end":"2023-09-08T15:00:00-04:00","event_time_end_last":"2023-09-08T15:00:00-04:00","gmt_time_start":"2023-09-06 14:00:00","gmt_time_end":"2023-09-08 19:00:00","gmt_time_end_last":"2023-09-08 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Main 1st Floor, Cecil G. Johnson Studio","extras":[],"hg_media":{"671582":{"id":"671582","type":"image","title":"ISyE Picture Day","body":null,"created":"1693914370","gmt_created":"2023-09-05 11:46:10","changed":"1693914370","gmt_changed":"2023-09-05 11:46:10","alt":"ISyE Picture Day 2023","file":{"fid":"254669","name":"Picture Day Banner copy Large.jpeg","image_path":"\/sites\/default\/files\/2023\/09\/05\/Picture%20Day%20Banner%20copy%20Large.jpeg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/09\/05\/Picture%20Day%20Banner%20copy%20Large.jpeg","mime":"image\/jpeg","size":142499,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/09\/05\/Picture%20Day%20Banner%20copy%20Large.jpeg?itok=v7OxqTTB"}}},"media_ids":["671582"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003ECamille C. Henriquez\u003C\/p\u003E\r\n\r\n\u003Cp\u003Echenriquez8@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669336":{"#nid":"669336","#data":{"type":"event","title":"ISyE Seminar Speaker - Nikita Zhivotovskiy","body":[{"value":"\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EOptimal PAC Bounds without Uniform Convergence\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cem\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/em\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn statistical learning theory, the problem of determining sample complexity of realizable binary classification for VC classes was a longstanding challenge. Notable advancements by Simon and Hanneke established sharp upper bounds, but their argument\u2019s reliance on the uniform convergence principle curtailed its broader applicability to learning settings like multiclass classification. In this presentation, we will discuss a new technique to resolve this limitation and introduce optimal high probability risk bounds within a framework that surpasses uniform convergence constraints. Beyond binary classification, we will also delve into applications in scenarios where uniform convergence is notably sub-optimal. For multiclass classification, we will prove an optimal risk bound that scales with the one-inclusion hypergraph density of the class, effectively addressing the sub-optimality in the analysis by Daniely and Shalev-Shwartz. Additionally, for realizable bounded regression with absolute loss, we will derive an optimal risk bound based on a revised version of the scale-sensitive dimension, thus refining the results of Bartlett and Long. This talk is based on the joint work with Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, and Abhishek Shetty.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ENikita Zhivotovskiy is a tenure-track Assistant Professor at the Unive\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003Ersity of\u0026nbsp;California Berkeley, Department of Statistics.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EFrom January 2021 to October 2022 he was a postdoctoral researcher at the department of mathematics ETH, Z\u00fcrich hosted by\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/people.math.ethz.ch\/~abandeira\/\u0022 target=\u0022_blank\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAfonso Bandeira\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBetween January 2019 and December 2020 he was a postdoctoral researcher at\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003EGoogle Research,\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003EZ\u00fcrich hosted by\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/research.google\/people\/OlivierBousquet\/\u0022 target=\u0022_blank\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EOlivier Bousquet\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBefore that he spent half a year at the department of mathematics,\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003ETechnion I.I.T.\u003C\/span\u003E\u003Cspan\u003E\u0026nbsp;hosted by\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/maths-people.anu.edu.au\/~mendelso\/\u0022 target=\u0022_blank\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EShahar Mendelson\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ENikita defended my thesis at Moscow Institute of Physics and Technology Moscow in 2018 under the supervision of\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Ca href=\u0022https:\/\/www.wias-berlin.de\/~spokoiny\/\u0022 target=\u0022_blank\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EVladimir Spokoiny\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u0026nbsp;and\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003EKonstantin Vorontsov. During my time in Moscow, he was affiliated (part-time) with the Institute for Information Transmission Problems, Higher School of Economics, and Skoltech.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EHis main interests are in the intersection of mathematical statistics, probability and learning theory.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cem\u003EIn statistical learning theory, the problem of determining sample complexity of realizable binary classification for VC classes was a longstanding challenge. Notable advancements by Simon and Hanneke established sharp upper bounds, but their argument\u2019s reliance on the uniform convergence principle curtailed its broader applicability to learning settings like multiclass classification. In this presentation, we will discuss a new technique to resolve this limitation and introduce optimal high probability risk bounds within a framework that surpasses uniform convergence constraints. Beyond binary classification, we will also delve into applications in scenarios where uniform convergence is notably sub-optimal. For multiclass classification, we will prove an optimal risk bound that scales with the one-inclusion hypergraph density of the class, effectively addressing the sub-optimality in the analysis by Daniely and Shalev-Shwartz. Additionally, for realizable bounded regression with absolute loss, we will derive an optimal risk bound based on a revised version of the scale-sensitive dimension, thus refining the results of Bartlett and Long. This talk is based on the joint work with Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, and Abhishek Shetty.\u003C\/em\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Optimal PAC Bounds without Uniform Convergence"}],"uid":"36374","created_gmt":"2023-09-01 12:26:03","changed_gmt":"2023-09-01 12:26:03","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-15T11:30:00-04:00","event_time_end":"2023-09-15T12:30:00-04:00","event_time_end_last":"2023-09-15T12:30:00-04:00","gmt_time_start":"2023-09-15 15:30:00","gmt_time_end":"2023-09-15 16:30:00","gmt_time_end_last":"2023-09-15 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669234":{"#nid":"669234","#data":{"type":"event","title":" Undergraduate \/ Graduate First-Time TA orientation","body":[{"value":"\u003Cp\u003EAll first-time Teaching Assistants (TAs) are required to participate in an orientation program.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation\u0022\u003ERegister On-Campus Link\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/vpn.gatech.edu\/https\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation\u0022\u003ERegister Off-Campus Link\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;Undergraduate \/ Graduate First-Time TA orientation\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" Undergraduate \/ Graduate First-Time TA orientation"}],"uid":"27764","created_gmt":"2023-08-29 17:59:43","changed_gmt":"2023-08-29 19:14:26","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-05T11:00:00-04:00","event_time_end":"2023-09-05T12:00:00-04:00","event_time_end_last":"2023-09-05T12:00:00-04:00","gmt_time_start":"2023-09-05 15:00:00","gmt_time_end":"2023-09-05 16:00:00","gmt_time_end_last":"2023-09-05 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Main 126","extras":[],"related_links":[{"url":"https:\/\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation","title":"Register On-Campus Link"},{"url":"https:\/\/vpn.gatech.edu\/https\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation","title":"Register Off-Campus Link"}],"groups":[{"id":"660354","name":"Center for Academics, Success, and Equity"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"172446","name":"TA orientation"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:case@isye.gatech.edu\u0022\u003Ecase@isye.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669238":{"#nid":"669238","#data":{"type":"event","title":"Undergraduate \/ Graduate First-Time TA orientation","body":[{"value":"\u003Cp\u003EAll first-time Teaching Assistants (TAs) are required to participate in an orientation program.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation\u0022\u003ERegister On-Campus Link\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/vpn.gatech.edu\/https\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation\u0022\u003ERegister Off-Campus Link\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EUndergraduate \/ Graduate First-Time TA orientation\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Undergraduate \/ Graduate First-Time TA orientation"}],"uid":"27764","created_gmt":"2023-08-29 19:10:54","changed_gmt":"2023-08-29 19:12:55","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-07T11:00:00-04:00","event_time_end":"2023-09-07T12:00:00-04:00","event_time_end_last":"2023-09-07T12:00:00-04:00","gmt_time_start":"2023-09-07 15:00:00","gmt_time_end":"2023-09-07 16:00:00","gmt_time_end_last":"2023-09-07 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Main 126","extras":[],"related_links":[{"url":"https:\/\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation","title":"Register On-Campus Link"},{"url":"https:\/\/vpn.gatech.edu\/https\/webforms.isye.gatech.edu\/graduate-forms\/teaching-assistant-orientation","title":"Register Off-Campus Link"}],"groups":[{"id":"660354","name":"Center for Academics, Success, and Equity"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"172446","name":"TA orientation"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:case@isye.gatech.edu\u0022\u003Ecase@isye.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669019":{"#nid":"669019","#data":{"type":"event","title":"SCL Course: Essentials of Negotiations and Stakeholder Influence (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEssentials of Negotiations and Stakeholder Influence level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u201cDNA\u201d to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u201cno judgement zone\u201d environment.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, project leaders, business unit leaders, operations managers, sales leaders and procurement \u0026amp; supply management-related professionals who are involved with supplier selection, contract development and supplier performance management.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease emphasis negotiation conditioning and philosophy setting before and throughout the entire sourcing engagement process\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance your toolbox of industry standard negotiation prep tools like the SWOT and BATNA\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter prepare for negotiations by leveraging knowledge of key negotiation terms and counter-offer tactics\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove negotiation table techniques and soft skills to direct and redirect negotiation momentum\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten ability to successfully utilize your traditional \u0022comfort zone\u0022 approach in combination with your negotiation team\u2019s strengths by leveraging Personal Negotiation Styles\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENegotiation Conditioning Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Preparation Tools\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Execution Techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStakeholder Engagement \u0026amp; Team Leadership\u003C\/li\u003E\r\n\t\u003Cli\u003ELive Negotiations Simulation \u0026amp; Feedback\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u201cDNA\u201d to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u201cno judgement zone\u201d environment.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations."}],"uid":"27233","created_gmt":"2023-08-17 14:10:05","changed_gmt":"2023-08-29 16:32:32","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-03-07T13:00:00-05:00","event_time_end":"2024-03-14T16:00:00-04:00","event_time_end_last":"2024-03-14T16:00:00-04:00","gmt_time_start":"2024-03-07 18:00:00","gmt_time_end":"2024-03-14 20:00:00","gmt_time_end_last":"2024-03-14 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/epn","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"668835":{"#nid":"668835","#data":{"type":"event","title":"SCL Course: Category Management and Sourcing Leadership (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECategory Management and Sourcing Leadership is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0022hands on\u0022 delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, procurement professionals, project managers, finance analyst, contract managers and all procurement \u0026amp; supply management-related professionals involved with bid package development, bid package analysis, negotiations preparation, contracting and supplier selection activity.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base of solicitation options (i.e. RFI, RFP, RFQ) and which solicitation approach to apply based on your organization\u0027s needs\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of sourcing process and critical steps in the Bid Package development and delivery activities\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage and utilization of solicitation tools to drive successful development of bid packages\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove set up and execution of supplier selection scorecards to aid in identifying best Total Cost of Ownership alternatives\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten understanding of executive communication to leverage leadership support throughout the organization\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBid Package Development Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ESourcing Initiative Process Roadmap\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EMarketplace Analysis Tools\u003C\/li\u003E\r\n\t\u003Cli\u003EBid Package Alternatives \u0026amp; Design\u003C\/li\u003E\r\n\t\u003Cli\u003ESupplier Selection \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026amp; supply management function. 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This \u0022hands on\u0022 delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026 supply management function."}],"uid":"27233","created_gmt":"2023-08-08 20:03:04","changed_gmt":"2023-08-29 16:32:25","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-02-26T13:00:00-05:00","event_time_end":"2024-02-29T14:30:00-05:00","event_time_end_last":"2024-02-29T14:30:00-05:00","gmt_time_start":"2024-02-26 18:00:00","gmt_time_end":"2024-02-29 19:30:00","gmt_time_end_last":"2024-02-29 19:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/cmsl","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EEMAIL: \u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E or CALL: (404) 385-3501 between 9:00a.m. and 4:00p.m., Eastern time.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661204":{"#nid":"661204","#data":{"type":"event","title":"SCL Course: Supply Chain Optimization and Prescriptive Analytics (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u2019ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. 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The course includes review of the key elements of transportation such as: modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms. \u0026nbsp;The course also will discuss emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course is designed for Supply Chain Managers, Distribution Managers, Transportation Planners, Transportation Clerks, Transportation Analysts, and Transportation Managers and learners seeking to enter these roles. \u0026nbsp;Supply chain professionals from other domains will also benefit through gaining insights into transportation operations.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the characteristics and best use of specific transportation modes\u003C\/li\u003E\r\n\t\u003Cli\u003EApply transportation cost analysis techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the multimodal role of ports in global trade\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify and apply best practices in transportation procurement\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how to minimize transportation costs through consolidation techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the role of Incoterms in global trade\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand emerging techniques in logistics including techniques to reduce greenhouse gas emissions in logistics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWhat is Covered\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EComparison of characteristics of alternative transportation modes\u003C\/li\u003E\r\n\t\u003Cli\u003EComponents of Port Logistics systems\u003C\/li\u003E\r\n\t\u003Cli\u003EBest practices in transportation procurement\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of practical transportation cost analysis techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EINCOTERMS purpose, types, and use\u003C\/li\u003E\r\n\t\u003Cli\u003EGreenhouse gas emission generation in logistics and mitigation strategies\u003C\/li\u003E\r\n\t\u003Cli\u003ENew business models in logistics enabled by emerging technologies\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course prepares students in the basics of transportation operations and analysis. \u0026nbsp;The course includes review of the key elements of transportation such as: modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms. \u0026nbsp;The course also will discuss emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course prepares students in the basics of transportation operations and analysis."}],"uid":"27233","created_gmt":"2022-10-18 21:51:55","changed_gmt":"2023-08-29 16:31:14","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-10-24T08:00:00-04:00","event_time_end":"2023-10-26T17:00:00-04:00","event_time_end_last":"2023-10-26T17:00:00-04:00","gmt_time_start":"2023-10-24 12:00:00","gmt_time_end":"2023-10-26 21:00:00","gmt_time_end_last":"2023-10-26 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/ptm","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"3843","name":"distribution"},{"id":"168044","name":"sourcing"},{"id":"168","name":"Transportation"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669227":{"#nid":"669227","#data":{"type":"event","title":"Professional Education Course: Systems Operations and Strategic Interactions in Supply Chains","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EOften the lack of cooperation and coordination between organizations or stakeholders lead to inefficiencies, despite having common goals. A systems view is needed to ensure appropriate use of scarce resources to meet the multiple, and often conflicting, short- and long-term goals from multiple constituents. This course will focus on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIdentify opportunities for coordination within organizations and collaboration across organizations for increased efficiency and improved outcomes.\u003C\/li\u003E\r\n\t\u003Cli\u003EDescribe the strategic behavior of decision-makers and the impact of the market (or contract) structure on the participant\u0027s actions and the overall system dynamics.\u003C\/li\u003E\r\n\t\u003Cli\u003EDefine evaluation metrics in alignment with the system goals and structure system operations and incentives that address and evaluate these metrics.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow coordination and collaboration can improve supply chain efficiency and effectiveness\u003C\/li\u003E\r\n\t\u003Cli\u003EHow events, decisions and actions in one part of a system, such as a supply chain, impact other parts of the system\u003C\/li\u003E\r\n\t\u003Cli\u003ESystem-wide inventory variability and costs mitigation and reduction\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation metrics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by December 31, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course focuses on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore conceptual and modeling skills to understand and effectively manage humanitarian response from a systems perspective."}],"uid":"27233","created_gmt":"2023-08-29 11:54:16","changed_gmt":"2023-08-29 11:55:37","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-04-22T09:30:00-04:00","event_time_end":"2024-04-25T13:00:00-04:00","event_time_end_last":"2024-04-25T13:00:00-04:00","gmt_time_start":"2024-04-22 13:30:00","gmt_time_end":"2024-04-25 17:00:00","gmt_time_end_last":"2024-04-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/courses\/systems-operations-and-strategic-interactions-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"192986","name":"supply chain, logistics, humanitarian"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669226":{"#nid":"669226","#data":{"type":"event","title":"Professional Education Course: Inventory Management and Resource Allocation in Supply Chains","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMany Supply Chain decisions are concerned with the timely and efficient procurement, allocation, and distribution of resources (e.g. funds, supplies, volunteers, money, employees) through a supply chain network. This course will explore methodologies for \u201cmedium term\u201d decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and supply chain design.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help your organization and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProcurement decisions\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management techniques for a single event versus ongoing operations under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for resource allocation geographically and over time\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the second in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by December 31, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course explores methodologies for tactical decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and transportation decisions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Inventory availability is the most important aspect of customer service, and the cost of inventory is one of the most important entries on a company\u0027s balance sheet."}],"uid":"27233","created_gmt":"2023-08-29 11:52:15","changed_gmt":"2023-08-29 11:53:36","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-04-15T09:30:00-04:00","event_time_end":"2024-04-18T13:00:00-04:00","event_time_end_last":"2024-04-18T13:00:00-04:00","gmt_time_start":"2024-04-15 13:30:00","gmt_time_end":"2024-04-18 17:00:00","gmt_time_end_last":"2024-04-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/courses\/inventory-management-and-resource-allocation-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"192986","name":"supply chain, logistics, humanitarian"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669225":{"#nid":"669225","#data":{"type":"event","title":"Professional Education Course: Responsive Supply Chain Design and Operations","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm ET each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMeeting demand in a timely and cost-effective manner is important both in public and private supply chains, and heavily depend on the design and operation of these supply chains. Demand is affected by ongoing factors such as local economy, infrastructure, and geographic location, as well as unexpected events such as natural or manmade disasters or other large-scale disruptions. Designing and operating responsive supply chains requires the consideration of uncertainty in timing, scope, scale, and understanding of various topics such as forecasting, distribution network design, and inventory management. This course will examine methods and models for making supply chain design and operational decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for meeting the need of customers and beneficiaries.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through learnings gained from applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help organizations and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a critical knowledge base to make tactical decisions around inventory, routing, and distribution.\u003C\/li\u003E\r\n\t\u003Cli\u003EDeliver best practices to measure and evaluate the efficiency, impact, and outcomes of focused initiatives or ongoing logistics and supply chain operations.\u003C\/li\u003E\r\n\t\u003Cli\u003ETransform the health and humanitarian sectors with increased capacity to participate in planning and strategic decision-making for effective supply-chain management.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENetwork modeling approaches\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for making decisions under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EOther data-driven analytical approaches\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by December 31, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course examines methods and models for making pre-planning decisions and explores the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for sustaining wellness.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term development"}],"uid":"27233","created_gmt":"2023-08-29 11:48:36","changed_gmt":"2023-08-29 11:52:10","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-04-01T09:30:00-04:00","event_time_end":"2024-04-04T13:00:00-04:00","event_time_end_last":"2024-04-04T13:00:00-04:00","gmt_time_start":"2024-04-01 13:30:00","gmt_time_end":"2024-04-04 17:00:00","gmt_time_end_last":"2024-04-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/courses\/responsive-supply-chain-design-and-operations","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"8039","name":"Humanitarian"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669224":{"#nid":"669224","#data":{"type":"event","title":"2023 Health \u0026 Humanitarian Logistics Conference (Kenya)","body":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u003Cstrong\u003E15th annual Health \u0026amp; Humanitarian Logistics (HHL) Conference\u0026nbsp;\u003C\/strong\u003Ewill take place \u003Cem\u003E\u003Cstrong\u003ENovember 21-22 | Nairobi, Kenya\u0026nbsp;\u003C\/strong\u003E\u003C\/em\u003Eto provide an open forum to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery. The event serves as an opportunity for practitioners, aid organizations, government representatives, innovators, academics, and others to learn and engage on challenges and opportunities relevant to today\u2019s health and humanitarian supply chains. It is an ideal platform for sponsors and innovators to show-case their brand to a wide audience and link to a valuable annual cycle of follow-on activities. The event will be driven by case studies and discussions with a mix of high level and practical engagement.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERepresentatives from the humanitarian sector, government, NGOs, foundations and private industry, and academia present diverse perspectives in health and humanitarian challenges through keynote addresses, panel discussions, focused workshops, lunchtime group discussions, and interactive poster sessions covering a broad set of research topics and applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe invite you to attend and participate as a presenter in the following areas:\u0026nbsp;\u003Cstrong\u003Ecollaborative workshops\u003C\/strong\u003E,\u0026nbsp;\u003Cstrong\u003Eoral presentations\u003C\/strong\u003E\u0026nbsp;and\u0026nbsp;\u003Cstrong\u003Eposter sessions\u003C\/strong\u003E. To see our requirements and\u0026nbsp;submit a proposal visit our\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2023\/program\/presentations\/overview\u0022\u003ECall For Presentations Page\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u0026nbsp;\u003Cstrong\u003E15th annual Health \u0026amp; Humanitarian Logistics (HHL) Conference\u0026nbsp;\u003C\/strong\u003Ewill take place \u003Cem\u003E\u003Cstrong\u003ENovember 21-22 | Nairobi, Kenya\u0026nbsp;\u003C\/strong\u003E\u003C\/em\u003Eto provide an open forum to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery.\u0026nbsp;We invite you to attend and participate as a presenter in the following areas:\u0026nbsp;\u003Cstrong\u003Ecollaborative workshops\u003C\/strong\u003E,\u0026nbsp;\u003Cstrong\u003Eoral presentations\u003C\/strong\u003E\u0026nbsp;and\u0026nbsp;\u003Cstrong\u003Eposter sessions\u003C\/strong\u003E.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"November 21-22 | Nairobi, Kenya"}],"uid":"27233","created_gmt":"2023-08-28 23:26:13","changed_gmt":"2023-08-29 11:42:05","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-11-21T13:00:00-05:00","event_time_end":"2023-11-22T17:15:00-05:00","event_time_end_last":"2023-11-22T17:15:00-05:00","gmt_time_start":"2023-11-21 18:00:00","gmt_time_end":"2023-11-22 22:15:00","gmt_time_end_last":"2023-11-22 22:15:00","rrule":null,"timezone":"America\/New_York"},"location":"The Boma Hotel","extras":[],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/conference\/2023","title":"Register Now for Early Bird Rates!"},{"url":"https:\/\/chhs.gatech.edu\/conference\/2023\/program\/presentations\/overview","title":"Call for Presentations"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"134861","name":"Institute and Campus"},{"id":"506","name":"alumni"},{"id":"1564","name":"community"},{"id":"1432","name":"education"},{"id":"63381","name":"exhibitions"},{"id":"180621","name":"Economic Development and Policy"},{"id":"2510","name":"Institute leadership"},{"id":"180622","name":"Special Events and Guest Speakers"},{"id":"167441","name":"student research"},{"id":"365","name":"Research"},{"id":"807","name":"environment"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EIf you have a question or comments for the organizers, please submit them using our\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/contact\u0022\u003Econtact form\u003C\/a\u003E.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669139":{"#nid":"669139","#data":{"type":"event","title":"Climate Sustainability Challenges and Opportunities Workshop","body":[{"value":"\u003Cp\u003EThe workshop is focused on advancing the frontiers of climate sustainability through the presentation of cutting-edge research, prioritizing time for discussion and fostering informal interactions among students and scientists of all career stages. This workshop includes four themes: Climate Justice, Climate Science, Climate Modeling, Climate Tech and Solutions. A daily schedule can be found\u0026nbsp;\u003Ca href=\u0022https:\/\/docs.google.com\/spreadsheets\/d\/1I4KWXYDXzYeFRIdkXvYv0IysoAWhlm2GWZ8beHaEkxY\/edit#gid=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022https:\/\/docs.google.com\/spreadsheets\/d\/1I4KWXYDXzYeFRIdkXvYv0IysoAWhlm2GWZ8beHaEkxY\/edit#gid=0\u0022\u003Ehere\u003C\/a\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECo-organized by Georgia Tech and Spelman College, it will be held in the Manley Atrium at Spelman College in the heart of the Atlanta University Center, near the historic community of West End, from\u0026nbsp;\u003Cstrong\u003ESeptember 10 to September 14, 2023\u003C\/strong\u003E, and is open to Georgia Tech graduate students and to undergraduates from all Colleges and Universities in the Atlanta area. In addition to premier talks, the workshop has designated time for poster sessions from individuals of all career stages, and communal meals for creating lasting collaborations and friendships and for informal networking opportunities with leaders in the climate sustainability challenge.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EParticipation at the event is free of charge, but registration is required, because space is limited. The registration deadline has been updated to September 3rd (Sunday). For registration, please complete the form at\u0026nbsp;\u003Ca href=\u0022https:\/\/forms.gle\/7CjuApx4V5cLFTUX7\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022https:\/\/forms.gle\/7CjuApx4V5cLFTUX7\u0022\u003Ehttps:\/\/forms.gle\/7CjuApx4V5cLFTUX7\u003C\/a\u003E\u0026nbsp;or follow the QR code on the enclosed poster. \u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinancial support for the workshop has been generously provided by UCAR\/NCAR, ORAU, and the Strategic Energy Institute, the Direct Air Capture Center (DirACC), the Brook Byers Institute for Sustainable Systems and the Ocean Science and Engineering Program at Georgia Tech.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Georgia Institute of Technology and Spelman College are pleased to present Climate Sustainability: Challenges \u0026amp; Opportunities. A workshop on climate science, climate solutions, and climate justice organized by graduate students for graduate and undergraduate students.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Climate Sustainability Challenges and Opportunities Workshop"}],"uid":"36284","created_gmt":"2023-08-24 02:58:21","changed_gmt":"2023-08-24 03:00:18","author":"chenriquez8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-10T09:00:00-04:00","event_time_end":"2023-09-14T09:00:00-04:00","event_time_end_last":"2023-09-14T09:00:00-04:00","gmt_time_start":"2023-09-10 13:00:00","gmt_time_end":"2023-09-14 13:00:00","gmt_time_end_last":"2023-09-14 13:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Spelman","extras":[],"hg_media":{"671470":{"id":"671470","type":"image","title":"Climate Sustainability Challenges and Opportunities Workshop","body":null,"created":"1692845651","gmt_created":"2023-08-24 02:54:11","changed":"1692845669","gmt_changed":"2023-08-24 02:54:29","alt":"Climate Sustainability Challenges and Opportunities Workshop","file":{"fid":"254538","name":"POSTER_SUSTAINABILITY.png","image_path":"\/sites\/default\/files\/2023\/08\/23\/POSTER_SUSTAINABILITY.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/08\/23\/POSTER_SUSTAINABILITY.png","mime":"image\/png","size":635632,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/08\/23\/POSTER_SUSTAINABILITY.png?itok=0BGVegto"}}},"media_ids":["671470"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"26411","name":"Training\/Workshop"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669138":{"#nid":"669138","#data":{"type":"event","title":"ISyE Thesis Defense Announcement \u2013 Sara Kaboudvand","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EThesis\u0026nbsp;Title:\u003C\/strong\u003E\u0026nbsp;Hyperconnected Parcel Logistics: Planning and Assessment\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThesis\u0026nbsp;Committee:\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Benoit Montreuil (advisor), School of Industrial and Systems Engineering, Georgia Institute of Technology\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Martin Savelsbergh (co-advisor), School of Industrial and Systems Engineering, Georgia Institute of Technology\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Leon McGinnis, School of Industrial and Systems Engineering, Georgia Institute of Technology\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Uday Venkatadri, School of Industrial Engineering, Dalhousie University\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Walid Klibi, Supply Chain Center of Excellence, Kedge Business School\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;Friday, August 25, 2023, 10 am - 12 pm EST\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EOnline Meeting Link:\u003C\/strong\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_ZDJlNzMxNTAtZTYyMi00ZjVkLThiYmQtOTcyZTIyMWRjODE4%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%229962fa72-ad37-42c1-b47c-14e8a0112a90%22%7d\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022\u003EClick Here to Join the Meeting\u003C\/a\u003E\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EToday\u0027s last-mile logistics faces numerous challenges, particularly concerning cost management and meeting customers\u0027 escalating expectations. With the steady expansion of e-commerce, the volume of last-mile deliveries has surged, consequently driving up costs for logistics providers. Additionally, the competitive landscape has intensified, with businesses striving to offer same-day or even on-demand deliveries to cater to customers\u0027 demands for convenience and satisfaction. This\u0026nbsp;thesis\u0026nbsp;investigates pivotal facets of megacity parcel logistics, with a specific emphasis on two main objectives: (1) realizing the cost-saving potential of package consolidation and containerization, and (2) analytically assessing novel logistical network configurations that revolutionize the handling of packages within the logistics network.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn Chapter 2, we present a formal definition of containerized consolidation in megacity parcel logistics and explore its potential benefits, including reductions in total handling and transit costs. We propose an Integer Programming (IP) formulation and conduct an extensive sensitivity analysis across diverse network configurations and demand patterns. The findings showcase the potential for remarkable savings, with up to 80% reduction in handling costs and over 20% reduction in total in-transit costs through the implementation of containerized consolidation.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn Chapter 3, we shift our focus from tactical containerized consolidation planning to a dynamic and data-driven approach tailored to the fast-paced last-mile delivery environment. We present a Mixed Integer Programming (MIP) formulation for decentralized and dynamic consolidation and containerization of packages at distribution hubs. Given the complexity of this model, solving it in real-time dynamic scenarios is impractical. To tackle this challenge, we introduce two heuristic approaches to handle dynamic decisions and assess their performance against the optimal solution. Our findings demonstrate that the proposed heuristics can achieve nearly optimal solutions while considerably reducing computational time.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinally, In Chapter 4, we adopt a more holistic perspective on megacity parcel logistics, evaluating the advantages of the recently introduced and innovative Hyperconnected Logistic Web concept for enhancing urban parcel logistics efficiency and responsiveness. We emphasize the significance of a holistic approach in validating such solutions and introduce an agent-based discrete-event simulator platform, capable of modeling urban delivery networks at the parcel granularity. This simulator adeptly handles a range of strategic, tactical, and operational decisions necessary for urban logistic operations. Utilizing the proposed model and\u0026nbsp;given real data from a high-profile package delivery company,\u0026nbsp;we execute two sets of experiments to evaluate the effect of different package routing and consolidation strategies on logistics network performance. Preliminary results illustrate that a higher level of interconnection among nodes in the lower network tiers leads to reduced in-transit costs, enabling the provision of tighter customer delivery services. Furthermore, the initial experiments with the consolidation heuristics introduced in Chapter 3, demonstrate that the proposed heuristic yields lower operational costs compared to other traditional consolidation approaches.\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EISyE Thesis Defense Announcement \u2013 Sara Kaboudvand, Industrial Engineering Ph.D. Candidate\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ISyE Thesis Defense Announcement \u2013 Sara Kaboudvand"}],"uid":"36284","created_gmt":"2023-08-24 02:25:10","changed_gmt":"2023-08-24 02:27:03","author":"chenriquez8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-08-25T10:00:00-04:00","event_time_end":"2023-08-30T12:00:00-04:00","event_time_end_last":"2023-08-30T12:00:00-04:00","gmt_time_start":"2023-08-25 14:00:00","gmt_time_end":"2023-08-30 16:00:00","gmt_time_end_last":"2023-08-30 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"671469":{"id":"671469","type":"image","title":"Sara Kaboudvand","body":null,"created":"1692843696","gmt_created":"2023-08-24 02:21:36","changed":"1692843721","gmt_changed":"2023-08-24 02:22:01","alt":"Sara Kaboudvand","file":{"fid":"254537","name":"b83a0886-sara-kaboudvandweb2-2432_13.jpg","image_path":"\/sites\/default\/files\/2023\/08\/23\/b83a0886-sara-kaboudvandweb2-2432_13.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/08\/23\/b83a0886-sara-kaboudvandweb2-2432_13.jpg","mime":"image\/jpeg","size":13753,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/08\/23\/b83a0886-sara-kaboudvandweb2-2432_13.jpg?itok=axhfomEW"}}},"media_ids":["671469"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669030":{"#nid":"669030","#data":{"type":"event","title":"ISyE Seminar Speaker - Jianfeng Lu","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EActor-critic method for solving high dimensional Hamilton-Jacobi-Bellman type PDEs\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, we will discuss numerical approach to solve high dimensional Hamilton-Jacobi-Bellman (HJB) type partial differential equations (PDEs).\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EThe HJB PDEs, reformulated as optimal control problems, are tackled by the actor-critic framework inspired by reinforcement learning, based on neural network parametrization of the value and control functions. Within the actor-critic framework, we employ a policy gradient approach to improve the control, while for the value function, we derive a variance reduced least-squares temporal difference method using stochastic calculus. We will also discuss convergence analysis for the actor-critic method, in particular the policy gradient method for solving stochastic optimal control. Joint work with Jiequn Han (Flatiron\u0026nbsp;Institute) and Mo Zhou (Duke University).\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EJianfeng Lu is a Professor of Mathematics, Physics, and Chemistry at Duke University. Before joining Duke University, he obtained his PhD in Applied Mathematics from Princeton University in 2009 and was a Courant Instructor at New York University from 2009 to 2012. He works on mathematical analysis and algorithm development for problems and challenges arising from computational physics, theoretical chemistry, materials science, high-dimensional PDEs, and machine learning. He is a fellow of AMS. His work has been recognized by a Sloan Fellowship, a NSF Career Award, the IMA Prize in Mathematics and its Applications, and the Feng Kang Prize.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, we will discuss numerical approach to solve high dimensional Hamilton-Jacobi-Bellman (HJB) type partial differential equations (PDEs).\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EThe HJB PDEs, reformulated as optimal control problems, are tackled by the actor-critic framework inspired by reinforcement learning, based on neural network parametrization of the value and control functions. Within the actor-critic framework, we employ a policy gradient approach to improve the control, while for the value function, we derive a variance reduced least-squares temporal difference method using stochastic calculus. We will also discuss convergence analysis for the actor-critic method, in particular the policy gradient method for solving stochastic optimal control. Joint work with Jiequn Han (Flatiron\u0026nbsp;Institute) and Mo Zhou (Duke University).\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Actor-critic method for solving high dimensional Hamilton-Jacobi-Bellman type PDEs "}],"uid":"36374","created_gmt":"2023-08-18 11:31:04","changed_gmt":"2023-08-18 11:31:04","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-01T11:30:00-04:00","event_time_end":"2023-09-01T12:30:00-04:00","event_time_end_last":"2023-09-01T12:30:00-04:00","gmt_time_start":"2023-09-01 15:30:00","gmt_time_end":"2023-09-01 16:30:00","gmt_time_end_last":"2023-09-01 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"669018":{"#nid":"669018","#data":{"type":"event","title":"SCL Course: Contracting and Legal Oversight (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EContracting and Legal Oversight provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents. The program is geared to reinforce standards of excellence for professionals who are responsible for delivering contractual agreements and mitigating financial risk for their organization.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (3) instructor-led LIVE group webinars, homework, and pre-work (e.g. installing and testing software on your computer, testing connectivity with Canvas LMS and BlueJeans meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for contract managers, procurement professionals, sourcing initiative leaders, project managers and all procurement \u0026amp; supply management-related professionals involved with bid contract development, contract execution or supplier performance management.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base in law of agency concepts to gain more confidence with contracting.\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of industry standard contract types and contract terms for more robust contract agreements.\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage sourcing category knowledge to modify existing contract elements for more holistic contract agreements.\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove internal contract execution communication for better results.\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten sense of executive financial impact and risk needs to gain leadership early support.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELaw of Agency Overview\u003C\/li\u003E\r\n\t\u003Cli\u003EContract Agreement Types\u003C\/li\u003E\r\n\t\u003Cli\u003EDefining Key Terms\u003C\/li\u003E\r\n\t\u003Cli\u003EContract Structure \u0026amp; Drafting\u003C\/li\u003E\r\n\t\u003Cli\u003ERisk Mitigation \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents. The program is geared to reinforce standards of excellence for professionals who are responsible for delivering contractual agreements and mitigating financial risk for their organization.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents."}],"uid":"27233","created_gmt":"2023-08-17 14:03:53","changed_gmt":"2023-08-17 14:05:16","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-02-29T15:00:00-05:00","event_time_end":"2024-03-06T17:00:00-05:00","event_time_end_last":"2024-03-06T17:00:00-05:00","gmt_time_start":"2024-02-29 20:00:00","gmt_time_end":"2024-03-06 22:00:00","gmt_time_end_last":"2024-03-06 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtual-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/clo","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"669016":{"#nid":"669016","#data":{"type":"event","title":"ISyE Seminar Speaker - Mor Harchol","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EScheduling Multiserver Compute Jobs\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAlmost all queueing models assume that a job runs on a single server. But this one-server-per-job model is not a good representation of today\u0027s compute jobs.\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003EA typical data center job today occupies multiple cores concurrently.\u0026nbsp; We refer to a job that requires a fixed number of cores for some duration as a multiserver job.\u0026nbsp; Unfortunately, very little is known about the performance of multiserver job queueing models.\u0026nbsp; We present the first results on response time for multiserver job models.\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003ETo do this, we introduce a new scheduling policy, called ServerFilling, which is both\u0026nbsp;throughput-optimal in many settings and also lends itself to response time analysis.\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003EJoint work with:\u003Cstrong\u003E \u003C\/strong\u003E\u0026nbsp;Isaac Grosof and Alan Scheller-Wolf\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EMor Harchol-Balter is the Bruce J. Nelson Professor of Computer Science at Carnegie Mellon University.\u0026nbsp; She is a Fellow of both ACM and IEEE.\u0026nbsp; She currently serves as SIG Chair for ACM SIGMETRICS, and has previously served as General Chair and TPC Chair for SIGMETRICS. She is the recipient of the NSF CAREER award, dozens of Industrial Faculty Awards, and several teaching awards, including the Herbert A. Simon Teaching Award and the Spira Teaching Award. Mor is the author of a popular queueing theory textbook, \u201c\u003Cem\u003EPerformance Analysis and Design of Computer Systems\u003C\/em\u003E,\u201d published by Cambridge University Press 2013.\u0026nbsp; She also has a new textbook coming out called \u201c\u003Cem\u003EIntroduction to Probability for Computing,\u201d\u003C\/em\u003E published by Cambridge University Press 2024. Mor\u2019s work has been honored with many paper awards: INFORMS George Nicholson Prize 22, SIGMETRICS 21, SIGMETRICS 19, PERFORMANCE 18, INFORMS APS 18, EUROSYS 16, MASCOTS 16, MICRO 10, SIGMETRICS 03, ITC 03, SIGMETRICS 96.\u0026nbsp; She has also been blessed with fantastic PhD students, almost all of whom are professors at top universities.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EAlmost all queueing models assume that a job runs on a single server. But this one-server-per-job model is not a good representation of today\u0027s compute jobs.\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003EA typical data center job today occupies multiple cores concurrently.\u0026nbsp; We refer to a job that requires a fixed number of cores for some duration as a multiserver job.\u0026nbsp; Unfortunately, very little is known about the performance of multiserver job queueing models.\u0026nbsp; We present the first results on response time for multiserver job models.\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003ETo do this, we introduce a new scheduling policy, called ServerFilling, which is both\u0026nbsp;throughput-optimal in many settings and also lends itself to response time analysis.\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003EJoint work with:\u003Cstrong\u003E \u003C\/strong\u003E\u0026nbsp;Isaac Grosof and Alan Scheller-Wolf\u0026nbsp;\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Scheduling Multiserver Compute Jobs"}],"uid":"36374","created_gmt":"2023-08-17 12:35:19","changed_gmt":"2023-08-17 12:35:19","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-08-25T11:30:00-04:00","event_time_end":"2023-08-25T12:30:00-04:00","event_time_end_last":"2023-08-25T12:30:00-04:00","gmt_time_start":"2023-08-25 15:30:00","gmt_time_end":"2023-08-25 16:30:00","gmt_time_end_last":"2023-08-25 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"668989":{"#nid":"668989","#data":{"type":"event","title":"ISYE Statistic Seminar - Annie Qu","body":[{"value":"\u003Cp\u003EA Model-Agnostic Graph Neural Network for Integrating Local and Global Information\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGraph neural networks (GNNs) have achieved promising performance in a variety of graph focused\u003C\/p\u003E\r\n\r\n\u003Cp\u003Etasks. Despite their success, the two major limitations of existing GNNs are the capability\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eof learning various-order representations and providing interpretability of such deep learning-based\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eblack-box models. To tackle these issues, we propose a novel Model-agnostic Graph Neural\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENetwork (MaGNet) framework. The proposed framework is able to extract knowledge from\u003C\/p\u003E\r\n\r\n\u003Cp\u003Ehigh-order neighbors, sequentially integrates information of various orders, and offers explanations\u003C\/p\u003E\r\n\r\n\u003Cp\u003Efor the learned model by identifying influential compact graph structures. In particular,\u0026nbsp;MaGNet\u003C\/p\u003E\r\n\r\n\u003Cp\u003Econsists of two components: an estimation model for the latent representation of complex\u003C\/p\u003E\r\n\r\n\u003Cp\u003Erelationships under graph topology, and an interpretation model that identifies influential nodes,\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eedges, and important node features. Theoretically, we establish the generalization error bound for\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMaGNet\u0026nbsp;via empirical Rademacher complexity and showcase its power to represent the layer-wise\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eneighborhood mixing. We conduct comprehensive numerical studies using both simulated data\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eand a real-world case study on investigating the neural mechanisms of the rat hippocampus,\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edemonstrating that the performance of\u0026nbsp;MaGNet\u0026nbsp;is competitive with state-of-the-art methods.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnnie Qu\u003C\/p\u003E\r\n\r\n\u003Cp\u003EChancellor\u2019s Professor, Department of Statistics, University of California Irvine\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D., Statistics, the Pennsylvania State University\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQu\u2019s research focuses on solving fundamental issues regarding structured and unstructured large-scale data, and developing cutting-edge statistical methods and theory in machine learning and algorithms on personalized medicine, text mining, recommender systems, medical imaging data and network data analyses for complex heterogeneous data. The newly developed methods are able to extract essential and relevant information from large volume high-dimensional data. Her research has impacts in many fields such as biomedical studies, genomic research, public health research, social and political sciences.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBefore she joins the UC Irvine, Dr. Qu is Data Science Founder Professor of Statistics, and the Director of the Illinois Statistics Office at the University of Illinois at Urbana-Champaign. She was awarded as Brad and Karen Smith Professorial Scholar by the College of LAS at UIUC, a recipient of the NSF Career award in 2004-2009. She is a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, and a Fellow of American Association for the Advancement of Science. She is also a recipient of Medallion Award and Lecturer. She is JASA Theory and Methods co-editor in 2023-2025.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGraph neural networks (GNNs) have achieved promising performance in a variety of graph focused\u003C\/p\u003E\r\n\r\n\u003Cp\u003Etasks. Despite their success, the two major limitations of existing GNNs are the capability\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eof learning various-order representations and providing interpretability of such deep learning-based\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eblack-box models. To tackle these issues, we propose a novel Model-agnostic Graph Neural\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENetwork (MaGNet) framework. The proposed framework is able to extract knowledge from\u003C\/p\u003E\r\n\r\n\u003Cp\u003Ehigh-order neighbors, sequentially integrates information of various orders, and offers explanations\u003C\/p\u003E\r\n\r\n\u003Cp\u003Efor the learned model by identifying influential compact graph structures. In particular,\u0026nbsp;MaGNet\u003C\/p\u003E\r\n\r\n\u003Cp\u003Econsists of two components: an estimation model for the latent representation of complex\u003C\/p\u003E\r\n\r\n\u003Cp\u003Erelationships under graph topology, and an interpretation model that identifies influential nodes,\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eedges, and important node features. Theoretically, we establish the generalization error bound for\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMaGNet\u0026nbsp;via empirical Rademacher complexity and showcase its power to represent the layer-wise\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eneighborhood mixing. We conduct comprehensive numerical studies using both simulated data\u003C\/p\u003E\r\n\r\n\u003Cp\u003Eand a real-world case study on investigating the neural mechanisms of the rat hippocampus,\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edemonstrating that the performance of\u0026nbsp;MaGNet\u0026nbsp;is competitive with state-of-the-art methods.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A Model-Agnostic Graph Neural Network for Integrating Local and Global Information"}],"uid":"36433","created_gmt":"2023-08-16 13:06:16","changed_gmt":"2023-08-16 13:06:16","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-12T11:00:00-04:00","event_time_end":"2023-09-12T12:00:00-04:00","event_time_end_last":"2023-09-12T12:00:00-04:00","gmt_time_start":"2023-09-12 15:00:00","gmt_time_end":"2023-09-12 16:00:00","gmt_time_end_last":"2023-09-12 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"668988":{"#nid":"668988","#data":{"type":"event","title":"ISYE Statistic Seminar - Sabyasachi Chatterjee","body":[{"value":"\u003Cdiv\u003E\r\n\u003Cdiv dir=\u0022ltr\u0022\u003E\r\n\u003Cdiv dir=\u0022ltr\u0022\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ETITLE\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E:\u0026nbsp; Theory for Cross Validation in Nonparametric Regression\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EABSTRACT\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E:\u0026nbsp; We formulate a general cross validation framework for signal\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Edenoising. The general framework is then applied to nonparametric\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Eregression methods such as Trend Filtering and Dyadic CART. The\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Eresulting cross validated versions are then shown to attain nearly the\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Esame rates of convergence as are known for the optimally tuned\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Eanalogues. There did not exist any previous theoretical analyses of\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003Ecross validated versions of Trend Filtering or Dyadic CART. Our general\u0026nbsp;framework is inspired by the ideas in\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EChatterjee\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;and Jafarov (2015) and\u0026nbsp;is potentially applicable to a wide range of estimation methods which\u0026nbsp;use tuning parameters.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EBIO\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E: I am an Assistant Professor (from 2017 onwards) in the Statistics Department at\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EUniversity\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;of Illinois at Urbana Champaign. Most of my research has been in Nonparametric Function Estimation\/ Statistical Signal Processing. I am also interested in\u0026nbsp;Machine Learning and Probability. I obtained my Phd in 2014 at Yale\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EUniversity\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;and then was a Kruskal Instructor at\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EUniversity\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;of Chicago till 2017\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cdiv\u003E\r\n\u003Cdiv dir=\u0022ltr\u0022\u003E\r\n\u003Cdiv dir=\u0022ltr\u0022\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EWe formulate a general cross validation framework for signal\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003Edenoising. The general framework is then applied to nonparametric\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003Eregression methods such as Trend Filtering and Dyadic CART. The\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003Eresulting cross validated versions are then shown to attain nearly the\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003Esame rates of convergence as are known for the optimally tuned\u0026nbsp;\u003C\/span\u003E\u003Cspan\u003Eanalogues. There did not exist any previous theoretical analyses of\u0026nbsp;\u003C\/span\u003Ecross validated versions of Trend Filtering or Dyadic CART. Our general\u0026nbsp;framework is inspired by the ideas in Chatterjee and Jafarov (2015) and\u0026nbsp;is potentially applicable to a wide range of estimation methods which\u0026nbsp;use tuning parameters.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Theory for Cross Validation in Nonparametric Regression"}],"uid":"36433","created_gmt":"2023-08-16 12:30:44","changed_gmt":"2023-08-16 12:35:13","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-08-29T13:00:00-04:00","event_time_end":"2023-08-29T14:00:00-04:00","event_time_end_last":"2023-08-29T14:00:00-04:00","gmt_time_start":"2023-08-29 17:00:00","gmt_time_end":"2023-08-29 18:00:00","gmt_time_end_last":"2023-08-29 18:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"668842":{"#nid":"668842","#data":{"type":"event","title":"ISyE Seminar Speaker - Sheldon H. Jacobson","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EUsing Computational Algorithms for Political Redistricting\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;Abstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EPolitical redistricting is a multi-criteria problem with conflicting objectives (based on metrics like compactness, population balance, and efficiency gaps, among others). Many of these metrics have received significant attention, though they remain controversial as to which such metrics are best suited to define fair district maps. This\u0026nbsp;research uses\u0026nbsp;a multi-objective optimization approach to reveal obstacles in defining fair district maps. The results obtained challenge a number of common perceptions of redistricting, suggesting that defining fair maps may not only be extremely difficult, but also, simply unrealistic.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EJoint research with Rahul Swamy and Douglas King\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ESheldon H. Jacobson is a Founder Professor of Computer Science at the University of Illinois.\u0026nbsp; He has a B.Sc. and M.Sc. (both in Mathematics) from McGill University, and a M.S. and Ph.D. (both in Operations Research) from Cornell University.\u0026nbsp; From 2012-2014, he was on leave from the University of Illinois, serving as a Program Director at the National Science Foundation.\u0026nbsp; His research interests span theory and practice, covering decision-making under uncertainty and optimization-based artificial intelligence, with applications in aviation security, public policy, public health, and sports.\u0026nbsp; He has been recognized by numerous awards, including a Guggenheim Fellowship from the John Simon Guggenheim Memorial Foundation.\u0026nbsp; He is a fellow of AAAS, IISE, and INFORMS.\u0026nbsp; He serves as the Founding Director for the Institute for Computational Redistricting (ICOR), \u003C\/span\u003E\u003Ca href=\u0022http:\/\/redistricting.cs.illinois.edu\u0022\u003Ehttp:\/\/redistricting.cs.illinois.edu\u003C\/a\u003E\u003Cspan\u003E.\u003C\/span\u003E\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EPolitical redistricting is a multi-criteria problem with conflicting objectives (based on metrics like compactness, population balance, and efficiency gaps, among others). Many of these metrics have received significant attention, though they remain controversial as to which such metrics are best suited to define fair district maps. This\u0026nbsp;research uses\u0026nbsp;a multi-objective optimization approach to reveal obstacles in defining fair district maps. The results obtained challenge a number of common perceptions of redistricting, suggesting that defining fair maps may not only be extremely difficult, but also, simply unrealistic.\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EJoint research with Rahul Swamy and Douglas King\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Using Computational Algorithms for Political Redistricting "}],"uid":"36374","created_gmt":"2023-08-08 20:27:04","changed_gmt":"2023-08-08 20:27:04","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-22T11:30:00-04:00","event_time_end":"2023-09-22T12:30:00-04:00","event_time_end_last":"2023-09-22T12:30:00-04:00","gmt_time_start":"2023-09-22 15:30:00","gmt_time_end":"2023-09-22 16:30:00","gmt_time_end_last":"2023-09-22 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"668483":{"#nid":"668483","#data":{"type":"event","title":"Fall 2023 IISE Career Fair","body":[{"value":"\u003Cp\u003EEvery fall and spring semester, during the IISE Career Fair, companies across the nation come to Georgia Tech to recruit some of the nation\u2019s top talent from our Bachelor\u2019s and Master\u2019s programs. Our students are recruited for a variety of roles and perform well past expectations in all positions. We hope that you will join us this semester and meet some of the country\u2019s brightest students.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis fall semester, we will be hosting an \u003Cstrong\u003Ein-person\u003C\/strong\u003E career fair on \u003Cstrong\u003EThursday, September 21st, 2023\u003C\/strong\u003E, at McCamish Pavilion. We are actively working to enhance your career fair experience through allowing students to see a summary of all companies including majors recruited, years recruited, GPA requirements, and industry. This ensures that students can pinpoint the companies actively recruiting for them helping both students and recruiters! In addition, we will be having a general diagram of company booth locations so students can easily find your booth! If you have any questions or concerns, please email us at \u003Ca href=\u0022mailto:iise@gatech.edu\u0022 title=\u0022mailto:iise@gatech.edu\u0022\u003E\u003Cstrong\u003Eiise@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/gatech-csm.symplicity.com\/events\/485969699eed9376d628826efc602adc\/overview\u0022 target=\u0022_blank\u0022\u003E\u003Cstrong\u003E\u003Cem\u003EEmployer Registration\u003C\/em\u003E\u003C\/strong\u003E\u003C\/a\u003E: \u003Cem\u003E If you register and PAY by August, registration is $850. After August 1st, the payment will be $1000.00.\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cem\u003ERegistration Deadline: September 14, 2023\u003C\/em\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EFall 2023 IISE Career Fair\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Fall 2023 IISE Career Fair"}],"uid":"27764","created_gmt":"2023-07-14 16:15:21","changed_gmt":"2023-07-28 18:07:58","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-21T09:00:00-04:00","event_time_end":"2023-09-21T15:30:00-04:00","event_time_end_last":"2023-09-21T15:30:00-04:00","gmt_time_start":"2023-09-21 13:00:00","gmt_time_end":"2023-09-21 19:30:00","gmt_time_end_last":"2023-09-21 19:30:00","rrule":null,"timezone":"America\/New_York"},"location":"McCamish Pavilion","extras":[],"hg_media":{"671283":{"id":"671283","type":"image","title":"1-iise.jpg","body":null,"created":"1690567631","gmt_created":"2023-07-28 18:07:11","changed":"1690567631","gmt_changed":"2023-07-28 18:07:11","alt":"2023 IISE career fair","file":{"fid":"254310","name":"1-iise.jpg","image_path":"\/sites\/default\/files\/2023\/07\/28\/1-iise.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/07\/28\/1-iise.jpg","mime":"image\/jpeg","size":249090,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/07\/28\/1-iise.jpg?itok=6pjdfZhm"}}},"media_ids":["671283"],"related_links":[{"url":"https:\/\/www.gtiise.org\/career-fair","title":"IISE Career Fair Information"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"4354","name":"career fair"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:iise@gatech.edu\u0022 title=\u0022mailto:iise@gatech.edu\u0022\u003E\u003Cstrong\u003Eiise@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"667111":{"#nid":"667111","#data":{"type":"event","title":"Leadership Development Seminar\/Webinar Series: Featuring Ron Johnson","body":[{"value":"\u003Cp\u003ERonald L. Johnson is a Professor of the Practice in ISyE and Faculty Leadership Fellow at Georgia Tech. Prior to joining the faculty at Georgia Tech, Retired Major General Ronald L. Johnson was the National Basketball Association\u2019s first Senior Vice President, Referee Operations, responsible for all aspects of the NBA\u2019s officiating program, including recruiting, training and development, scheduling, data management and analysis, and work rules enforcement.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPrior to joining the NBA, General Johnson served as the deputy commanding general and deputy chief of engineers (COO), the second highest-ranking senior engineer staff officer for the U.S. Army Corps of Engineers (USACE). He retired in April 2008 after serving 32 years of military service.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFrom October 2005 until his retirement, Johnson was assisting the chief of engineers in maintaining Army Staff oversight for organizing, training, and equipping 70,000 engineer soldiers in the active and reserve components and USACE. He additionally served as the principal engineer advisor to the chief of staff of the Army.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJohnson\u2019s awards and decorations include the Distinguished Service Medal (with two Oak Leaf Clusters), Bronze Star, Legion of Merit (with 4 Oak Leaf Clusters), Combat Action Badge, Parachutist Badge, Air Assault Badge, Army Staff Identification Badge, and the Recruiter Badge.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe look forward to having you attend the event in person or online!\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EZoom Meeting\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/95517853132\u0022 title=\u0022https:\/\/gatech.zoom.us\/j\/95517853132\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/95517853132\u003C\/a\u003E\u003Cbr \/\u003E\r\nMeeting ID: 955 1785 3132\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ERonald L. Johnson is a Professor of the Practice in ISyE and Faculty Leadership Fellow at Georgia Tech. Prior to joining the faculty at Georgia Tech, Retired Major General Ronald L. Johnson was the National Basketball Association\u2019s first Senior Vice President, Referee Operations, responsible for all aspects of the NBA\u2019s officiating program, including recruiting, training and development, scheduling, data management and analysis, and work rules enforcement.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Ronald L. Johnson is a Professor of the Practice in ISyE and Faculty Leadership Fellow at Georgia Tech."}],"uid":"27233","created_gmt":"2023-04-06 12:22:52","changed_gmt":"2023-07-06 17:32:44","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-06T15:30:00-04:00","event_time_end":"2023-04-06T16:00:00-04:00","event_time_end_last":"2023-04-06T16:00:00-04:00","gmt_time_start":"2023-04-06 19:30:00","gmt_time_end":"2023-04-06 20:00:00","gmt_time_end_last":"2023-04-06 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose Building, Room 402 (765 Ferst Drive) OR Zoom","extras":[],"hg_media":{"670463":{"id":"670463","type":"image","title":"rjohnson.jpg","body":null,"created":"1680784242","gmt_created":"2023-04-06 12:30:42","changed":"1680784242","gmt_changed":"2023-04-06 12:30:42","alt":"Ron Johnson","file":{"fid":"253320","name":"rjohnson.jpg","image_path":"\/sites\/default\/files\/2023\/04\/06\/rjohnson.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/04\/06\/rjohnson.jpg","mime":"image\/jpeg","size":17007,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/04\/06\/rjohnson.jpg?itok=UJ4EMy4d"}}},"media_ids":["670463"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"668036":{"#nid":"668036","#data":{"type":"event","title":"SCL September 2023 Supply Chain Day","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain students and employers, please join us for our first fall Supply Chain Day!\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEvent Details\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (Georgia Tech Exhibition Hall)\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EWednesday, September 13, 2023 | 11am - 2pm ET\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003EStudents\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage you to attend to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EOrganizations\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIf you are interested in hosting a table for the upcoming session, please let us know after reviewing the below information within our website.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students and employers, please join us for our first fall Supply Chain Day! We will be hosting an On Campus session\u0026nbsp;Wednesday, September 13, 2023 from 11am-2pm ET at the Georgia Tech Exhibition Hall.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Supply chain and logistics career fair where industry supply chain representatives meet with Georgia Tech students."}],"uid":"27233","created_gmt":"2023-06-08 19:38:41","changed_gmt":"2023-07-06 11:52:44","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-09-13T11:00:00-04:00","event_time_end":"2023-09-13T14:00:00-04:00","event_time_end_last":"2023-09-13T14:00:00-04:00","gmt_time_start":"2023-09-13 15:00:00","gmt_time_end":"2023-09-13 18:00:00","gmt_time_end_last":"2023-09-13 18:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech Exhibition Hall","extras":[],"hg_media":{"670952":{"id":"670952","type":"image","title":"Wednesday, September 13, 2023 Supply Chain Day Career Fair","body":null,"created":"1686253353","gmt_created":"2023-06-08 19:42:33","changed":"1686253353","gmt_changed":"2023-06-08 19:42:33","alt":"Wednesday, September 13, 2023 Supply Chain Day Career Fair","file":{"fid":"253926","name":"homepage-scday_20230913-600px.jpg","image_path":"\/sites\/default\/files\/2023\/06\/08\/homepage-scday_20230913-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/06\/08\/homepage-scday_20230913-600px.jpg","mime":"image\/jpeg","size":80338,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/06\/08\/homepage-scday_20230913-600px.jpg?itok=fY-ixq0S"}}},"media_ids":["670952"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"},{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"659321":{"#nid":"659321","#data":{"type":"event","title":"SCL Course: Creating Business Value with Statistical Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. You\u2019ll learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. You\u2019ll use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand why and how to align Supply Chain Management (SCM) strategy with business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn statistics techniques as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand inventory management models and how to apply statistics techniques to them\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate time series forecasts based on SCM data\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to perform statistical analyses, create time series forecasts and visualize results\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe importance of aligning SCM and business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to ask the right business questions as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to use statistics to identify issues, compare data, and forecast decision outcomes\u003C\/li\u003E\r\n\t\u003Cli\u003EStatistical\u0026nbsp;concepts including variance analysis and hypothesis testing\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EApplying statistics to inventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques including time series forecasting\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models to improve operational performance metrics and align supply chain management with strategic business goals.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models."}],"uid":"27233","created_gmt":"2022-07-08 12:25:44","changed_gmt":"2023-05-17 11:31:42","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-07-10T13:00:00-04:00","event_time_end":"2023-07-13T17:00:00-04:00","event_time_end_last":"2023-07-13T17:00:00-04:00","gmt_time_start":"2023-07-10 17:00:00","gmt_time_end":"2023-07-13 21:00:00","gmt_time_end_last":"2023-07-13 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scabv","title":"Course webpage within the SCL website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"667483":{"#nid":"667483","#data":{"type":"event","title":"ISyE Seminar - Dmitrii Ostrovskii","body":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003ETitle: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ESelf-concordance meets Laplace approximation:\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EFast and optimal algorithm for online portfolio selection\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn 1991, Thomas\u0026nbsp;M.\u0026nbsp;Cover introduced a simple and elegant mathematical model for stock trading, which later on came to be known as\u0026nbsp;online portfolio selection\u0026nbsp;(OPS). In each round\u0026nbsp;t\u0026nbsp;= 1,\u0026nbsp;2, ..., T, the trader selects a\u0026nbsp;portfolio\u2014distribution\u0026nbsp;pt\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u2208\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;R+d\u0026nbsp;of the current capital over the set of\u0026nbsp;d\u0026nbsp;assets; then, the adversary generates a vector\u0026nbsp;rt\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u2208\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ER\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E+\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Ed\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;of\u0026nbsp;returns\u0026nbsp;(i.e.,\u0026nbsp;relative prices of the assets), and the trader\u2019s capital is multiplied by the \u201caggregated return\u201d\u0026nbsp;pt\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u1e59\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Et\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E. The model makes no further assumptions on the asset prices; in particular, they are not assumed to be sampled randomly from a distribution; at the same time, it captures the two key properties of the stock market: that it is naturally adversarial, and that money tends to accummulate multiplicatively. In the 30 years that followed, it had received a great deal of attention across several communities.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the same paper, Cover also proposed an algorithm, termed Universal Portfolios, that admitted a strong performance guarantee: the regret of\u0026nbsp;O(dlog\u0026nbsp;T) against the best portfolio in hindsight, and without any restrictions of returns or portfolios. This guarantee was later on shown to be worst-case optimal; unfortunately, exact computation of a universal portfolio amounts to averaging over a log-concave distribution, which is a challenging task. To address this, Kalai and Vempala (2002) achieved the running time of\u0026nbsp;O(d4T14) per round via sampling techniques. However, with such a running time essentially prohibiting problems of nontrivial size, yet remaining state-of-the-art, the problem of finding an\u0026nbsp;optimal and practical\u0026nbsp;OPS algorithm was left open.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, after discussing some of the arising technical challenges, I shall present a fast and optimal OPS algorithm that combines regret optimality with the runtime of\u0026nbsp;O(d2T), thus dramatically improving state of the art. Its motivation and analysis turn out to be related to establishing a sharp bound on the accuracy of the Laplace approximation for a log-concave distribution with a polyhedral support; this result is of independent interest, and I shall explore the underlying connection. Finally, I shall present a broader perspective of these ideas beyond online portfolio selection.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EBio: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EDmitrii M. Ostrovskii is an Assistant Professor (RTPC) of Mathematics at the University of Southern California. Dmitrii graduated in 2018, advised by Anatoli Juditsky (University of Grenoble) and Zaid Harchaoui (University of Washington), and actively collaborated with Arkadi Nemirovski (Georgia Tech ISyE) when working on his PhD thesis. Prior to the\u0026nbsp;present appointment, he was a postdoc first at Inria Research Institute in Paris, hosted by Francis Bach and funded by the ERCIM Alain Bensoussan fellowship (2018-2019), and then at USC Viterbi School of Engineering (2019-2021). Dmitrii\u0027s interests span several topics at the intersection of optimization theory, mathematical statistics, machine learning, and operations research. In particular, his recent work concerns nonconvex min-max optimization, robust estimation, statistical testing under privacy constraints, and tractable learning algorithms with near-optimal guarantees.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn 1991, Thomas\u0026nbsp;M.\u0026nbsp;Cover introduced a simple and elegant mathematical model for stock trading, which later on came to be known as\u0026nbsp;online portfolio selection\u0026nbsp;(OPS). In each round\u0026nbsp;t\u0026nbsp;= 1,\u0026nbsp;2, ..., T, the trader selects a\u0026nbsp;portfolio\u2014distribution\u0026nbsp;pt\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u2208\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;R+d\u0026nbsp;of the current capital over the set of\u0026nbsp;d\u0026nbsp;assets; then, the adversary generates a vector\u0026nbsp;rt\u0026nbsp;\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u2208\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u0026nbsp;\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ER\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E+\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Ed\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u0026nbsp;of\u0026nbsp;returns\u0026nbsp;(i.e.,\u0026nbsp;relative prices of the assets), and the trader\u2019s capital is multiplied by the \u201caggregated return\u201d\u0026nbsp;pt\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u1e59\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003Et\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E. The model makes no further assumptions on the asset prices; in particular, they are not assumed to be sampled randomly from a distribution; at the same time, it captures the two key properties of the stock market: that it is naturally adversarial, and that money tends to accummulate multiplicatively. In the 30 years that followed, it had received a great deal of attention across several communities.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn the same paper, Cover also proposed an algorithm, termed Universal Portfolios, that admitted a strong performance guarantee: the regret of\u0026nbsp;O(dlog\u0026nbsp;T) against the best portfolio in hindsight, and without any restrictions of returns or portfolios. This guarantee was later on shown to be worst-case optimal; unfortunately, exact computation of a universal portfolio amounts to averaging over a log-concave distribution, which is a challenging task. To address this, Kalai and Vempala (2002) achieved the running time of\u0026nbsp;O(d4T14) per round via sampling techniques. However, with such a running time essentially prohibiting problems of nontrivial size, yet remaining state-of-the-art, the problem of finding an\u0026nbsp;optimal and practical\u0026nbsp;OPS algorithm was left open.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EIn this talk, after discussing some of the arising technical challenges, I shall present a fast and optimal OPS algorithm that combines regret optimality with the runtime of\u0026nbsp;O(d2T), thus dramatically improving state of the art. Its motivation and analysis turn out to be related to establishing a sharp bound on the accuracy of the Laplace approximation for a log-concave distribution with a polyhedral support; this result is of independent interest, and I shall explore the underlying connection. Finally, I shall present a broader perspective of these ideas beyond online portfolio selection.\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Self-concordance meets Laplace approximation:  Fast and optimal algorithm for online portfolio selection"}],"uid":"34977","created_gmt":"2023-04-24 01:24:26","changed_gmt":"2023-04-24 01:25:24","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-25T11:00:00-04:00","event_time_end":"2023-04-25T12:00:00-04:00","event_time_end_last":"2023-04-25T12:00:00-04:00","gmt_time_start":"2023-04-25 15:00:00","gmt_time_end":"2023-04-25 16:00:00","gmt_time_end_last":"2023-04-25 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"667482":{"#nid":"667482","#data":{"type":"event","title":"ISyE Seminar Speaker - Peter Glynn","body":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003ETitle:\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EThe Fragility of Optimized Bandits\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EMuch of the literature on optimal design of bandit algorithms is based on minimization of expected regret. It is well known that algorithms that are optimal over certain exponential families can achieve expected regret that grows logarithmically in the number of trials, at a rate specified by the Lai-Robbins lower bound. In this talk, we point out that when one uses such optimized algorithms, the resulting regret distribution necessarily has a very heavy tail, specifically, that of a truncated Cauchy distribution. We show that optimized UCB algorithms are also fragile in an additional sense, namely when the problem is even slightly mis-specified, the regret can grow much faster than the conventional theory suggests. To alleviate the fragility issues exposed, we show that UCB algorithms can be modified so as to ensure a desired degree of robustness to mis-specification. This is joint work with Lin Fan.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EPeter W. Glynn is the Thomas Ford Professor in the Department of Management Science and Engineering (MS\u0026amp;E) at Stanford University, and also holds a courtesy appointment in the Department of Electrical Engineering. He received his Ph.D in Operations Research from Stanford University in 1982. He then joined the faculty of the University of Wisconsin at Madison, where he held a joint appointment between the Industrial Engineering Department and Mathematics Research Center, and courtesy appointments in Computer Science and Mathematics. In 1987, he returned to Stanford, where he joined the Department of Operations Research. From 1999 to 2005, he served as Deputy Chair of the Department of Management Science and Engineering, and was Director of Stanford\u0027s Institute for Computational and Mathematical Engineering from 2006 until 2010. He served as Chair of MS\u0026amp;E from 2011 through 2015. He is a Fellow of INFORMS and a Fellow of the Institute of Mathematical Statistics, and was an IMS Medallion Lecturer in 1995, a Lunteren Lecturer in 2007, the INFORMS Markov Lecturer in 2014, an Infosys-ICTS Turing Lecturer in 2019, and gave a Titan of Simulation talk at the 2019 Winter Simulation Conference. He was co-winner of the Outstanding Publication Awards from the INFORMS Simulation Society in 1993, 2008, and 2016, was a co-winner of the Best (Biannual) Publication Award from the INFORMS Applied Probability Society in 2009, was the co-winner of the John von Neumann Theory Prize from INFORMS in 2010, and gave the INFORMS Philip McCord Morse Lecture in 2020. In 2012, he was elected to the National Academy of Engineering, and in 2021 he received the Lifetime Professional Achievement Award of the INFORMS Simulation Society. He was Founding Editor-in-Chief of Stochastic Systems and served as Editor-in-Chief of Journal of Applied Probability and Advances in Applied Probability from 2016 to 2018. His research interests lie in simulation, computational probability, queueing theory, statistical inference for stochastic processes, and stochastic modeling.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EMuch of the literature on optimal design of bandit algorithms is based on minimization of expected regret. It is well known that algorithms that are optimal over certain exponential families can achieve expected regret that grows logarithmically in the number of trials, at a rate specified by the Lai-Robbins lower bound. In this talk, we point out that when one uses such optimized algorithms, the resulting regret distribution necessarily has a very heavy tail, specifically, that of a truncated Cauchy distribution. We show that optimized UCB algorithms are also fragile in an additional sense, namely when the problem is even slightly mis-specified, the regret can grow much faster than the conventional theory suggests. To alleviate the fragility issues exposed, we show that UCB algorithms can be modified so as to ensure a desired degree of robustness to mis-specification. This is joint work with Lin Fan.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The Fragility of Optimized Bandits"}],"uid":"36374","created_gmt":"2023-04-22 20:22:10","changed_gmt":"2023-04-22 20:22:10","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-28T11:30:00-04:00","event_time_end":"2023-04-28T12:30:00-04:00","event_time_end_last":"2023-04-28T12:30:00-04:00","gmt_time_start":"2023-04-28 15:30:00","gmt_time_end":"2023-04-28 16:30:00","gmt_time_end_last":"2023-04-28 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Exhibition Hall - Buckhead Room","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"667175":{"#nid":"667175","#data":{"type":"event","title":"ISyE Seminar: Modeling Polio Eradication with Dr. Kimberly M. Thompson","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESeminar Abstract\u003C\/strong\u003E\u003Cbr \/\u003E\r\nIn 1988, the World Health Assembly resolved to eradicate poliomyelitis by the year 2000. As of 2023, the job is not done. Since 2000, analytical modeling of the polio end game has provided critical insights to some national and global decision makers. However, the Global Polio Eradication Initiative (GPEI) partnership has evolved over time, with different perspectives driving the development and implementation of strategic plans. While countries and the GPEI can count many successes, polioviruses still continue to circulate, and in 2022 the US reported a case. This presentation will provide an overview of some of the decision support modeling provided over the last 2 decades, and perspective on what makes modeling impactful (or not) for highly complex global systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbout Dr. Thompson\u003C\/strong\u003E\u003Cbr \/\u003E\r\nDr. Kimberly M. Thompson\u0027s research interests and teaching focus on improving children\u2019s lives and global health by integrating the best available evidence into integrated health risk, economic, and policy models that inform decisions and improve management. While on the faculty at the Harvard School of Public Health, Dr. Thompson created and directed the Harvard Kids Risk Project, which initiated collaborative work with several partners of the Global Polio Eradication Initiative (GPEI) to support polio endgame policy analyses. In late 2008, Dr. Thompson incorporated Kid Risk, Inc. as a self-standing, non-profit organization, which has continued the collaborative work with GPEI partners. In 2014, Dr. Thompson led the U.S. Centers for Disease Control and Prevention (CDC)\/Kid Risk, Inc. team that won the Institute for Operations Research and the Management Sciences (INFORMS) Edelman Award.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn 1988, the World Health Assembly resolved to eradicate poliomyelitis by the year 2000. As of 2023, the job is not done.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"In 1988, the World Health Assembly resolved to eradicate poliomyelitis by the year 2000. As of 2023, the job is not done."}],"uid":"27233","created_gmt":"2023-04-07 17:26:06","changed_gmt":"2023-04-20 11:43:43","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-21T11:30:00-04:00","event_time_end":"2023-04-21T12:30:00-04:00","event_time_end_last":"2023-04-21T12:30:00-04:00","gmt_time_start":"2023-04-21 15:30:00","gmt_time_end":"2023-04-21 16:30:00","gmt_time_end_last":"2023-04-21 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE Main Building, Room 228 (755 Ferst Dr, NW)","extras":[],"hg_media":{"670477":{"id":"670477","type":"image","title":"Dr. Karen Thompson","body":null,"created":"1680888395","gmt_created":"2023-04-07 17:26:35","changed":"1680888395","gmt_changed":"2023-04-07 17:26:35","alt":"Dr. Karen Thompson","file":{"fid":"253341","name":"DrKarenThompson.jpg","image_path":"\/sites\/default\/files\/2023\/04\/07\/DrKarenThompson.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/04\/07\/DrKarenThompson.jpg","mime":"image\/jpeg","size":22213,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/04\/07\/DrKarenThompson.jpg?itok=6ULIiWe6"}}},"media_ids":["670477"],"related_links":[{"url":"https:\/\/hg.gatech.edu\/sites\/default\/files\/documents\/2023-04\/GTISyE_%20Seminar_KThompson_20230421.pdf","title":"Download the Event flyer"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"667378":{"#nid":"667378","#data":{"type":"event","title":"ISyE Seminar Speaker - Kimberly M. Thompson","body":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EModeling Polio Eradication: \u0026nbsp;Insights from 2 Decades of Waiting for the Endgame\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn 1988, the World Health Assembly resolved to eradication poliomyelitis by the year 2000.\u0026nbsp; As of 2023, the job is not done.\u0026nbsp; Since 2000, analytical modeling of the polio end game has provided critical insights to some national and global decision makers.\u0026nbsp; However, the Global Polio Eradication Initiative (GPEI) partnership has evolved over time, with different perspectives driving the development and implementation of strategic plans.\u0026nbsp; While countries and the GPEI can count many successes, polioviruses still continue to circulate, and in 2022 the US reported a case.\u0026nbsp; This presentation will provide an overview of some of the decision support modeling provided over the last 2 decades, and perspective on what makes modeling impactful (or not) for highly complex global systems.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EDr. Kimberly M. Thompson\u0027s research interests and teaching focus on improving children\u2019s lives and global health by integrating the best available evidence into integrated health risk, economic, and policy models that inform decisions and improve management.\u0026nbsp; While on the faculty at the Harvard School of Public Health, Dr. Thompson created and directed the Harvard Kids Risk Project, which initiated collaborative work with several partners of the Global Polio Eradication Initiative (GPEI) to support polio endgame policy analyses.\u0026nbsp; In late 2008, Dr. Thompson incorporated Kid Risk, Inc. as a self-standing, non-profit organization, which has continued the collaborative work with GPEI partners.\u0026nbsp; In 2014, Dr. Thompson led the U.S. Centers for Disease Control and Prevention (CDC)\/Kid Risk, Inc. team that won the Institute for Operations Research and the Management Sciences (INFORMS) Edelman Award.\u0026nbsp; \u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn 1988, the World Health Assembly resolved to eradication poliomyelitis by the year 2000.\u0026nbsp; As of 2023, the job is not done.\u0026nbsp; Since 2000, analytical modeling of the polio end game has provided critical insights to some national and global decision makers.\u0026nbsp; However, the Global Polio Eradication Initiative (GPEI) partnership has evolved over time, with different perspectives driving the development and implementation of strategic plans.\u0026nbsp; While countries and the GPEI can count many successes, polioviruses still continue to circulate, and in 2022 the US reported a case.\u0026nbsp; This presentation will provide an overview of some of the decision support modeling provided over the last 2 decades, and perspective on what makes modeling impactful (or not) for highly complex global systems.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" Modeling Polio Eradication:  Insights from 2 decades of waiting for the endgame"}],"uid":"36374","created_gmt":"2023-04-17 16:01:21","changed_gmt":"2023-04-17 16:01:21","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-21T11:30:00-04:00","event_time_end":"2023-04-21T12:30:00-04:00","event_time_end_last":"2023-04-21T12:30:00-04:00","gmt_time_start":"2023-04-21 15:30:00","gmt_time_end":"2023-04-21 16:30:00","gmt_time_end_last":"2023-04-21 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Main 228","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"659322":{"#nid":"659322","#data":{"type":"event","title":"SCL Course: Supply Chain Risk Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn today\u2019s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop a broader, more comprehensive understanding of how their company\u2019s supply chain may be at risk\u003C\/li\u003E\r\n\t\u003Cli\u003EMore effectively communicate to their company\u2019s stakeholders the realities of supply chain risks\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a cross-functional understanding of the building blocks for an effective Supply Chain Risk Management to be used in their particular business\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove their company\u2019s Supply Chain Risk Mitigation program\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe difference between crisis management and supply chain risk management\u003C\/li\u003E\r\n\t\u003Cli\u003EThe significant long term impact of supply chain disruptions\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy supply chain risk management activities require enterprise wide participation\u003C\/li\u003E\r\n\t\u003Cli\u003EHow companies can take proactive, actionable steps to add significant resiliency to their supply chain operation, often without requiring significant levels of investments\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn today\u2019s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2022-07-08 12:29:43","changed_gmt":"2023-04-14 14:39:46","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-26T08:00:00-04:00","event_time_end":"2023-04-27T13:00:00-04:00","event_time_end_last":"2023-04-27T13:00:00-04:00","gmt_time_start":"2023-04-26 12:00:00","gmt_time_end":"2023-04-27 17:00:00","gmt_time_end_last":"2023-04-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scrm","title":"Course webpage within the SCL website"},{"url":"https:\/\/pe.gatech.edu\/courses\/supply-chain-risk-management","title":"Course registration page"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661474":{"#nid":"661474","#data":{"type":"event","title":"Professional Education Course: Responsive Supply Chain Design and Operations","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm ET each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMeeting demand in a timely and cost-effective manner is important both in public and private supply chains, and heavily depend on the design and operation of these supply chains. Demand is affected by ongoing factors such as local economy, infrastructure, and geographic location, as well as unexpected events such as natural or manmade disasters or other large-scale disruptions. Designing and operating responsive supply chains requires the consideration of uncertainty in timing, scope, scale, and understanding of various topics such as forecasting, distribution network design, and inventory management. This course will examine methods and models for making supply chain design and operational decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for meeting the need of customers and beneficiaries.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through learnings gained from applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help organizations and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a critical knowledge base to make tactical decisions around inventory, routing, and distribution.\u003C\/li\u003E\r\n\t\u003Cli\u003EDeliver best practices to measure and evaluate the efficiency, impact, and outcomes of focused initiatives or ongoing logistics and supply chain operations.\u003C\/li\u003E\r\n\t\u003Cli\u003ETransform the health and humanitarian sectors with increased capacity to participate in planning and strategic decision-making for effective supply-chain management.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENetwork modeling approaches\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for making decisions under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EOther data-driven analytical approaches\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by February 19, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course examines methods and models for making pre-planning decisions and explores the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for sustaining wellness.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term development"}],"uid":"27233","created_gmt":"2022-09-22 21:54:42","changed_gmt":"2023-04-14 14:32:15","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-03T09:30:00-04:00","event_time_end":"2023-04-06T13:00:00-04:00","event_time_end_last":"2023-04-06T13:00:00-04:00","gmt_time_start":"2023-04-03 13:30:00","gmt_time_end":"2023-04-06 17:00:00","gmt_time_end_last":"2023-04-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/responsive-supply-chain-design-and-operations","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/humpps","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"8039","name":"Humanitarian"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661475":{"#nid":"661475","#data":{"type":"event","title":"Professional Education Course: Inventory Management and Resource Allocation in Supply Chains","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMany Supply Chain decisions are concerned with the timely and efficient procurement, allocation, and distribution of resources (e.g. funds, supplies, volunteers, money, employees) through a supply chain network. This course will explore methodologies for \u201cmedium term\u201d decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and supply chain design.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help your organization and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProcurement decisions\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management techniques for a single event versus ongoing operations under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for resource allocation geographically and over time\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the second in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by February 19, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course explores methodologies for tactical decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and transportation decisions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Inventory availability is the most important aspect of customer service, and the cost of inventory is one of the most important entries on a company\u0027s balance sheet."}],"uid":"27233","created_gmt":"2022-09-22 21:57:04","changed_gmt":"2023-04-14 14:32:06","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-17T09:30:00-04:00","event_time_end":"2023-04-20T13:00:00-04:00","event_time_end_last":"2023-04-20T13:00:00-04:00","gmt_time_start":"2023-04-17 13:30:00","gmt_time_end":"2023-04-20 17:00:00","gmt_time_end_last":"2023-04-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/inventory-management-and-resource-allocation-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/invmgmt","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661476":{"#nid":"661476","#data":{"type":"event","title":"Professional Education Course: Systems Operations and Strategic Interactions in Supply Chains","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EOften the lack of cooperation and coordination between organizations or stakeholders lead to inefficiencies, despite having common goals. A systems view is needed to ensure appropriate use of scarce resources to meet the multiple, and often conflicting, short- and long-term goals from multiple constituents. This course will focus on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIdentify opportunities for coordination within organizations and collaboration across organizations for increased efficiency and improved outcomes.\u003C\/li\u003E\r\n\t\u003Cli\u003EDescribe the strategic behavior of decision-makers and the impact of the market (or contract) structure on the participant\u0027s actions and the overall system dynamics.\u003C\/li\u003E\r\n\t\u003Cli\u003EDefine evaluation metrics in alignment with the system goals and structure system operations and incentives that address and evaluate these metrics.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow coordination and collaboration can improve supply chain efficiency and effectiveness\u003C\/li\u003E\r\n\t\u003Cli\u003EHow events, decisions and actions in one part of a system, such as a supply chain, impact other parts of the system\u003C\/li\u003E\r\n\t\u003Cli\u003ESystem-wide inventory variability and costs mitigation and reduction\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation metrics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbout the Course and the\u0026nbsp;HHSCM Course Series\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in a 3-part virtually synchronous professional education program. Register and pay for all three required\u0026nbsp;\u003Ca href=\u0022https:\/\/pe.gatech.edu\/node\/54\u0022\u003EHealth and Humanitarian Supply Chain Management Certificate courses\u003C\/a\u003E\u0026nbsp;and receive a discount of $400 off per course. Enter coupon code\u0026nbsp;\u003Cstrong\u003ESCL-HHS\u003C\/strong\u003E\u0026nbsp;at checkout with the Georgia Tech Professional Education website..\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdditionally, there are scholarships available for the certificate program. Apply at\u0026nbsp;\u003Ca href=\u0022https:\/\/hhls.scl.gatech.edu\/\u0022\u003Ehttps:\/\/hhls.scl.gatech.edu\/\u003C\/a\u003E\u0026nbsp;by February 19, 2023.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EQuestions? Reach out to\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E!\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course focuses on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore conceptual and modeling skills to understand and effectively manage humanitarian response from a systems perspective."}],"uid":"27233","created_gmt":"2022-09-22 22:13:20","changed_gmt":"2023-04-14 14:31:55","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-24T09:30:00-04:00","event_time_end":"2023-04-27T13:00:00-04:00","event_time_end_last":"2023-04-27T13:00:00-04:00","gmt_time_start":"2023-04-24 13:30:00","gmt_time_end":"2023-04-27 17:00:00","gmt_time_end_last":"2023-04-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/systems-operations-and-strategic-interactions-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/humso","title":"Course Details via Center for Health and Humanitarian Systems website"},{"url":"https:\/\/pe.gatech.edu\/certificates\/health-humanitarian-supply-chain-management-certificate","title":"Health \u0026 Humanitarian Supply Chain Management Certificate"},{"url":"https:\/\/hhls.scl.gatech.edu\/","title":"Apply for a Scholarship!"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"667343":{"#nid":"667343","#data":{"type":"event","title":"ISyE Seminar Speaker - Prof. Fabio Sgarbossa -  Advancements in Logistics: The Experience of Logistics 4.0 Lab at NTNU","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Prof. Fabio Sgarbossa\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EShort Bio:\u003C\/strong\u003E\u0026nbsp;Fabio Sgarbossa is Full Professor of Industrial Logistics, leader of the Production Management and Logistics Group at Norwegian University of Science and Technology. He is also responsible of the Logistics 4.0 Lab the Norway\u0027s first logistics laboratory that merges digital technologies with traditional P\u0026amp;L systems, enabling researchers, practitioners, engineers, pioneers, students, and other enthusiasts to come together and collaborate on common ground. His research projects focus on traditional topics as design and management of industrial logistics systems, technological innovation, material handling and warehousing, but also new advanced one, as industry 4.0 and 5.0, human centric design, additive manufacturing, hydrogen supply chain. He has published over 150 publications in relevant international journals, and he is Associate Editor for International Journal of Production Research and member of several editorial boards.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract Seminar:\u003C\/strong\u003E\u0026nbsp;Advancements in Logistics: the experience of Logistics 4.0 Lab at NTNU\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELogistics 4.0 laboratory is the Norway\u0027s first logistics laboratory that merges digital technologies with traditional production and logistics systems, enabling researchers, practitioners, engineers, pioneers, students, and other enthusiasts to come together and collaborate on common ground. Since its establishment, researchers have been carrying out projects in collaboration with partners from industrial and public sectors developing new solutions for making production and logistics systems smarter, greener, more human-centric, more resilient.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this seminar, Prof. Fabio Sgarbossa will present the research activities carried out in some projects, like SmartLIB: Smart Logistics in Library Sector, H2GLASS: Hydrogen Supply Chain, and other ones.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Advancements in Logistics: The Experience of Logistics 4.0 Lab at NTNU"}],"uid":"36458","created_gmt":"2023-04-14 14:09:45","changed_gmt":"2023-04-14 14:21:19","author":"mellis74","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-25T11:00:00-04:00","event_time_end":"2023-04-25T12:00:00-04:00","event_time_end_last":"2023-04-25T12:00:00-04:00","gmt_time_start":"2023-04-25 15:00:00","gmt_time_end":"2023-04-25 16:00:00","gmt_time_end_last":"2023-04-25 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 119","extras":[],"hg_media":{"670543":{"id":"670543","type":"image","title":"Fabio Sgarbossa","body":null,"created":"1681481410","gmt_created":"2023-04-14 14:10:10","changed":"1681481410","gmt_changed":"2023-04-14 14:10:10","alt":"Fabio Sgarbossa","file":{"fid":"253424","name":"Fabio Sgarbossa.jpg","image_path":"\/sites\/default\/files\/2023\/04\/14\/Fabio%20Sgarbossa_1.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/04\/14\/Fabio%20Sgarbossa_1.jpg","mime":"image\/jpeg","size":181324,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/04\/14\/Fabio%20Sgarbossa_1.jpg?itok=IWO-Lygo"}}},"media_ids":["670543"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662934":{"#nid":"662934","#data":{"type":"event","title":"SCL Course: Essentials of Negotiations and Stakeholder Influence (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEssentials of Negotiations and Stakeholder Influence level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u201cDNA\u201d to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u201cno judgement zone\u201d environment.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, project leaders, business unit leaders, operations managers, sales leaders and procurement \u0026amp; supply management-related professionals who are involved with supplier selection, contract development and supplier performance management.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease emphasis negotiation conditioning and philosophy setting before and throughout the entire sourcing engagement process\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance your toolbox of industry standard negotiation prep tools like the SWOT and BATNA\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter prepare for negotiations by leveraging knowledge of key negotiation terms and counter-offer tactics\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove negotiation table techniques and soft skills to direct and redirect negotiation momentum\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten ability to successfully utilize your traditional \u0022comfort zone\u0022 approach in combination with your negotiation team\u2019s strengths by leveraging Personal Negotiation Styles\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENegotiation Conditioning Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Preparation Tools\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Execution Techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStakeholder Engagement \u0026amp; Team Leadership\u003C\/li\u003E\r\n\t\u003Cli\u003ELive Negotiations Simulation \u0026amp; Feedback\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u201cDNA\u201d to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u201cno judgement zone\u201d environment.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations."}],"uid":"27233","created_gmt":"2022-11-07 14:29:23","changed_gmt":"2023-04-14 12:53:32","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-06T13:00:00-04:00","event_time_end":"2023-04-17T17:00:00-04:00","event_time_end_last":"2023-04-17T17:00:00-04:00","gmt_time_start":"2023-04-06 17:00:00","gmt_time_end":"2023-04-17 21:00:00","gmt_time_end_last":"2023-04-17 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/epn","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"659320":{"#nid":"659320","#data":{"type":"event","title":"SCL Course: Transforming Supply Chain Management and Performance Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in the four-course Supply Chain Analytics Professional certificate program. It prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. You\u2019ll learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the most relevant planning challenges across the strategic, tactical, and operational levels of supply chains\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the difference between analytics types, the links between them, and how to best use them to improve\u0026nbsp;supply chain management (SCM)\u0026nbsp;processes\u003C\/li\u003E\r\n\t\u003Cli\u003EUse\u0026nbsp;Key Performance Indicators (KPIs)\u0026nbsp;to find causes of underperformance in supply chains and to plan for analytics projects that will address strategic SCM goals\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to understand, visualize, and analyze data in order to prepare for deeper analytics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe role of analytics in SCM\u003C\/li\u003E\r\n\t\u003Cli\u003ETypes of analytics (descriptive, diagnostic, predictive, and prescriptive) and the relationships between them\u003C\/li\u003E\r\n\t\u003Cli\u003EPreprocessing (cleaning and integrating) data as it relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EConducting exploratory data analysis on supply chain data\u003C\/li\u003E\r\n\t\u003Cli\u003EBest practices for visualizing data and building dashboards\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentifying and analyzing KPIs of SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to apply leading-edge analytical methods and technology enablers across the supply chain"}],"uid":"27233","created_gmt":"2022-07-08 12:22:29","changed_gmt":"2023-04-14 12:49:44","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-05-15T13:00:00-04:00","event_time_end":"2023-05-18T17:00:00-04:00","event_time_end_last":"2023-05-18T17:00:00-04:00","gmt_time_start":"2023-05-15 17:00:00","gmt_time_end":"2023-05-18 21:00:00","gmt_time_end_last":"2023-05-18 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scapa","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"667201":{"#nid":"667201","#data":{"type":"event","title":"ISyE Seminar Speaker - Tony Cai","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EOptimal Statistical Estimation under Nonstatistical Constraints\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EAbstract:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the conventional statistical framework, a major goal is to develop optimal statistical procedures based on the sample size and statistical model. However, in many contemporary applications, non-statistical concerns such as privacy and communication constraints associated with the statistical procedures become crucial. This raises a fundamental question in data science: how can we make optimal statistical inference under these non-statistical constraints?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, we explore recent advances in differentially private learning and distributed learning under communication constraints in a few specific settings. Our results demonstrate novel and interesting phenomena and suggest directions for further investigation.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EBio:\u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EEducation:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EPh.D., Cornell University, 1996.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAcademic Appointments:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDaniel H. Silberberg Professor, Professor of Statistics and Data Science, The Wharton School.\u003C\/li\u003E\r\n\t\u003Cli\u003EProfessor, Applied Math. \u0026amp; Computational Science Graduate Group.\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Scholar, Dept. of Biostatistics, Epidemiology, \u0026amp; Bioinformatics, Perelman School of Medicine.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAdministrative Appointment:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EVice Dean for China Initiatives, The Wharton School, 2017-2020\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EEditorial Appointments:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EEditor,\u0026nbsp;\u003Cem\u003EThe Annals of Statistics\u003C\/em\u003E, 2010-2012\r\n\r\n\t\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Editor,\u0026nbsp;\u003Cem\u003EJournal of the Royal Statistical Society, Series B\u003C\/em\u003E, 2014-2018\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Editor,\u0026nbsp;\u003Cem\u003EJournal of the American Statistical Association\u003C\/em\u003E, 2005-2010\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Editor,\u0026nbsp;\u003Cem\u003EThe Annals of Statistics\u003C\/em\u003E, 2004-2009\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Editor,\u0026nbsp;\u003Cem\u003EStatistica Sinica\u003C\/em\u003E, 2005-2011\u003C\/li\u003E\r\n\t\u003Cli\u003EAssociate Editor,\u0026nbsp;\u003Cem\u003EStatistics Surveys\u003C\/em\u003E, 2006-2009\u003C\/li\u003E\r\n\t\u003Cli\u003EEditorial Board,\u0026nbsp;\u003Cem\u003EFrontiers of Statistics\u003C\/em\u003E\u0026nbsp;book series, 2009-present\u003C\/li\u003E\r\n\t\u003Cli\u003EGuest Editor,\u0026nbsp;\u003Cem\u003EStatistica Sinica\u003C\/em\u003E\u0026nbsp;Special Issue on Multiscale Methods\u003C\/li\u003E\r\n\t\u003Cli\u003EGuest Editor,\u0026nbsp;\u003Cem\u003EJournal of Nonparametric Statistics\u003C\/em\u003E\u0026nbsp;Special Issue for the Inaugural IMS-China International Conference\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EHonors \u0026amp; Awards:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELaplace Lecturer of the Bernoulli Society, 10th World Congress in Probability \u0026amp; Statistics, 2021\u003C\/li\u003E\r\n\t\u003Cli\u003EInternational Chinese Statistical Association Distinguished Achievement Award, 2019\u003C\/li\u003E\r\n\t\u003Cli\u003EPeter Whittle Lecturer, Cambridge University, 2018\u003C\/li\u003E\r\n\t\u003Cli\u003EICCM Best Paper Award, 2018\u003C\/li\u003E\r\n\t\u003Cli\u003EPresident, the International Chinese Statistical Association, 2017\u003C\/li\u003E\r\n\t\u003Cli\u003EHermann Otto Hirschfeld Lecturer, Humboldt-Universit\u00e4t zu Berlin, 2012\u003C\/li\u003E\r\n\t\u003Cli\u003EForum Lecturer, 28th European Meeting of Statisticians, Piraeus, Greece, 2010\u003C\/li\u003E\r\n\t\u003Cli\u003EMedallion Lecturer, Institute of Mathematical Statistics, 2009\u003C\/li\u003E\r\n\t\u003Cli\u003EThe\u0026nbsp;\u003Ca href=\u0022http:\/\/en.wikipedia.org\/wiki\/COPSS_Presidents\u0027_Award\u0022\u003ECOPSS Presidents\u0027 Award\u003C\/a\u003E, Committee of Presidents of Statistical Societies, 2008\u003C\/li\u003E\r\n\t\u003Cli\u003EFellow, Institute of Mathematical Statistics, 2006\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EResearch Interests:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHigh-dimensional statistics\u003C\/li\u003E\r\n\t\u003Cli\u003EStatistical machine learning\u003C\/li\u003E\r\n\t\u003Cli\u003ELarge-scale inference\u003C\/li\u003E\r\n\t\u003Cli\u003EFunctional data analysis\u003C\/li\u003E\r\n\t\u003Cli\u003EStatistical decision theory\u003C\/li\u003E\r\n\t\u003Cli\u003ENonparametric function estimation\u003C\/li\u003E\r\n\t\u003Cli\u003EApplications to genomics, chemical identification, and medical imaging\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EPublications:\u0026nbsp;\u003C\/strong\u003E\u003Ca href=\u0022http:\/\/www-stat.wharton.upenn.edu\/~tcai\/Papers.html\u0022\u003EPapers can be downloaded here.\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EProfessional Society Membership:\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EInstitute of Mathematical Statistics (IMS)\u003C\/li\u003E\r\n\t\u003Cli\u003EInstitute of Electrical and Electronics Engineers (IEEE)\u003C\/li\u003E\r\n\t\u003Cli\u003EAmerican Statistical Association (ASA)\u003C\/li\u003E\r\n\t\u003Cli\u003EInternational Chinese Statistical Association (ICSA)\u003C\/li\u003E\r\n\t\u003Cli\u003EAmerican Association for the Advancement of Science (AAAS)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EIn the conventional statistical framework, a major goal is to develop optimal statistical procedures based on the sample size and statistical model. However, in many contemporary applications, non-statistical concerns such as privacy and communication constraints associated with the statistical procedures become crucial. This raises a fundamental question in data science: how can we make optimal statistical inference under these non-statistical constraints?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn this talk, we explore recent advances in differentially private learning and distributed learning under communication constraints in a few specific settings. Our results demonstrate novel and interesting phenomena and suggest directions for further investigation.\u003C\/span\u003E\u003C\/span\u003E\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Optimal Statistical Estimation under Nonstatistical Constraints"}],"uid":"36374","created_gmt":"2023-04-10 14:50:38","changed_gmt":"2023-04-10 14:50:38","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-14T11:30:00-04:00","event_time_end":"2023-04-14T12:30:00-04:00","event_time_end_last":"2023-04-14T12:30:00-04:00","gmt_time_start":"2023-04-14 15:30:00","gmt_time_end":"2023-04-14 16:30:00","gmt_time_end_last":"2023-04-14 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Main 228","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"667196":{"#nid":"667196","#data":{"type":"event","title":"ISyE Statistics Seminar - Tracy Ke","body":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EText analysis is an interesting research area in data science and has various applications, such as in artificial intelligence, biomedical research, and engineering. In this talk, I will review popular methods for text analysis, ranging from topic modeling to the recent neural language models. In particular, I will introduce Topic-SCORE (Ke and Wang, 2022), a statistical approach to topic modeling, and discuss how to use it to analyze MADStat - a dataset on statistical publications that we collected and cleaned on our own. The application of Topic-SCORE and other methods on MADStat leads to interesting findings. For example, 11 representative topics in statis- tics are identified. For each journal, the evolution of topic weights over time can be visualized, and these results are used to analyze the trends in statistical research. In particular, we propose a new statistical model for ranking the citation impacts of 11 topics, and we also build a cross- topic citation graph to illustrate how research results on different topics spread to one another.\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003EText analysis is an interesting research area in data science and has various applications, such as in artificial intelligence, biomedical research, and engineering. In this talk, I will review popular methods for text analysis, ranging from topic modeling to the recent neural language models. In particular, I will introduce Topic-SCORE (Ke and Wang, 2022), a statistical approach to topic modeling, and discuss how to use it to analyze MADStat - a dataset on statistical publications that we collected and cleaned on our own. \u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Recent Advances in Text Analysis"}],"uid":"36358","created_gmt":"2023-04-10 13:22:48","changed_gmt":"2023-04-10 13:49:54","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-18T11:00:00-04:00","event_time_end":"2023-04-18T12:00:00-04:00","event_time_end_last":"2023-04-18T12:00:00-04:00","gmt_time_start":"2023-04-18 15:00:00","gmt_time_end":"2023-04-18 16:00:00","gmt_time_end_last":"2023-04-18 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ISyE -  Main 126","extras":["free_food"],"hg_media":{"670482":{"id":"670482","type":"image","title":"4.18.2023.Tracy_.Ke_.PNG","body":null,"created":"1681133898","gmt_created":"2023-04-10 13:38:18","changed":"1681133898","gmt_changed":"2023-04-10 13:38:18","alt":"ISyE Statistics Seminar- Tracy Ke ","file":{"fid":"253346","name":"4.18.2023.Tracy_.Ke_.PNG","image_path":"\/sites\/default\/files\/2023\/04\/10\/4.18.2023.Tracy_.Ke_.PNG","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/04\/10\/4.18.2023.Tracy_.Ke_.PNG","mime":"image\/png","size":1239846,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/04\/10\/4.18.2023.Tracy_.Ke_.PNG?itok=E0UXi0rb"}}},"media_ids":["670482"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665221":{"#nid":"665221","#data":{"type":"event","title":"SCL IRC Seminar: Supply Chain and Logistics Innovation Showcase","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe will hear from two seasoned founders of supply chain organizations who navigated the ups and downs of building a company from scratch. They will share their personal experiences and insights into the challenges and successes and their early experiences of being part of the Advanced Technology Development Center (ATDC).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKERS\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/sr98bj\u0022\u003EBarbara Jones\u003C\/a\u003E of \u003Ca href=\u0022https:\/\/freeingreturns.com\/\u0022\u003EFreeing Returns\u003C\/a\u003E and \u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/michaelmalakhov\u0022\u003EMichael Malakhov\u003C\/a\u003E of \u003Ca href=\u0022https:\/\/carpoollogistics.com\/\u0022\u003ECarpool Logistics\u003C\/a\u003E (Panelists).\u0026nbsp;\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/alex-rhodeen\u0022\u003EAlex Rhodeen\u003C\/a\u003E,\u0026nbsp;Supply Chain Catalyst,\u0026nbsp;ATDC\u0026nbsp;(Moderator)\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person and wish to order lunch, the cost to attend is $5 per session\u003C\/strong\u003E. Virtual attendance is always free*.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E*Please see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2023-01-27 22:55:27","changed_gmt":"2023-03-30 19:02:47","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-20T13:00:00-04:00","event_time_end":"2023-04-20T14:30:00-04:00","event_time_end_last":"2023-04-20T14:30:00-04:00","gmt_time_start":"2023-04-20 17:00:00","gmt_time_end":"2023-04-20 18:30:00","gmt_time_end_last":"2023-04-20 18:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Hybrid Event (ISyE Building and Online via Zoom)","extras":[],"hg_media":{"670380":{"id":"670380","type":"image","title":"GTSCL-SCLIRC20230416_16by9.jpg","body":null,"created":"1680202688","gmt_created":"2023-03-30 18:58:08","changed":"1680202688","gmt_changed":"2023-03-30 18:58:08","alt":"SCL IRC Seminar April 20, 2023","file":{"fid":"253217","name":"GTSCL-SCLIRC20230416_16by9.jpg","image_path":"\/sites\/default\/files\/2023\/03\/30\/GTSCL-SCLIRC20230416_16by9.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/2023\/03\/30\/GTSCL-SCLIRC20230416_16by9.jpg","mime":"image\/jpeg","size":164132,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/03\/30\/GTSCL-SCLIRC20230416_16by9.jpg?itok=1iJrCWJ5"}}},"media_ids":["670380"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"666780":{"#nid":"666780","#data":{"type":"event","title":"ISyE Seminar Speaker - Daniel Bienstock","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESolving ACOPF Problems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe ACOPF problem concerns the optimal selection of an operating point for an electrical power grid.\u0026nbsp; Even though the problem was initially formulated in the early 1960s, it is now gaining increased prominence due to impending changes in the electrical power delivery, which are placing increased pressure on simple approximations now used in operations.\u0026nbsp; We will begin the talk by describing\u0026nbsp;our participation in an ongoing and previous instances of an ARPA-E-run competition on ACOPF, which uses modern and highly extended (and realistic) formulations for the problem, together with very large-size and realistic data sets with demanding computational requirements.\u0026nbsp; We will then explore challenges in implementing robust and fast ACOPF solvers using standardized software (the meaning for this statement will be made clear in the talk).\u0026nbsp; Finally we will conclude with some observations on purely linear formulations for ACOPF.\u0026nbsp; This is joint work with several authors.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDaniel Bienstock is Liu Family Professor of Operations Research, with joint appointments in Applied Math and Electrical Engineering, at Columbia University.\u0026nbsp; His work focuses on high-performance algorithms for nonconvex optimization, with focus on large-scale cases; and with an additional focus on problems arising in engineering.\u0026nbsp; He became an Informs Fellow in 2013 and received the Khachiyan Prize in Optimization in 2022.\u0026nbsp; He received a PhD from MIT in Operations Research.\u003C\/p\u003E\r\n","summary":"","format":"basic_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe ACOPF problem concerns the optimal selection of an operating point for an electrical power grid.\u0026nbsp; Even though the problem was initially formulated in the early 1960s, it is now gaining increased prominence due to impending changes in the electrical power delivery, which are placing increased pressure on simple approximations now used in operations.\u0026nbsp; We will begin the talk by describing\u0026nbsp;our participation in an ongoing and previous instances of an ARPA-E-run competition on ACOPF, which uses modern and highly extended (and realistic) formulations for the problem, together with very large-size and realistic data sets with demanding computational requirements.\u0026nbsp; We will then explore challenges in implementing robust and fast ACOPF solvers using standardized software (the meaning for this statement will be made clear in the talk).\u0026nbsp; Finally we will conclude with some observations on purely linear formulations for ACOPF.\u0026nbsp; This is joint work with several authors.\u003C\/p\u003E\r\n","format":"basic_html"}],"field_summary_sentence":[{"value":"Solving ACOPF Problems"}],"uid":"36374","created_gmt":"2023-03-23 17:20:35","changed_gmt":"2023-03-23 20:57:09","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-31T11:30:00-04:00","event_time_end":"2023-03-31T12:30:00-04:00","event_time_end_last":"2023-03-31T12:30:00-04:00","gmt_time_start":"2023-03-31 15:30:00","gmt_time_end":"2023-03-31 16:30:00","gmt_time_end_last":"2023-03-31 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Main 228","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"666781":{"#nid":"666781","#data":{"type":"event","title":"ISyE Seminar Speaker - Shane Henderson","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EModeling the Impact of Community First Responders\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBody:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPatient survival from out-of-hospital cardiac arrest (OHCA) can be improved by augmenting traditional ambulance response with the dispatch of community first responders (volunteers) who are alerted via an app. How many volunteers are needed, from where should volunteers be recruited, and how should they be dispatched? We use a combination of Poisson point process modeling and convex optimization to address the first two questions; the right areas from which to recruit are not always obvious, because volunteers recruited from one area may spend time in various areas across a city. We use a combination of dynamic programming and decision trees to answer the last question, balancing the goal of a fast response to the current patient with the need to avoid disengagement of volunteers that arises when multiple volunteers respond. A case study for Auckland, New Zealand demonstrates the ideas.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;This is joint work with Pieter van den Berg, Oce\u0301ane Fourmentraux, Caroline Jagtenberg, and Hemeng (Maggie) Li\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProfessor Shane G. Henderson holds the Charles W. Lake, Jr. Chair in Productivity in the School of Operations Research and Information Engineering (ORIE) at Cornell University. His research interests include discrete-event simulation, simulation optimization, emergency services planning and transportation. He is the editor in chief of the open-access journal\u0026nbsp;\u003Ca href=\u0022http:\/\/pubsonline.informs.org\/journal\/stsy\u0022\u003EStochastic Systems\u003C\/a\u003E. He is an INFORMS Fellow and a co-recipient of the INFORMS Wagner Prize for his work on bike-sharing programs. He has served as Director of the School of ORIE, as chair of the INFORMS Applied Probability Society, and as simulation area editor for\u0026nbsp;\u003Cem\u003EOperations Research\u003C\/em\u003E. He has previously held positions in the Department of Industrial and Operations Engineering at the University of Michigan and the Department of Engineering Science at the University of Auckland. He likes cats, climbing walls, biking, Harry Potter and being a Dad.\u003C\/p\u003E\r\n","summary":"","format":"basic_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPatient survival from out-of-hospital cardiac arrest (OHCA) can be improved by augmenting traditional ambulance response with the dispatch of community first responders (volunteers) who are alerted via an app. How many volunteers are needed, from where should volunteers be recruited, and how should they be dispatched? We use a combination of Poisson point process modeling and convex optimization to address the first two questions; the right areas from which to recruit are not always obvious, because volunteers recruited from one area may spend time in various areas across a city. We use a combination of dynamic programming and decision trees to answer the last question, balancing the goal of a fast response to the current patient with the need to avoid disengagement of volunteers that arises when multiple volunteers respond. A case study for Auckland, New Zealand demonstrates the ideas.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is joint work with Pieter van den Berg, Oce\u0301ane Fourmentraux, Caroline Jagtenberg, and Hemeng (Maggie) Li\u003C\/p\u003E\r\n","format":"basic_html"}],"field_summary_sentence":[{"value":"Modeling the Impact of Community First Responders"}],"uid":"36374","created_gmt":"2023-03-23 17:34:07","changed_gmt":"2023-03-23 20:56:53","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-07T11:30:00-04:00","event_time_end":"2023-04-07T12:30:00-04:00","event_time_end_last":"2023-04-07T12:30:00-04:00","gmt_time_start":"2023-04-07 15:30:00","gmt_time_end":"2023-04-07 16:30:00","gmt_time_end_last":"2023-04-07 16:30:00","rrule":null,"timezone":"America\/New_York"},"location":" ISYE Main 228","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"666647":{"#nid":"666647","#data":{"type":"event","title":" IEN Soft Lithography Short Course","body":[{"value":"\u003Cdiv\u003E\r\n\u003Cp\u003EThe Institute for Electronics and Nanotechnology (IEN) at Georgia Tech will offer a short course on Soft Lithography for Microfluidics on April 13 - 14, 2023. This course module is designed for individuals interested in hands-on training in the fabrication of microfluidic devices using the soft lithography technique. This two-day intensive short course will be structured to assume no prior knowledge of the technologies by the participants. The course agenda is evenly divided between laboratory hands-on sessions, including SU-8 master mold creation using photolithography, and PDMS device fabrication in the IEN cleanroom, and supporting lectures.\u0026nbsp; The goal of this course is to impart a basic understanding of soft lithography for microfluidic applications as practiced in academia and industry.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003ESpring 2023 Rates\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EGeorgia Tech attendee - $150\u003Cbr \/\u003E\r\nAcademic or government attendee - $300\u003Cbr \/\u003E\r\nIndustry attendee - $600\u003C\/p\u003E\r\n\r\n\u003Cp\u003E* Lunch and break refreshments are included\u003C\/p\u003E\r\n\r\n\u003Ch5\u003E\u003Ca href=\u0022https:\/\/research.gatech.edu\/nano\/ien-soft-lithography-short-course\u0022\u003ELearn more about the course and register.\u003C\/a\u003E\u003C\/h5\u003E\r\n\u003C\/div\u003E\r\n","summary":"","format":"basic_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Institute for Electronics and Nanotechnology (IEN) at Georgia Tech will offer a short course on Soft Lithography for Microfluidics on April 13 - 14, 2023.\u003C\/p\u003E\r\n","format":"basic_html"}],"field_summary_sentence":[{"value":"The Institute for Electronics and Nanotechnology (IEN) at Georgia Tech will offer a short course on Soft Lithography for Microfluidics on April 13 - 14, 2023. "}],"uid":"34760","created_gmt":"2023-03-17 19:16:54","changed_gmt":"2023-03-17 19:22:18","author":"Laurie Haigh","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-13T09:00:00-04:00","event_time_end":"2023-04-13T17:00:00-04:00","event_time_end_last":"2023-04-13T17:00:00-04:00","gmt_time_start":"2023-04-13 13:00:00","gmt_time_end":"2023-04-13 21:00:00","gmt_time_end_last":"2023-04-13 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Marcus Nanotechnology Building, 345 Ferst Drive","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EPaul Joseph\u003C\/strong\u003E\u003Cbr \/\u003E\r\nPrincipal Research Scientist\u003Cbr \/\u003E\r\nInstitute for Electronics and Nanotechnology\u003Cbr \/\u003E\r\npaul.joseph@ien.gatech.edu\u003Cbr \/\u003E\r\n404.894.3360\u003C\/p\u003E\r\n","format":"basic_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"666539":{"#nid":"666539","#data":{"type":"event","title":"ISyE Seminar- Ralph Smith","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EEngineering and biological models generally have a number of parameters which are nonidentifiable in the sense that they are not uniquely determined by measured responses.\u0026nbsp; Furthermore, the computational cost of high-fidelity simulation codes often precludes their direct use for Bayesian model calibration and uncertainty propagation.\u0026nbsp; In this presentation, we will discuss techniques to isolate influential parameters for subsequent surrogate model construction, Bayesian inference and uncertainty propagation.\u0026nbsp; For parameter selection, we will discuss advantages and shortcomings of global sensitivity analysis to isolate influential inputs and detail the use of parameter subset selection and active subspace techniques as an alternative.\u0026nbsp; We will also discuss the manner in which Bayesian calibration on active subspaces can be used to quantify uncertainties in physical parameters.\u0026nbsp; These techniques will be illustrated for models arising in nuclear power plant design and quantitative systems pharmacology (QSP), as well as models for transductive materials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBiography:\u003C\/strong\u003E Ralph C. Smith joined the North Carolina State University faculty in 1998 where he is presently a Distinguished University Professor of Mathematics.\u0026nbsp; He is co-author of the research monograph \u003Cem\u003ESmart Material Structures: Modeling, Estimation and Control\u003C\/em\u003E and author of the books \u003Cem\u003ESmart Material Systems: Model Development\u003C\/em\u003E and \u003Cem\u003EUncertainty Quantification: Theory, Implementation, and Applications\u003C\/em\u003E.\u0026nbsp; He is on the editorial boards of the \u003Cem\u003EJournal of Intelligent Material Systems and Structures\u003C\/em\u003E and the \u003Cem\u003ESIAM\/ASA Journal on Uncertainty Quantification\u003C\/em\u003E. He is the recipient of the 2016 ASME \u003Cem\u003EAdaptive Structures and Material Systems Prize \u003C\/em\u003Eand the SPIE 2017 \u003Cem\u003ESmart Structures and Materials Lifetime Achievement, \u003C\/em\u003Eand he was named a \u003Cem\u003ESIAM Fellow\u003C\/em\u003E in 2018 and an \u003Cem\u003EASME Fellow\u003C\/em\u003E in 2022\u003Cem\u003E. \u003C\/em\u003EHis research areas include mathematical modeling of smart material systems, numerical analysis and methods for physical systems, Bayesian model calibration, sensitivity analysis, control, and uncertainty quantification for physical and biological systems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Parameter Subset Selection and Active Subspace Techniques for Engineering and Biological Models"}],"uid":"36358","created_gmt":"2023-03-08 19:10:15","changed_gmt":"2023-03-09 14:23:10","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-27T12:00:00-04:00","event_time_end":"2023-03-27T13:15:00-04:00","event_time_end_last":"2023-03-27T13:15:00-04:00","gmt_time_start":"2023-03-27 16:00:00","gmt_time_end":"2023-03-27 17:15:00","gmt_time_end_last":"2023-03-27 17:15:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"666540":{"#nid":"666540","#data":{"type":"event","title":"ISyE Statistics Seminar- Zhuoran Yang","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe study offline reinforcement learning under a novel model called strategic MDP, which characterizes the strategic interactions between a principal and a sequence of myopic agents with private types. Due to the bilevel structure and private types, strategic MDP involves information asymmetry between the principal and the agents. We focus on the offline RL problem, where the goal is to learn the optimal policy of the principal concerning a target population of agents based on a pre-collected dataset that consists of historical interactions. The unobserved private types confound such a dataset as they affect both the rewards and observations received by the principal. We propose a novel algorithm, Pessimistic policy Learning with Algorithmic iNstruments (PLAN), which leverages the ideas of instrumental variable regression and the pessimism principle to learn a near-optimal principal\u0026#39;s policy in the context of general function approximation. Our algorithm is based on the critical observation that the principal\u0026#39;s actions serve as valid instrumental variables. In particular, under a partial coverage assumption on the offline dataset, we prove that PLAN outputs a nearly optimal policy at a root-N statistical rate, where N is the number of trajectories. We further apply our framework to some special cases of strategic MDP, including strategic regression, strategic bandit, and noncompliance in recommendation systems. This is joint work with Mengxin Yu and Jianqing Fan.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EZhuoran Yang is an Assistant Professor of Statistics and Data Science at Yale University, starting in July 2022. His research interests lie in the interface between machine learning, statistics, and optimization. He is particularly interested in the foundations of reinforcement learning, representation learning, and deep learning. Before joining Yale, Zhuoran worked as a postdoctoral researcher at the University of California, Berkeley, advised by Michael. I. Jordan. Prior to that, he obtained his Ph.D. from the Department of Operations Research and Financial Engineering at Princeton University, co-advised by Jianqing Fan and Han Liu. He received his bachelor\u0026rsquo;s degree in Mathematics from Tsinghua University in 2015.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments"}],"uid":"36358","created_gmt":"2023-03-08 19:15:25","changed_gmt":"2023-03-08 19:16:33","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-15T15:11:00-04:00","event_time_end":"2023-03-15T15:11:00-04:00","event_time_end_last":"2023-03-15T15:11:00-04:00","gmt_time_start":"2023-03-15 19:11:00","gmt_time_end":"2023-03-15 19:11:00","gmt_time_end_last":"2023-03-15 19:11:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"666493":{"#nid":"666493","#data":{"type":"event","title":"Leadership Development Seminar\/Webinar Series: Featuring Josh Roberts","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJosh Roberts\u003C\/strong\u003E\u0026nbsp;is an energetic, results-oriented healthcare executive with over 20 years of industry and management consulting experience leading and managing large-scale enterprise transformation. He has demonstrated the ability to develop and implement innovative and sustainable business solutions while cultivating sponsorship and advocacy across all organizational levels. He has deep experience relative to hospital operations, physician practice management\/alignment, and healthcare strategy formulation\/execution.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECurrently, Mr. Roberts serves as the Chief Operating Officer (COO) for Piedmont Atlanta Hospital. He has a passion for improving healthcare delivery. He feels a sense of purpose from helping people solve problems and gets his energy from teaching and coaching others.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMr. Roberts received his MBA from the University of Georgia and his B.S. degree from the Georgia Institute of Technology in Industrial Engineering.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe look forward to having you attend the event in person or online!\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EZoom Meeting\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/93695197551?pwd=ZXVqRW84L0htVHQ4K0pIUnlTKzhnQT09\u0022 title=\u0022https:\/\/gatech.zoom.us\/j\/93695197551?pwd=ZXVqRW84L0htVHQ4K0pIUnlTKzhnQT09\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/93695197551?pwd=ZXVqRW84L0htVHQ4K0pIUnlTKzhnQT09\u003C\/a\u003E\u003Cbr \/\u003E\r\nMeeting ID: 936 9519 7551\u003Cbr \/\u003E\r\nPasscode: 432854\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Josh Roberts serves as the Chief Operating Officer (COO) for Piedmont Atlanta Hospital"}],"uid":"27233","created_gmt":"2023-03-07 16:08:50","changed_gmt":"2023-03-07 16:12:15","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-16T15:30:00-05:00","event_time_end":"2023-02-16T16:00:00-05:00","event_time_end_last":"2023-02-16T16:00:00-05:00","gmt_time_start":"2023-02-16 20:30:00","gmt_time_end":"2023-02-16 21:00:00","gmt_time_end_last":"2023-02-16 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"666492":{"id":"666492","type":"image","title":"Josh Roberts, Chief Operating Officer (COO),\u00a0Piedmont Atlanta Hospital","body":null,"created":"1678205309","gmt_created":"2023-03-07 16:08:29","changed":"1678205309","gmt_changed":"2023-03-07 16:08:29","alt":"","file":{"fid":"252005","name":"jroberts.jpg","image_path":"\/sites\/default\/files\/images\/jroberts.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/jroberts.jpg","mime":"image\/jpeg","size":25262,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/jroberts.jpg?itok=HCm69ROx"}}},"media_ids":["666492"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"666222":{"#nid":"666222","#data":{"type":"event","title":"Leadership Development Seminar\/Webinar Series: Featuring Ron Nash","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ERon Nash\u003C\/strong\u003E\u0026nbsp;is the Managing Director of Nash Technology Group and the author of \u0026ldquo;The Making of a Business Leader.\u0026rdquo; Previously, he served as Sr. Advisor for Transformation and Reform for the US Department of Defense. He was the CEO and Board Member at Pivot3, a leader in the hyper-converged infrastructure segment.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERon has successfully developed and grown multiple companies in the broader technology industry. As a Partner at InterWest Partners, he invested in new technology start-up companies and served as a director to help chart their growth and increase their market value. He led multiple companies as their top executive through challenging turnaround periods to business success. His executive experience spans the range from small start-up companies to multi-billion dollar global corporations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERon received his M.S. from The University of Texas at Dallas in Management and his B.S. degree from the Georgia Institute of Technology in Industrial Engineering.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe look forward to seeing you at the seminar\/webinar!\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EJoin Zoom Meeting\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/99337158510?pwd=Y3pFRk1EZTJaV28zMWxDbmwra0syZz09\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022https:\/\/gatech.zoom.us\/j\/99337158510?pwd=Y3pFRk1EZTJaV28zMWxDbmwra0syZz09\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/99337158510?pwd=Y3pFRk1EZTJaV28zMWxDbmwra0syZz09\u003C\/a\u003E\u003Cbr \/\u003E\r\nMeeting ID: 993 3715 8510\u003Cbr \/\u003E\r\nPasscode: 780822\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Ron Nash is the Managing Director of Nash Technology Group and the author of \u201cThe Making of a Business Leader.\u201d"}],"uid":"27233","created_gmt":"2023-02-28 01:47:56","changed_gmt":"2023-03-02 20:15:32","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-09T15:30:00-05:00","event_time_end":"2023-03-09T16:00:00-05:00","event_time_end_last":"2023-03-09T16:00:00-05:00","gmt_time_start":"2023-03-09 20:30:00","gmt_time_end":"2023-03-09 21:00:00","gmt_time_end_last":"2023-03-09 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"666221":{"id":"666221","type":"image","title":"Ron Nash, Managing Director, Nash Technology Group","body":null,"created":"1677548617","gmt_created":"2023-02-28 01:43:37","changed":"1677548617","gmt_changed":"2023-02-28 01:43:37","alt":"","file":{"fid":"251919","name":"ron-nash.jpg","image_path":"\/sites\/default\/files\/images\/ron-nash.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/ron-nash.jpg","mime":"image\/jpeg","size":27543,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/ron-nash.jpg?itok=_leM0v1W"}}},"media_ids":["666221"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"666005":{"#nid":"666005","#data":{"type":"event","title":"ISyE Seminar - Alyssa Kody","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EWildfire Risk Mitigation and Data-Driven Methods for Electric Power Systems\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe electric power grid of the future faces many challenges, including rapidly increasing quantities of renewable generation and growing threats from extreme weather events, which necessitate the development of new computational tools. The first part of this talk will focus on one extreme weather event: elevated wildfire ignition risk. Wildfire risk mitigation is a critical consideration in regions like the western United States, where, historically, electric power systems have ignited some of the most destructive wildfires. To reduce the risk of igniting a wildfire, power system operators preemptively de-energize high-risk power lines during extreme wildfire conditions as part of \u0026ldquo;Public Safety Power Shutoff\u0026rdquo; (PSPS) events. However, PSPS events can also result in significant amounts of load shedding, leading to the need for new operation and planning decision-making algorithms for power systems experiencing high wildfire risk. The second part of the talk will focus on the specialized and targeted use of data-driven methods to increase the accuracy and computation speeds of power systems decision-making algorithms. The talk will conclude by outlining opportunities for the use of targeted data-driven methods to aid in wildfire risk mitigation algorithms, and for resilience decision-making for power systems in general.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAlyssa Kody is a Maria Goeppert Mayer Postdoctoral Fellow in the Energy Systems Division at Argonne National Laboratory in Lemont, Illinois. Her research focuses on developing control and optimization algorithms for power and energy systems. She was recently named a 2022 Rising Star in EECS. She received her Ph.D. in Electrical Engineering from the University of Michigan in Ann Arbor in 2019, where her thesis was on developing control systems for self-powered technologies. Her graduate work was supported by a National Science Foundation Graduate Research Fellowship and a Rackham Merit Fellowship.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe electric power grid of the future faces many challenges, including rapidly increasing quantities of renewable generation and growing threats from extreme weather events, which necessitate the development of new computational tools. The first part of this talk will focus on one extreme weather event: elevated wildfire ignition risk. Wildfire risk mitigation is a critical consideration in regions like the western United States, where, historically, electric power systems have ignited some of the most destructive wildfires. To reduce the risk of igniting a wildfire, power system operators preemptively de-energize high-risk power lines during extreme wildfire conditions as part of \u0026ldquo;Public Safety Power Shutoff\u0026rdquo; (PSPS) events. However, PSPS events can also result in significant amounts of load shedding, leading to the need for new operation and planning decision-making algorithms for power systems experiencing high wildfire risk. The second part of the talk will focus on the specialized and targeted use of data-driven methods to increase the accuracy and computation speeds of power systems decision-making algorithms. The talk will conclude by outlining opportunities for the use of targeted data-driven methods to aid in wildfire risk mitigation algorithms, and for resilience decision-making for power systems in general.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Wildfire Risk Mitigation and Data-Driven Methods for Electric Power Systems"}],"uid":"34977","created_gmt":"2023-02-21 13:20:10","changed_gmt":"2023-02-21 13:20:10","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-06T11:00:00-05:00","event_time_end":"2023-03-06T12:00:00-05:00","event_time_end_last":"2023-03-06T12:00:00-05:00","gmt_time_start":"2023-03-06 16:00:00","gmt_time_end":"2023-03-06 17:00:00","gmt_time_end_last":"2023-03-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665860":{"#nid":"665860","#data":{"type":"event","title":"ISyE Stats Seminar- Andrew Brown","body":[{"value":"\u003Cp\u003EBio:\u0026nbsp;Andrew Brown holds a BS in Applied Mathematics from Georgia Tech and earned his MS and PhD in Statistics from the University of Georgia under the guidance of Gauri Datta and Nicole Lazar. He subsequently took a faculty position in the School of Mathematical and Statistical Sciences at Clemson University, where he is now an Associate Professor. His primary research interests are in uncertainty quantification \/ computer experiments, Bayesian computation, and neuroimaging data analysis. This is in addition to some interdisciplinary work he has been involved with, including seroprevalence mapping in parasitology, group testing, engineering design, and risk assessment. He was a visiting research fellow at SAMSI for the program on Challenges in Computational Neuroscience, and has served as elected treasurer of the Industrial Statistics section of ISBA, secretary for the UQ interest group of the ASA, and President of the South Carolina chapter of the ASA. His work has been supported by the National Science Foundation and the Department of Education.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp;Alzheimer\u0026#39;s disease is a neurodegenerative condition that accelerates cognitive decline relative to normal aging. It is of critical scientific importance to gain a better understanding of early disease mechanisms in the brain to facilitate effective, targeted therapies. The volume of the hippocampus is often used in diagnosis and monitoring of the disease. Measuring this volume via neuroimaging is difficult since each hippocampus must either be manually identified or automatically delineated, a task referred to as segmentation. Automatic hippocampal segmentation often involves mapping a previously manually segmented image to a new brain image and propagating the labels to obtain an estimate of where each hippocampus is located in the new image. A more recent approach to this problem is to propagate labels from multiple manually segmented atlases and combine the results using a process known as label fusion. To date, most label fusion algorithms employ voting procedures with voting weights assigned directly or estimated via optimization. We propose using a fully Bayesian spatial regression model for label fusion that facilitates direct incorporation of covariate information while making accessible the entire posterior distribution. Our results suggest that incorporating tissue classification (e.g, gray matter) into the label fusion procedure can greatly improve segmentation when relatively homogeneous, healthy brains are used as atlases for diseased brains. The fully Bayesian approach also produces meaningful uncertainty measures about hippocampal volumes, information which can be leveraged to detect significant, scientifically meaningful differences between healthy and diseased populations, improving the potential for early detection and tracking of the disease.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBio:\u0026nbsp;Andrew Brown holds a BS in Applied Mathematics from Georgia Tech and earned his MS and PhD in Statistics from the University of Georgia under the guidance of Gauri Datta and Nicole Lazar. He subsequently took a faculty position in the School of Mathematical and Statistical Sciences at Clemson University, where he is now an Associate Professor. His primary research interests are in uncertainty quantification \/ computer experiments, Bayesian computation, and neuroimaging data analysis. This is in addition to some interdisciplinary work he has been involved with, including seroprevalence mapping in parasitology, group testing, engineering design, and risk assessment. He was a visiting research fellow at SAMSI for the program on Challenges in Computational Neuroscience, and has served as elected treasurer of the Industrial Statistics section of ISBA, secretary for the UQ interest group of the ASA, and President of the South Carolina chapter of the ASA. His work has been supported by the National Science Foundation and the Department of Education.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u0026nbsp;Alzheimer\u0026#39;s disease is a neurodegenerative condition that accelerates cognitive decline relative to normal aging. It is of critical scientific importance to gain a better understanding of early disease mechanisms in the brain to facilitate effective, targeted therapies. The volume of the hippocampus is often used in diagnosis and monitoring of the disease. Measuring this volume via neuroimaging is difficult since each hippocampus must either be manually identified or automatically delineated, a task referred to as segmentation. Automatic hippocampal segmentation often involves mapping a previously manually segmented image to a new brain image and propagating the labels to obtain an estimate of where each hippocampus is located in the new image. A more recent approach to this problem is to propagate labels from multiple manually segmented atlases and combine the results using a process known as label fusion. To date, most label fusion algorithms employ voting procedures with voting weights assigned directly or estimated via optimization. We propose using a fully Bayesian spatial regression model for label fusion that facilitates direct incorporation of covariate information while making accessible the entire posterior distribution. Our results suggest that incorporating tissue classification (e.g, gray matter) into the label fusion procedure can greatly improve segmentation when relatively homogeneous, healthy brains are used as atlases for diseased brains. The fully Bayesian approach also produces meaningful uncertainty measures about hippocampal volumes, information which can be leveraged to detect significant, scientifically meaningful differences between healthy and diseased populations, improving the potential for early detection and tracking of the disease.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging"}],"uid":"36358","created_gmt":"2023-02-16 15:33:22","changed_gmt":"2023-02-16 15:33:22","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-12T15:00:00-04:00","event_time_end":"2023-04-12T16:00:00-04:00","event_time_end_last":"2023-04-12T16:00:00-04:00","gmt_time_start":"2023-04-12 19:00:00","gmt_time_end":"2023-04-12 20:00:00","gmt_time_end_last":"2023-04-12 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665859":{"#nid":"665859","#data":{"type":"event","title":"ISyE Seminar - Dr. Brandon Pitts","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe era of increasingly intelligent technologies:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EInsights into human-automation interaction schemes across different environments, contexts, and tasks\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAutomation and artificial intelligence (AI) have begun to penetrate every area of human life including work, transportation, healthcare, and leisure environments. These advancements promise many benefits, such as improving public safety, providing convenience, extending human abilities, and enabling mobility. However, as automation and AI become increasingly integrated into our daily activities, there are several societal challenges and unanswered research questions that must be addressed related to the roles and responsibilities of humans within human-automation systems, the impact of automation on human behavior and performance, and the perception of (potential) users regarding the utility and usability of intelligent systems. This presentation will discuss a series of research projects aimed at developing and\/or evaluating various autonomous systems in different knowledge work environments. Studies involve: 1) predictions of situation awareness using physiological sensing in automated vehicles, 2) assessments of workload and performance with increasing levels of automation support for X-ray screening tasks, 3) evaluations of automatic speech-to-text tools for communicating weather information in aviation, and 4) evaluations of a fully autonomous, universally-designed vehicle prototype for people with travel-limiting disabilities. Findings from this research are expected to contribute to the broader discussion on how to thoughtfully design collaborative human-automation systems that successfully leverage the unique strengths and capabilities of each acting agent.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Brandon J. Pitts is an Assistant Professor in the School of Industrial Engineering at Purdue University, West Lafayette, IN. At Purdue, he is also Director of the \u003Cem\u003EN\u003C\/em\u003Eext-generation Human-systems and Cognitive Engineering (\u003Cem\u003EN\u003C\/em\u003EHanCE) Lab, Faculty Associate with the Center on Aging and the Life Course (CALC), and Co-Director of the Federal Aviation Administration (FAA) Center of Excellence for Technical Training and Human Performance (TTHP). His research interests include human factors, cognitive engineering, human-automation interaction, cyber-physical-human systems, interface design, gerontechnology, and inclusive design in complex transportation and work environments, such as driving and aviation. In 2022, Dr. Pitts\u0026rsquo; co-led team, EASI RIDER, was named the 1\u003Csup\u003Est\u003C\/sup\u003E place winner of the U.S. Department of Transportation (DOT) Inclusive Design Challenge (IDC) for their life-size autonomous vehicle solution that seeks to enable independent and seamless travel for individuals with disabilities. His research has been funded by sponsors such as the National Science Foundation (NSF), DOT, FAA, and Ford Motor Company. Dr. Pitts completed a B.S. in Industrial Engineering at Louisiana State University in 2010, and a M.S.E and Ph.D. in Industrial and Operations Engineering at the University of Michigan (UM), Ann Arbor, MI in 2013 and 2016, respectively. Prior to his faculty appointment, he was a Research Fellow in the UM Center for Healthcare Engineering and Patient Safety (CHEPS). He is also a registered Engineer Intern (E.I.T).\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAutomation and artificial intelligence (AI) have begun to penetrate every area of human life including work, transportation, healthcare, and leisure environments. These advancements promise many benefits, such as improving public safety, providing convenience, extending human abilities, and enabling mobility. However, as automation and AI become increasingly integrated into our daily activities, there are several societal challenges and unanswered research questions that must be addressed related to the roles and responsibilities of humans within human-automation systems, the impact of automation on human behavior and performance, and the perception of (potential) users regarding the utility and usability of intelligent systems. This presentation will discuss a series of research projects aimed at developing and\/or evaluating various autonomous systems in different knowledge work environments. Studies involve: 1) predictions of situation awareness using physiological sensing in automated vehicles, 2) assessments of workload and performance with increasing levels of automation support for X-ray screening tasks, 3) evaluations of automatic speech-to-text tools for communicating weather information in aviation, and 4) evaluations of a fully autonomous, universally-designed vehicle prototype for people with travel-limiting disabilities. Findings from this research are expected to contribute to the broader discussion on how to thoughtfully design collaborative human-automation systems that successfully leverage the unique strengths and capabilities of each acting agent.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The era of increasingly intelligent technologies:  Insights into human-automation interaction schemes across different environments, contexts, and tasks "}],"uid":"36374","created_gmt":"2023-02-16 15:06:54","changed_gmt":"2023-02-16 15:06:54","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-24T12:00:00-05:00","event_time_end":"2023-02-24T13:00:00-05:00","event_time_end_last":"2023-02-24T13:00:00-05:00","gmt_time_start":"2023-02-24 17:00:00","gmt_time_end":"2023-02-24 18:00:00","gmt_time_end_last":"2023-02-24 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665584":{"#nid":"665584","#data":{"type":"event","title":"Online Information Session: Supply Chain Analytics Professional Certificate","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbout Our Session\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EJoin us online February 16 from 1-2pm ET to learn about our 4-course series offered through Georgia Tech Professional Education. The information session will discuss certificate requirements, course curriculum, key components, and learning outcomes for the Supply Chain Analytics series.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf\u0026nbsp;you cannot join us live, still register to receive the slide deck presentation via email after the event.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ESession Host\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDarrell Kent\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Cem\u003EInstructor @GT Supply Chain Analytics\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDarrell Kent is the professional education manager for ORTEC and the lead instructor for the Georgia Tech Supply Chain \u0026amp; Logistics Institute\u0026rsquo;s Supply Chain Analytics Professional Certificate program. He brings more than 15 years of senior experience helping companies deploy machine learning, mathematical optimization, and other advanced analytics solutions as part of their wider digital transformation efforts, including in relation to pricing management, customer segmentation, demand forecasting, resource planning, network design, visual detection systems for automated yard management, predictive maintenance, machine learning-based booking control, and dispatch automation and optimization. His instructional style focuses on helping learners develop practical skills that can be immediately used to address real supply chain challenges in their organizations.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EJoin us online February 16 from 1-2pm ET to learn about our 4-course series offered through Georgia Tech Professional Education. The information session will discuss certificate requirements, course curriculum, key components, and learning outcomes for the Supply Chain Analytics series.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join us to learn about our 4-course series offered through Georgia Tech Professional Education."}],"uid":"27233","created_gmt":"2023-02-07 22:52:02","changed_gmt":"2023-02-09 13:34:03","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-16T13:00:00-05:00","event_time_end":"2023-02-16T14:00:00-05:00","event_time_end_last":"2023-02-16T14:00:00-05:00","gmt_time_start":"2023-02-16 18:00:00","gmt_time_end":"2023-02-16 19:00:00","gmt_time_end_last":"2023-02-16 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"665583":{"id":"665583","type":"image","title":"Online Information Session: Supply Chain Analytics Professional Certificate","body":null,"created":"1675810018","gmt_created":"2023-02-07 22:46:58","changed":"1675810018","gmt_changed":"2023-02-07 22:46:58","alt":"","file":{"fid":"251712","name":"GTSCL-SCA_Webinar_16by9.jpg","image_path":"\/sites\/default\/files\/images\/GTSCL-SCA_Webinar_16by9.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/GTSCL-SCA_Webinar_16by9.jpg","mime":"image\/jpeg","size":259049,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/GTSCL-SCA_Webinar_16by9.jpg?itok=1tQpHjfw"}}},"media_ids":["665583"],"related_links":[{"url":"https:\/\/gatech.zoom.us\/webinar\/register\/7416751809445\/WN_NNlb0ckrT1-2ba4iPmoOCQ","title":"Register Online for the SCA Information Session"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"2153","name":"Distance Learning and Professional Education"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665468":{"#nid":"665468","#data":{"type":"event","title":"ISyE Seminar - Linda Boyle","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA framework for modeling human-vehicle interactions with increasingly autonomous systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EModeling human-vehicle interactions requires an understanding of the human behavior. The model development needs to capture human\u0026rsquo;s interaction with other people, the environment, and their surroundings.\u0026nbsp; A challenge in model development is the ability to accurately predict human behavior, particularly in complex environments that include other human road users, such as pedestrians and bicyclists. In this presentation, a framework is provided to better quantify and predict interactive human-vehicle decision-making, which can then be used to better inform the algorithms for advanced driver assistance systems (ADAS).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELinda Ng Boyle is Professor in Industrial \u0026amp; Systems Engineering at the University of Washington, Seattle. She has a joint appointment in Civil \u0026amp; Environmental Engineering. She has degrees from the University of Buffalo (BS) and University of Washington (MS, PhD).\u0026nbsp; She is a member of the National Academies Board of Human System Integration and co-author of the textbook, \u0026ldquo;Designing for People: An Introduction to Human Factors Engineering\u0026rdquo;.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EModeling human-vehicle interactions requires an understanding of the human behavior. The model development needs to capture human\u0026rsquo;s interaction with other people, the environment, and their surroundings.\u0026nbsp; A challenge in model development is the ability to accurately predict human behavior, particularly in complex environments that include other human road users, such as pedestrians and bicyclists. In this presentation, a framework is provided to better quantify and predict interactive human-vehicle decision-making, which can then be used to better inform the algorithms for advanced driver assistance systems (ADAS).\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" A framework for modeling human-vehicle interactions with increasingly autonomous systems"}],"uid":"36374","created_gmt":"2023-02-06 12:59:57","changed_gmt":"2023-02-06 12:59:57","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-17T11:30:00-05:00","event_time_end":"2023-02-17T12:30:00-05:00","event_time_end_last":"2023-02-17T12:30:00-05:00","gmt_time_start":"2023-02-17 16:30:00","gmt_time_end":"2023-02-17 17:30:00","gmt_time_end_last":"2023-02-17 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665301":{"#nid":"665301","#data":{"type":"event","title":"ISyE Seminar - Zhimei Ren","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EStable Variable Selection with Knockoffs\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EA common problem in many modern statistical applications is to find a set of important variables\u0026mdash;from a pool of many candidates\u0026mdash;that explain the response of interest. For this task,\u0026nbsp;model-X knockoffs offers a general framework that can leverage any feature importance measure to produce a variable selection algorithm: it discovers true effects while rigorously controlling the number or fraction of false positives, paving the way for reproducible scientific discoveries. The model-X knockoffs, however, is a randomized procedure that relies on the one-time construction of synthetic (random) variables. Different runs of model-X knockoffs on the same dataset often result in different sets of selected variables, which is not desirable for the reproducibility of the reported results.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will introduce derandomization schemes that aggregate the selection results across multiple runs of the knockoffs algorithm to yield stable selection. In the first part, I will present a derandomization scheme that controls the number of false positives, i.e., the per family error rate (PFER) and the k family-wise error rate (k-FWER). In the second part, I will talk about an alternative derandomization scheme with provable false discovery rate (FDR) control. Equipped with these derandomization steps, the knockoffs framework provides a powerful tool for making reproducible scientific discoveries. The proposed methods are evaluated on both simulated and real data, demonstrating comparable power and dramatically lower selection variability when compared with the original model-X knockoffs.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EZhimei Ren is a postdoctoral researcher in the Statistics Department at the University of Chicago, advised by Professor Rina Foygel Barber. Before joining the University of Chicago, she obtained her Ph.D. in Statistics from Stanford University, under the supervision of Professor Emmanuel Cand\u0026egrave;s. Her research interests lie broadly in multiple hypothesis testing, distribution-free inference, causal inference, survival analysis and data-driven decision-making.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EA common problem in many modern statistical applications is to find a set of important variables\u0026mdash;from a pool of many candidates\u0026mdash;that explain the response of interest. For this task,\u0026nbsp;model-X knockoffs offers a general framework that can leverage any feature importance measure to produce a variable selection algorithm: it discovers true effects while rigorously controlling the number or fraction of false positives, paving the way for reproducible scientific discoveries. The model-X knockoffs, however, is a randomized procedure that relies on the one-time construction of synthetic (random) variables. Different runs of model-X knockoffs on the same dataset often result in different sets of selected variables, which is not desirable for the reproducibility of the reported results.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Stable Variable Selection with Knockoffs "}],"uid":"34977","created_gmt":"2023-01-31 20:43:52","changed_gmt":"2023-01-31 20:43:52","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-13T11:00:00-05:00","event_time_end":"2023-02-13T12:00:00-05:00","event_time_end_last":"2023-02-13T12:00:00-05:00","gmt_time_start":"2023-02-13 16:00:00","gmt_time_end":"2023-02-13 17:00:00","gmt_time_end_last":"2023-02-13 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665277":{"#nid":"665277","#data":{"type":"event","title":"ISyE Seminar - Jovan Julien","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EBridging an Information Divide: Clinically Relevant Models of Alcohol Consumption and Liver Disease to Inform Dynamic and Interpretable Community Alcohol Policies\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAlcohol-attributable liver disease (ALD) rates have been on the rise globally and in the United States over the past two decades and harmful alcohol use contributes to more than 200 disease and injury conditions. Each disease event carries a significant cost for the individual, their community, and society at large. Due to the unobserved nature of early disease states and limited data on disease prevalence in the general population, most models of ALD and alcohol-use disorders focus on the treatment of late-stage disease including liver cirrhosis and liver cancer without the ability to consider harm reduction strategies available at the population and individual level.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis talk will focus on a clinically relevant model of ALD that incorporates the regenerative abilities of the liver, with the objective of projecting the impact of current drinking patterns on disease morbidity and mortality in the US population and the impact of societal and individual level interventions on projected disease burden and healthcare costs. The first portion of the talk will focus on building an alcohol consumption and liver disease model incorporating current consumption data that can be leveraged for decision analysis by stake holders at the individual, clinical, and population level. The second part will consider the potential of harm reduction strategies and alcohol policy to positively impact the future burden of disease in the United States. A data collection scheme will be proposed to parameterize a personalized disease progression and decision-making model.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EJovan Julien is currently on a postdoctoral fellowship at Massachusetts General Hospital\u0026#39;s Institute for Technology Assessment and Harvard Medical School, where they are currently working on modeling the impact of breathing modulation and other meditation and mindfulness techniques on disease mitigation strategies. Their broader research interests are in predictive health models that can inform wellness interventions and policy at the individual, interpersonal, and systemic levels to limit and eventually reverse the growth rate in per capita spending on healthcare while improving long-term outcomes. Jovan received their B.Sc in Biomedical Engineering from Brown University, and a master\u0026rsquo;s in health systems engineering and PhD degree in Operations Research from Georgia Institute of Technology\u0026#39;s H. Milton Stewart School of Industrial \u0026amp; Systems Engineering. Their studies were supported with a Health Policy Research Fellowship sponsored by the Robert Wood Johnson Foundation.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAlcohol-attributable liver disease (ALD) rates have been on the rise globally and in the United States over the past two decades and harmful alcohol use contributes to more than 200 disease and injury conditions. Each disease event carries a significant cost for the individual, their community, and society at large. Due to the unobserved nature of early disease states and limited data on disease prevalence in the general population, most models of ALD and alcohol-use disorders focus on the treatment of late-stage disease including liver cirrhosis and liver cancer without the ability to consider harm reduction strategies available at the population and individual level.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis talk will focus on a clinically relevant model of ALD that incorporates the regenerative abilities of the liver, with the objective of projecting the impact of current drinking patterns on disease morbidity and mortality in the US population and the impact of societal and individual level interventions on projected disease burden and healthcare costs. The first portion of the talk will focus on building an alcohol consumption and liver disease model incorporating current consumption data that can be leveraged for decision analysis by stake holders at the individual, clinical, and population level. The second part will consider the potential of harm reduction strategies and alcohol policy to positively impact the future burden of disease in the United States. A data collection scheme will be proposed to parameterize a personalized disease progression and decision-making model.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Bridging an Information Divide: Clinically Relevant Models of Alcohol Consumption and Liver Disease to Inform Dynamic and Interpretable Community Alcohol Policies"}],"uid":"34977","created_gmt":"2023-01-31 12:43:14","changed_gmt":"2023-01-31 12:43:39","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-15T11:00:00-05:00","event_time_end":"2023-02-15T12:00:00-05:00","event_time_end_last":"2023-02-15T12:00:00-05:00","gmt_time_start":"2023-02-15 16:00:00","gmt_time_end":"2023-02-15 17:00:00","gmt_time_end_last":"2023-02-15 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665230":{"#nid":"665230","#data":{"type":"event","title":"ISyE Seminar - Yale Herer","body":[{"value":"\u003Cp\u003ETITLE\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAn asymptotic perspective on risk pooling: Limitations and relationship to transshipments.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk we provide a novel perspective on risk pooling approaches by characterizing and comparing their asymptotic performance, highlighting the conditions under which one approach dominates the other. More specifically, we determine the inventory policy and the expected total costs of systems under physical and information pooling as the number of locations grows. We show that physical pooling dominates information pooling in settings with no additional per-item and per-location costs for operating the centralized system. In the presence of such costs, however, information pooling becomes a viable alternative to physical pooling. Through asymptotic analysis, we also address the grouping problem, the division of a given set of non-identical locations into an ordered collection of mutually exclusive and collectively exhaustive subsets of predetermined sizes and demonstrate that homogeneous groups, comprising locations with similar demand volatility, achieve a lower expected total cost. Finally, the convergence of the expected total costs and the base stock levels under the two pooling approaches is demonstrated through a simple numerical illustration. Our analysis supports the assertion that it is important to consider not only the individual characteristics of each location in isolation, but also the interactions among them, when designing pooling systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBIO\u003C\/p\u003E\r\n\r\n\u003Cp\u003EYale T. Herer, BS (1986), MS (1990), PhD (1990), Cornell University, Department of Operations Research and Industrial Engineering. Yale is an associate professor in the Faculty of Industrial Engineering and Management at the Technion\u0026mdash;Israel Institute of Technology where, since 2018, he serves as Vice Dean of Programs of Study. Yale has worked for several industrial concerns, both as a consultant and as an advisor to project groups. He also serves as an associate editor for Naval Research Logistics and has served on the editorial staff of IIE Transactions and Operations Research Letters. Yale has successfully planned and executed four conferences, including the 2010 annual conference for the Manufacturing and Service Operations Management Society (MSOM). Yale\u0026rsquo;s research interest can be broadly defined as covering Production Planning and Control. More recently Yale has focused his research on the area of Supply Chain Management, especially when integrated with transshipments or other responsive operational activities. Yale has won various prizes including a 1996 IIE Transactions Best Paper Award, the 2002 Mitchner Award in Quality Sciences and Quality Management, a 2008 IBM Faculty Award, and INFORM\u0026rsquo;s 2013 Daniel H. Wagner Prize for Excellence in Operations Research Practice.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn this talk we provide a novel perspective on risk pooling approaches by characterizing and comparing their asymptotic performance, highlighting the conditions under which one approach dominates the other. More specifically, we determine the inventory policy and the expected total costs of systems under physical and information pooling as the number of locations grows. We show that physical pooling dominates information pooling in settings with no additional per-item and per-location costs for operating the centralized system. In the presence of such costs, however, information pooling becomes a viable alternative to physical pooling. Through asymptotic analysis, we also address the grouping problem, the division of a given set of non-identical locations into an ordered collection of mutually exclusive and collectively exhaustive subsets of predetermined sizes and demonstrate that homogeneous groups, comprising locations with similar demand volatility, achieve a lower expected total cost. Finally, the convergence of the expected total costs and the base stock levels under the two pooling approaches is demonstrated through a simple numerical illustration. Our analysis supports the assertion that it is important to consider not only the individual characteristics of each location in isolation, but also the interactions among them, when designing pooling systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"An asymptotic perspective on risk pooling: Limitations and relationship to transshipments"}],"uid":"36374","created_gmt":"2023-01-30 13:46:45","changed_gmt":"2023-01-30 13:46:45","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-01T11:30:00-05:00","event_time_end":"2023-02-01T12:30:00-05:00","event_time_end_last":"2023-02-01T12:30:00-05:00","gmt_time_start":"2023-02-01 16:30:00","gmt_time_end":"2023-02-01 17:30:00","gmt_time_end_last":"2023-02-01 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"665219":{"#nid":"665219","#data":{"type":"event","title":"SCL IRC Seminar: Towards a Circular Carbon Economy: Plants do it \u2013 why don\u0027t we?","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOur current energy systems are undergoing a significant shift from fossil carbon burning to the utilization of current sunlight.\u0026nbsp; There is the misconception that this shift also implies that we have to stop using carbon-based fuels as energy carriers.\u0026nbsp; What mix of energy carriers will be optimal for our future energy systems, and possibly more importantly what mix can we use during the next 30-40 years as we transition from fossil to renewable is still a very open question.\u0026nbsp; In this talk I will describe how we might couple renewable energy to carbon-based fuels through systems of direct air capture of CO2 and subsequent conversion.\u0026nbsp; Even within this space there is significant potential diversity of molecules that can be used, for example methanol is currently gaining favor in the shipping industry, but it could be that traditional hydrocarbons are a better fit due to the existing infrastructure.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKER\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/matthew-realff\u0022\u003E\u003Cstrong\u003EMatthew Realff\u003C\/strong\u003E\u003C\/a\u003E,\u0026nbsp;Professor and David Wang Sr Fellow, School of Chemical and Biomolecular Engineering\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person, the cost to attend is $5 per session which includes a boxed lunch*\u003C\/strong\u003E. Virtual attendance is always free.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2023-01-27 22:49:36","changed_gmt":"2023-01-27 22:49:45","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-16T13:00:00-04:00","event_time_end":"2023-03-16T14:30:00-04:00","event_time_end_last":"2023-03-16T14:30:00-04:00","gmt_time_start":"2023-03-16 17:00:00","gmt_time_end":"2023-03-16 18:30:00","gmt_time_end_last":"2023-03-16 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"665218":{"id":"665218","type":"image","title":"SCL IRC Seminar: Towards a Circular Carbon Economy: Plants do it \u2013 why don\u0027t we?","body":null,"created":"1674859744","gmt_created":"2023-01-27 22:49:04","changed":"1674859744","gmt_changed":"2023-01-27 22:49:04","alt":"","file":{"fid":"251597","name":"GTSCL-SCLIRC_202303.jpg","image_path":"\/sites\/default\/files\/images\/GTSCL-SCLIRC_202303.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/GTSCL-SCLIRC_202303.jpg","mime":"image\/jpeg","size":164942,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/GTSCL-SCLIRC_202303.jpg?itok=HlYWSuNN"}}},"media_ids":["665218"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"665066":{"#nid":"665066","#data":{"type":"event","title":"SCL IRC Seminar: Re-imagining the Future of the Construction Industry","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we will share a vision for the future of the built-environment, which is smart, inter-connected, and both user-and environmental-conscious. We will also discuss the challenges that need to be overcome to realize this vision and the innovative trends and emerging technologies that will facilitate the transformation of the construction industry.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKER\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/pardis-pishdad-bozorgi\u0022\u003EPardis Pishdad-Bozorgi\u003C\/a\u003E\u003C\/strong\u003E,\u0026nbsp;Associate Professor | Graduate Program Director | Director, Smart Built EcoSystem (Smart Bees) Laboratory\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person, the cost to attend is $5 per session which includes a boxed lunch*\u003C\/strong\u003E. Virtual attendance is always free.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2023-01-24 20:16:40","changed_gmt":"2023-01-24 20:16:47","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-23T12:00:00-05:00","event_time_end":"2023-02-23T13:30:00-05:00","event_time_end_last":"2023-02-23T13:30:00-05:00","gmt_time_start":"2023-02-23 17:00:00","gmt_time_end":"2023-02-23 18:30:00","gmt_time_end_last":"2023-02-23 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"665065":{"id":"665065","type":"image","title":"SCL IRC Seminar: Re-imagining the Future of the Construction Industry with Dr. Pardis Pishdad-Bozorgi","body":null,"created":"1674591372","gmt_created":"2023-01-24 20:16:12","changed":"1674841786","gmt_changed":"2023-01-27 17:49:46","alt":"","file":{"fid":"251590","name":"banner-SCLIRC-20230223_300x100.jpg","image_path":"\/sites\/default\/files\/images\/banner-SCLIRC-20230223_300x100.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/banner-SCLIRC-20230223_300x100.jpg","mime":"image\/jpeg","size":172725,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/banner-SCLIRC-20230223_300x100.jpg?itok=1EL1I30W"}}},"media_ids":["665065"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"664926":{"#nid":"664926","#data":{"type":"event","title":"ISyE Seminar - Paul G\u00f6lz","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EFair, Representative, and Transparent Algorithms for Citizens\u0026rsquo; Assemblies\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EGlobally, an alternative approach to democracy is gaining momentum: citizens\u0026rsquo; assemblies, in which randomly selected constituents discuss policy questions and propose solutions. Domain experts have two conflicting requirements on the selection of these assemblies: (1) assemblies should reflect the demographics of the population, and (2) all constituents should have equal chances of being selected. In this talk, I will describe work on designing and analyzing randomized selection algorithms that favorably trade off these objectives. I will share experiences with deploying these algorithms on our online platform Panelot and discuss what we learned from practitioners in the process of adoption. Finally, I will explore how these lessons sparked work on other aspects of citizens\u0026rsquo; assemblies, such as making the random selection process transparent and managing the discussions within the assembly.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EPaul G\u0026ouml;lz is a postdoctoral researcher at the School of Engineering and Applied Sciences at Harvard. He received his Ph.D. in computer science from Carnegie Mellon University under the supervision of Ariel Procaccia. Paul studies democratic decision-making and the fair allocation of resources, using tools from algorithms, optimization, and artificial intelligence. Algorithms developed in his work are now deployed to select citizens\u0026rsquo; assemblies around the world and to allocate refugees for a major US resettlement agency.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EGlobally, an alternative approach to democracy is gaining momentum: citizens\u0026rsquo; assemblies, in which randomly selected constituents discuss policy questions and propose solutions. Domain experts have two conflicting requirements on the selection of these assemblies: (1) assemblies should reflect the demographics of the population, and (2) all constituents should have equal chances of being selected. In this talk, I will describe work on designing and analyzing randomized selection algorithms that favorably trade off these objectives. I will share experiences with deploying these algorithms on our online platform Panelot and discuss what we learned from practitioners in the process of adoption. Finally, I will explore how these lessons sparked work on other aspects of citizens\u0026rsquo; assemblies, such as making the random selection process transparent and managing the discussions within the assembly.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Fair, Representative, and Transparent Algorithms for Citizens\u2019 Assemblies"}],"uid":"34977","created_gmt":"2023-01-20 17:37:39","changed_gmt":"2023-01-20 17:37:39","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-07T11:00:00-05:00","event_time_end":"2023-02-07T12:00:00-05:00","event_time_end_last":"2023-02-07T12:00:00-05:00","gmt_time_start":"2023-02-07 16:00:00","gmt_time_end":"2023-02-07 17:00:00","gmt_time_end_last":"2023-02-07 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664911":{"#nid":"664911","#data":{"type":"event","title":"ISyE Seminar -  Karen Smilowitz","body":[{"value":"\u003Cp\u003ETITLE\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ERevisiting School District Design: A Stream-based Approach\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EKaren Smilowitz, James N. and Margie M. Krebs Professor in Industrial Engineering and Management Sciences, McCormick School of Engineering; Professor of Operations, Kellogg School of Management, Northwestern University\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOperations research methods have been used to improve operations in public school systems for over fifty years. \u0026nbsp;The talk will explore connections between evolving issues in public education and advances in optimization, computing and geographic information systems, beginning with early work motivated by Supreme Court decisions to desegregate schools.\u0026nbsp; The talk will focus specifically on the school district design problem. We introduce a new compact formulation that incorporates multiple assignment decisions simultaneously by assigning students in small geographic units to sets of schools (e.g., elementary, middle, high school) and programs (e.g., bilingual education) with single composite variables, referred to as \u0026ldquo;streams\u0026rdquo;. This compact formulation incorporates advances in district design modeling from the literature and extends the decision-making capabilities of such models. We tie these extensions to education literature and policies at specific school districts. This new formulation is computationally efficient, easily reconfigurable for evolving problem specifications, and facilitates improved communication with stakeholders.\u0026nbsp; To illustrate these capabilities, we present a case study from a partnership focused on district redesign to address historic inequities in access to education.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBIO\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Karen Smilowitz is the James N. and Margie M. Krebs Professor in Industrial Engineering and Management Science at Northwestern University, with a joint appointment in the Operations group at the Kellogg School of Management.\u0026nbsp; Dr. Smilowitz is an expert in modeling and solution approaches for logistics and transportation systems in both commercial and nonprofit applications.\u0026nbsp; She has been instrumental in promoting the use of operations research within the humanitarian and nonpro\ufb01t sectors through the Woodrow Wilson International Center for Scholars, the American Association for the Advancement of Science, and the National Academy of Engineering, as well as various media outlets.\u0026nbsp; Dr. Smilowitz is the Editor-in-Chief of \u003Cem\u003ETransportation Science\u003C\/em\u003E and a Fellow of the INFORMS society.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EOperations research methods have been used to improve operations in public school systems for over fifty years. \u0026nbsp;The talk will explore connections between evolving issues in public education and advances in optimization, computing and geographic information systems, beginning with early work motivated by Supreme Court decisions to desegregate schools.\u0026nbsp; The talk will focus specifically on the school district design problem. We introduce a new compact formulation that incorporates multiple assignment decisions simultaneously by assigning students in small geographic units to sets of schools (e.g., elementary, middle, high school) and programs (e.g., bilingual education) with single composite variables, referred to as \u0026ldquo;streams\u0026rdquo;. This compact formulation incorporates advances in district design modeling from the literature and extends the decision-making capabilities of such models. We tie these extensions to education literature and policies at specific school districts. This new formulation is computationally efficient, easily reconfigurable for evolving problem specifications, and facilitates improved communication with stakeholders.\u0026nbsp; To illustrate these capabilities, we present a case study from a partnership focused on district redesign to address historic inequities in access to education.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Revisiting School District Design: A Stream-based Approach"}],"uid":"36374","created_gmt":"2023-01-19 20:32:52","changed_gmt":"2023-01-19 20:32:52","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-27T11:30:00-05:00","event_time_end":"2023-01-27T12:30:00-05:00","event_time_end_last":"2023-01-27T12:30:00-05:00","gmt_time_start":"2023-01-27 16:30:00","gmt_time_end":"2023-01-27 17:30:00","gmt_time_end_last":"2023-01-27 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664902":{"#nid":"664902","#data":{"type":"event","title":"ISyE Seminar - Maryam Zahabi ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECognitive Workload Assessment of Upper-Limb Prosthetic Devices\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ELimb amputation can cause severe functional disability for the performance of activities of daily living (ADLs). Amputees use prosthetic devices on a regular basis to perform ADLs. Prosthetic devices require substantial amount of cognitive resources, which can lead to device rejection. However, prior research was mainly focused on measuring physical performance of using prosthetic devices. Assessing cognitive workload of prostheses is critical to ensure device usability. This study investigated models for classifying cognitive workload in electromyography (EMG)-based prosthetic devices with various types of input features, metrics, and tasks. The proposed algorithms can help manufacturers and clinicians predict cognitive workload of future EMG-based prosthetic devices in early design phases.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMaryam Zahabi is an assistant professor in the Wm Michael Barnes \u0026rsquo;64 department of industrial and systems engineering at Texas A\u0026amp;M University. Her research focuses on human performance modeling with applications in assistive technologies and surface transportation. She received her PhD in industrial and systems engineering from North Carolina State University in 2017. Dr. Zahabi\u0026rsquo;s research has received support from agencies including the NSF, DARPA, and U.S. DOT. She is also the recipient of the 2021 NSF CAREER Award. Dr. Zahabi has published over 35 journal papers in the human systems engineering area and serves an associate editor for \u003Cem\u003EIEEE Transactions on Human-Machine Systems\u003C\/em\u003E journal.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ELimb amputation can cause severe functional disability for the performance of activities of daily living (ADLs). Amputees use prosthetic devices on a regular basis to perform ADLs. Prosthetic devices require substantial amount of cognitive resources, which can lead to device rejection. However, prior research was mainly focused on measuring physical performance of using prosthetic devices. Assessing cognitive workload of prostheses is critical to ensure device usability. This study investigated models for classifying cognitive workload in electromyography (EMG)-based prosthetic devices with various types of input features, metrics, and tasks. The proposed algorithms can help manufacturers and clinicians predict cognitive workload of future EMG-based prosthetic devices in early design phases.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Cognitive Workload Assessment of Upper-Limb Prosthetic Devices"}],"uid":"34977","created_gmt":"2023-01-19 17:13:50","changed_gmt":"2023-01-19 17:13:50","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-09T11:00:00-05:00","event_time_end":"2023-02-09T12:00:00-05:00","event_time_end_last":"2023-02-09T12:00:00-05:00","gmt_time_start":"2023-02-09 16:00:00","gmt_time_end":"2023-02-09 17:00:00","gmt_time_end_last":"2023-02-09 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664589":{"#nid":"664589","#data":{"type":"event","title":"ISyE Seminar - Constance Crozier","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EDecarbonization of the power sector with human-in-the-loop\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe variability of renewable generation is a barrier to the decarbonization of the power sector. Existing methods for coping with uncertainty in power systems focus on the supply side (e.g using energy storage, power imports, or supplementing with controllable fossil generation). However, many of the emerging technologies which consumer power have inherent flexibility, meaning control of the demand-side will be possible. This talk will cover the integration of residential demand flexibility into power systems, with the objective of offsetting variability from renewable generation. The focus will largely be on domestic electric vehicle charging. The first part of the talk will focus on building decision models to quantify the aggregated flexibility of charging. A data-driven approach will be introduced that is based on clustering of conventional vehicle usage data. The second part will focus on control strategies for large numbers of distributed flexible resources. An optimization scheme will be introduced which preserves consumer privacy and equity, while protecting local network components.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EConstance received both M.Eng and PhD degrees from the University of Oxford. Her PhD focused on understanding the impact that electric vehicle charging will have on power systems. She is currently a postdoc at CU Boulder, where she has been working on the ARPA-E Grid Optimization Competition. Her broader research interests are in realizing the potential of demand flexibility in power systems.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe variability of renewable generation is a barrier to the decarbonization of the power sector. Existing methods for coping with uncertainty in power systems focus on the supply side (e.g using energy storage, power imports, or supplementing with controllable fossil generation). However, many of the emerging technologies which consumer power have inherent flexibility, meaning control of the demand-side will be possible. This talk will cover the integration of residential demand flexibility into power systems, with the objective of offsetting variability from renewable generation. First, the classical optimal power flow problem will be introduced and the challenges of scaling it to include controllable generation will be discussed. Then two methods will be introduced which both aim to coordinate flexible resources in a scalable manner that preserves consumer privacy. The first method uses formal optimization to determine price signals, while the second uses multi-agent reinforcement learning.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Decarbonization of the power sector with human-in-the-loop"}],"uid":"34977","created_gmt":"2023-01-10 14:06:22","changed_gmt":"2023-01-10 15:51:17","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-02T11:00:00-05:00","event_time_end":"2023-02-02T12:00:00-05:00","event_time_end_last":"2023-02-02T12:00:00-05:00","gmt_time_start":"2023-02-02 16:00:00","gmt_time_end":"2023-02-02 17:00:00","gmt_time_end_last":"2023-02-02 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"664033":{"#nid":"664033","#data":{"type":"event","title":"ISyE Seminar - Tianyi Peng","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperimentation Platforms and Learning Treatment Effects in Panels\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperiments in brick-and-mortar retail are contaminated for myriad reasons. Pragmatic inference in such settings is more akin to learning from observational data, as opposed to the typical setup one might consider for a carefully designed randomized experiment. So motivated, we consider the problem of causal inference in panels with general intervention patterns that may depend on the historical data. We provide a novel, near-complete solution to this problem that allows for rate-optimal recovery of treatment effects. Our work generalizes the outcome model of the difference-in-difference paradigm and expands the applicability of the synthetic-control paradigm. In doing so, we provide a novel de-biasing analysis that addresses the low-rank matrix regression with non-random intervention patterns and noise; a non-trivial feature of independent interest.\u0026nbsp; Our algorithms form the core of a new testing platform we co-developed with a USD 100B drink company, which increased revenue by millions of dollars monthly in Mexico alone.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ETianyi Peng is a Ph.D. student at MIT. He is advised by Vivek Farias, and also mentored by Andrew Li.\u0026nbsp;He is broadly interested in developing algorithms for learning and inference in large-scale dynamic decision-making systems. In particular, he is interested in\u0026nbsp;developing next-generation experimentation platforms, which provide scalable, low-cost solutions for discovering beneficial strategies\/policies. In translating these ideas, he is engaged with Anheuser-Busch InBev, Takeda Pharmaceuticals, TikTok, and Liberty Mutual. His work has been recognized as a\u0026nbsp;finalist for the MSOM Student Paper\u0026nbsp;Competition (2022), and\u0026nbsp;has won\u0026nbsp;the INFORMS Daniel H. Wagner Prize (2022), Applied Probability Society Best Student Paper Prize (2022), Jeff McGill Student Paper Award (2022)\u0026nbsp;and the best thesis award at Tsinghua where he\u0026nbsp;graduated with the 2017 Yao Class.\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperiments in brick-and-mortar retail are contaminated for myriad reasons. Pragmatic inference in such settings is more akin to learning from observational data, as opposed to the typical setup one might consider for a carefully designed randomized experiment. So motivated, we consider the problem of causal inference in panels with general intervention patterns that may depend on the historical data. We provide a novel, near-complete solution to this problem that allows for rate-optimal recovery of treatment effects. Our work generalizes the outcome model of the difference-in-difference paradigm and expands the applicability of the synthetic-control paradigm. In doing so, we provide a novel de-biasing analysis that addresses the low-rank matrix regression with non-random intervention patterns and noise; a non-trivial feature of independent interest.\u0026nbsp; Our algorithms form the core of a new testing platform we co-developed with a USD 100B drink company, which increased revenue by millions of dollars monthly in Mexico alone.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Experimentation Platforms and Learning Treatment Effects in Panels"}],"uid":"34977","created_gmt":"2022-12-21 18:20:49","changed_gmt":"2022-12-22 14:35:24","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-12T11:00:00-05:00","event_time_end":"2023-01-12T12:00:00-05:00","event_time_end_last":"2023-01-12T12:00:00-05:00","gmt_time_start":"2023-01-12 16:00:00","gmt_time_end":"2023-01-12 17:00:00","gmt_time_end_last":"2023-01-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663174":{"#nid":"663174","#data":{"type":"event","title":"ISyE Seminar - Huseyin Topaloglu","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint Inventory Allocation and Assortment Personalization with Performance Guarantees\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we give approximation algorithms for a joint inventory allocation and assortment personalization problem motivated by\u0026nbsp;an online retail setting. In our problem, we have a limited amount of storage capacity that needs to be allocated among multiple products to\u0026nbsp;serve customers that arrive over a selling horizon. At the beginning of the selling horizon, we decide how many units of each product to\u0026nbsp;stock. Over the selling horizon, customers arrive at the platform one by one to make a purchase. Based on the remaining inventories of the\u0026nbsp;products and the information available on the arriving customer, we offer a personalized assortment of products to each customer. The\u0026nbsp;customer either makes a choice within the offered assortment or leaves without a purchase. Our goal is to decide how many units of each\u0026nbsp;product to stock at the beginning of the selling horizon and to find a policy to figure out which personalized assortment to offer to each\u0026nbsp;arriving customer to maximize the total expected revenue over the selling horizon. Our problem is motivated by same-day-delivery\u0026nbsp;applications in online retail, where the retailer needs to allocate the limited storage capacity in an urban warehouse among different\u0026nbsp;variants in a product category, while having the capability of offering personalized assortments to customers to make better use of\u0026nbsp;remaining inventories. Allocating the storage capacity among the products requires tackling a combinatorial problem, whereas finding an\u0026nbsp;assortment personalization policy requires approximating a dynamic program with a high-dimensional state variable. When the choices of\u0026nbsp;the customers are governed by the multinomial logit model, we give a constant-factor approximation algorithm for this joint inventory\u0026nbsp;allocation and assortment personalization problem. Under a general choice model, we give an algorithm that is asymptotically optimal as\u0026nbsp;the storage capacity gets large. In the latter result, the demand can be scaled in an arbitrary fashion along with the storage capacity. This\u0026nbsp;is joint work with Yicheng Bai, Omar El Housni and Paat Rusmevichientong.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHuseyin Topaloglu is the Howard and Eleanor Morgan Professor in the School of Operations Research and Information Engineering at\u0026nbsp;Cornell Tech. He holds a Ph.D. in Operations Research and Financial Engineering from Princeton. His recent research focuses on\u0026nbsp;constructing tractable solution methods for large-scale network revenue management problems and building approximation strategies for\u0026nbsp;retail assortment planning. Huseyin Topaloglu is currently serving as an area editor for Analytics in Operations area at Manufacturing and\u0026nbsp;Service Operations Management.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn this talk, we give approximation algorithms for a joint inventory allocation and assortment personalization problem motivated by\u0026nbsp;an online retail setting. In our problem, we have a limited amount of storage capacity that needs to be allocated among multiple products to\u0026nbsp;serve customers that arrive over a selling horizon. At the beginning of the selling horizon, we decide how many units of each product to\u0026nbsp;stock. Over the selling horizon, customers arrive at the platform one by one to make a purchase. Based on the remaining inventories of the\u0026nbsp;products and the information available on the arriving customer, we offer a personalized assortment of products to each customer. The\u0026nbsp;customer either makes a choice within the offered assortment or leaves without a purchase. Our goal is to decide how many units of each\u0026nbsp;product to stock at the beginning of the selling horizon and to find a policy to figure out which personalized assortment to offer to each\u0026nbsp;arriving customer to maximize the total expected revenue over the selling horizon. Our problem is motivated by same-day-delivery\u0026nbsp;applications in online retail, where the retailer needs to allocate the limited storage capacity in an urban warehouse among different\u0026nbsp;variants in a product category, while having the capability of offering personalized assortments to customers to make better use of\u0026nbsp;remaining inventories. Allocating the storage capacity among the products requires tackling a combinatorial problem, whereas finding an\u0026nbsp;assortment personalization policy requires approximating a dynamic program with a high-dimensional state variable. When the choices of\u0026nbsp;the customers are governed by the multinomial logit model, we give a constant-factor approximation algorithm for this joint inventory\u0026nbsp;allocation and assortment personalization problem. Under a general choice model, we give an algorithm that is asymptotically optimal as\u0026nbsp;the storage capacity gets large. In the latter result, the demand can be scaled in an arbitrary fashion along with the storage capacity. This\u0026nbsp;is joint work with Yicheng Bai, Omar El Housni and Paat Rusmevichientong.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Joint Inventory Allocation and Assortment Personalization with Performance Guarantees"}],"uid":"34977","created_gmt":"2022-11-14 19:39:28","changed_gmt":"2022-12-02 16:11:18","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-12-01T11:00:00-05:00","event_time_end":"2022-12-01T12:00:00-05:00","event_time_end_last":"2022-12-01T12:00:00-05:00","gmt_time_start":"2022-12-01 16:00:00","gmt_time_end":"2022-12-01 17:00:00","gmt_time_end_last":"2022-12-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"166896","name":"seminar"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663511":{"#nid":"663511","#data":{"type":"event","title":"SCL IRC Seminar: Robotics Research and Perspectives","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERobotic systems have been very successful in performing tasks where the inputs are well defined and known in advance. Automotive and electronic manufacturing are the classic success stories where robotic systems have demonstrated incredible value for the industry. In unstructured manufacturing, the inputs of the system can vary significantly, but the outputs of the system are defined. Food and agriculture production are examples of this type of unstructured manufacturing problem, but traditional manufacturing is also moving in this direction as robotics move beyond welding and painting. This presentation will give examples of systems that integrate advanced perception and control technologies into robotic systems to perform complex tasks like cutting, grasping, and manipulation of objects in an unstructured environment.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKER\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/gtri.gatech.edu\/newsroom\/meet-gary-mcmurray-principal-research-engineer\u0022\u003EGary McMurray, Principal Research Engineer\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person, the cost to attend is $5 per session which includes a boxed lunch*\u003C\/strong\u003E. Virtual attendance is always free.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2022-11-29 19:52:29","changed_gmt":"2022-11-29 19:52:40","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-24T12:00:00-05:00","event_time_end":"2023-01-24T13:30:00-05:00","event_time_end_last":"2023-01-24T13:30:00-05:00","gmt_time_start":"2023-01-24 17:00:00","gmt_time_end":"2023-01-24 18:30:00","gmt_time_end_last":"2023-01-24 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"663510":{"id":"663510","type":"image","title":"SCL IRC Seminar: Robotics Research and Perspectives","body":null,"created":"1669751506","gmt_created":"2022-11-29 19:51:46","changed":"1669751506","gmt_changed":"2022-11-29 19:51:46","alt":"","file":{"fid":"251142","name":"GTSCL-McMurray_IRC_202301_16by9.jpg","image_path":"\/sites\/default\/files\/images\/GTSCL-McMurray_IRC_202301_16by9.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/GTSCL-McMurray_IRC_202301_16by9.jpg","mime":"image\/jpeg","size":152161,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/GTSCL-McMurray_IRC_202301_16by9.jpg?itok=HkC7SOja"}}},"media_ids":["663510"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"663476":{"#nid":"663476","#data":{"type":"event","title":"BBISS Seminar Series - Valerie Thomas - 12\/1\/22","body":[{"value":"\u003Ch2\u003E\u003Cstrong\u003ECurrent Methods for Life Cycle Assessment of Low-Carbon Transportation Fuels\u003C\/strong\u003E\u003C\/h2\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EValerie Thomas, Ph.D.,\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003EAnderson-Interface Chair of Natural Systems,\u0026nbsp;Professor,\u0026nbsp;H. Milton School of Industrial and Systems Engineering,\u0026nbsp;joint appointment in the School of Public Policy\u003C\/strong\u003E\u003Cstrong\u003E, Georgia Institute of Technology\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDecmber 1, 2022, 3 - 4 PM ET\u003Cbr \/\u003E\r\nHybrid Event - \u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_OTdkMDNjYzItYTFiZi00ZDZhLTgwYTMtNzBiYzA1OGMyM2Zi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%226fb9bd55-08b4-48ee-baf0-8bbb6cf2e0be%22%7d\u0022 target=\u0022_blank\u0022\u003ETeams Link\u003C\/a\u003E\u003Cbr \/\u003E\r\nGeorgia Tech Exhibition Hall, Room 222, Buckhead Room\u003Cbr \/\u003E\r\nRefreshments will be served. Door prize for in-person participants.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;This talk will present the\u0026nbsp;results of a recent National Academies study chaired by Dr. Thomas, which looks into the methods used to calculate the climate impacts of various low-carbon transportation fuels for life cycle assessments. The\u0026nbsp;implications and opportunities for sustainability research at Georgia Tech will also be discussed.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis talk will present the\u0026nbsp;results of a recent National Academies study chaired by Dr. Thomas, as well as\u0026nbsp;implications and opportunities for sustainability research at Georgia Tech.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Valerie Thomas - Current Methods for life cycle assessment of Low-Carbon Transportation Fuels."}],"uid":"27233","created_gmt":"2022-11-29 00:02:07","changed_gmt":"2022-11-29 15:34:14","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-12-01T15:00:00-05:00","event_time_end":"2022-12-01T16:00:00-05:00","event_time_end_last":"2022-12-01T16:00:00-05:00","gmt_time_start":"2022-12-01 20:00:00","gmt_time_end":"2022-12-01 21:00:00","gmt_time_end_last":"2022-12-01 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food","freebies"],"hg_media":{"663483":{"id":"663483","type":"image","title":"BBISS Speaker Series Speaker - Valerie Thomas","body":null,"created":"1669735110","gmt_created":"2022-11-29 15:18:30","changed":"1669735118","gmt_changed":"2022-11-29 15:18:38","alt":"BBISS Speaker Series Banner for 12\/1\/22","file":{"fid":"251133","name":"hgbanner-vthomas_BBISS.jpg","image_path":"\/sites\/default\/files\/images\/hgbanner-vthomas_BBISS.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/hgbanner-vthomas_BBISS.jpg","mime":"image\/jpeg","size":85052,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/hgbanner-vthomas_BBISS.jpg?itok=MiBKW-tg"}}},"media_ids":["663483"],"related_links":[{"url":"https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_OTdkMDNjYzItYTFiZi00ZDZhLTgwYTMtNzBiYzA1OGMyM2Zi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%226fb9bd55-08b4-48ee-baf0-8bbb6cf2e0be%22%7d","title":"Teams Link for Virtual Participants"},{"url":"https:\/\/calendar.gatech.edu\/event\/2022\/12\/01\/bbiss-seminar-series-valerie-thomas-12122","title":"Event Listing via GT Calendar"}],"groups":[{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"188360","name":"go-bbiss"},{"id":"132161","name":"BBISS"},{"id":"166896","name":"seminar"},{"id":"1135","name":"valerie thomas"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:susan.ryan@gatech.edu\u0022\u003ESusan Ryan\u003C\/a\u003E, Program and Operations Manager, BBISS\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"663278":{"#nid":"663278","#data":{"type":"event","title":"SCL January 2023 Supply Chain Days","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for spring Supply Chain Days! We will be hosting both an On Campus (Jan 26) and a Virtual session\u0026nbsp;(Jan 27). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThursday, Jan 26 | 11am - 2pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, Jan 27\u0026nbsp;|\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our spring Supply Chain Days! We will be hosting both an On Campus (Nov 1) and a Virtual session\u0026nbsp;(Nov 2). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Events where industry supply chain representatives meet with Georgia Tech Supply Chain students"}],"uid":"27233","created_gmt":"2022-11-17 15:13:26","changed_gmt":"2022-11-17 15:13:41","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-26T11:00:00-05:00","event_time_end":"2023-01-27T15:00:00-05:00","event_time_end_last":"2023-01-27T15:00:00-05:00","gmt_time_start":"2023-01-26 16:00:00","gmt_time_end":"2023-01-27 20:00:00","gmt_time_end_last":"2023-01-27 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"663277":{"id":"663277","type":"image","title":"SCL January 2022 Supply Chain Days","body":null,"created":"1668697961","gmt_created":"2022-11-17 15:12:41","changed":"1668697961","gmt_changed":"2022-11-17 15:12:41","alt":"","file":{"fid":"251092","name":"homepage-SCDay_202301-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-SCDay_202301-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-SCDay_202301-600px.jpg","mime":"image\/jpeg","size":81521,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-SCDay_202301-600px.jpg?itok=zgm442Eb"}}},"media_ids":["663277"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"663232":{"#nid":"663232","#data":{"type":"event","title":"ISyE Seminar - Sophie Yu","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEfficient network alignment at Otter\u0026#39;s tree-counting threshold via counting chandeliers\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EGiven a pair of networks, the problem of network alignment or graph matching refers to finding the underlying vertex correspondence that maximally aligns the edges. This is a ubiquitous problem arising in a variety of applications across diverse fields, such as network privacy, computational biology, computer vision, and natural language processing. \u0026nbsp;Network alignment is an instance of the notoriously difficult quadratic assignment problem (QAP), which is NP-hard to solve or approximate.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nDespite the worst-case computational hardness of QAP, I will present a computationally efficient network alignment algorithm based on counting a special family of trees. When the two networks are Erd\u0151s\u0026ndash;R\u0026eacute;nyi random graphs with correlated edges through the hidden vertex correspondence, we show that our algorithm correctly matches all but a vanishing fraction of vertices with high probability as soon as the edge correlation exceeds the square root of Otter\u0026#39;s constant. Moreover, we further upgrade the almost exact recovery to exact recovery whenever it is information-theoretically possible. This is the first polynomial-time algorithm that achieves exact and almost exact matching with an explicit constant correlation for both dense and sparse networks.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHere is the paper link:\u0026nbsp;\u003Ca href=\u0022https:\/\/arxiv.org\/pdf\/2209.12313.pdf\u0022\u003Ehttps:\/\/arxiv.org\/pdf\/2209.12313.pdf\u003C\/a\u003E.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ESophie Yu is a fifth-year Ph.D. Candidate in the field of Decision Sciences in the Fuqua School of Business at Duke University, under Prof. Jiaming Xu. She visited the Simons Institute for the Theory of Computing as a visiting graduate student in Fall 2021. She received her MS in statistical and economic modeling under Prof. Jerry Reiter from Duke University in 2017, and her BS in Economics from Renmin University of China in 2015.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHer research interests focus on data analysis, algorithm design, and performance evaluation in large-scale networks and stochastic systems. Her works draw inspiration from real-world business, engineering, and natural sciences problems that can be modeled into large and complex networks. She has explored a range of topics, from the fundamental limits and efficient algorithms on network alignment to online platform policy design with bounded regret and data confidentiality protection.\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nGiven a pair of networks, the problem of network alignment or graph matching refers to finding the underlying vertex correspondence that maximally aligns the edges. This is a ubiquitous problem arising in a variety of applications across diverse fields, such as network privacy, computational biology, computer vision, and natural language processing. \u0026nbsp;Network alignment is an instance of the notoriously difficult quadratic assignment problem (QAP), which is NP-hard to solve or approximate.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nDespite the worst-case computational hardness of QAP, I will present a computationally efficient network alignment algorithm based on counting a special family of trees. When the two networks are Erd\u0151s\u0026ndash;R\u0026eacute;nyi random graphs with correlated edges through the hidden vertex correspondence, we show that our algorithm correctly matches all but a vanishing fraction of vertices with high probability as soon as the edge correlation exceeds the square root of Otter\u0026#39;s constant. Moreover, we further upgrade the almost exact recovery to exact recovery whenever it is information-theoretically possible. This is the first polynomial-time algorithm that achieves exact and almost exact matching with an explicit constant correlation for both dense and sparse networks.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHere is the paper link:\u0026nbsp;\u003Ca href=\u0022https:\/\/arxiv.org\/pdf\/2209.12313.pdf\u0022\u003Ehttps:\/\/arxiv.org\/pdf\/2209.12313.pdf\u003C\/a\u003E.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Efficient network alignment at Otter\u0027s tree-counting threshold via counting chandeliers"}],"uid":"34977","created_gmt":"2022-11-16 13:48:08","changed_gmt":"2022-11-16 13:48:08","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-12-05T11:00:00-05:00","event_time_end":"2022-12-05T12:00:00-05:00","event_time_end_last":"2022-12-05T12:00:00-05:00","gmt_time_start":"2022-12-05 16:00:00","gmt_time_end":"2022-12-05 17:00:00","gmt_time_end_last":"2022-12-05 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"663139":{"#nid":"663139","#data":{"type":"event","title":"ISyE Seminar - Hansheng Jiang","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EPricing Analytics Under Heterogeneous Consumer Behaviors\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EWe consider intertemporal pricing in the presence of reference effects and consumer heterogeneity. Our research question encompasses how to estimate heterogeneous consumer reference effects from data and how to efficiently compute the optimal pricing policy. Understanding reference effects is essential for designing pricing policies in modern retailing. Our work contributes to this area by incorporating consumer heterogeneity under arbitrary distributions. We propose a mixed logit demand model that allows arbitrary joint distributions of valuations, responsiveness to prices, and responsiveness to reference prices among consumers. We use a nonparametric estimation method to learn consumer heterogeneity from transaction data. Further, we formulate the pricing optimization as an infinite horizon dynamic programming problem and solve it by applying a modified policy iteration algorithm. Moreover, we investigate the structure of optimal pricing policies and prove the sub-optimality of constant pricing policies even when all consumers are loss-averse according to the classical definition. Our numerical studies show that our estimation and optimization framework improves the expected revenue of retailers via accounting for heterogeneity. We validate our model using real data from JD.com, a large E-commerce retailer, and find empirical evidence of consumer heterogeneity. In practice, ignoring consumer heterogeneity may lead to a significant loss of revenue. Furthermore, heterogeneous reference effects offer\u0026nbsp;a strong motive for promotions and price fluctuations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EHansheng Jiang is a final-year Ph.D. candidate in the Department of Industrial Engineering and Operations Research at UC Berkeley, co-advised by Zuo-Jun Max Shen and Aditya Guntuboyina. Her research focuses on developing methodologies and algorithms for sequential and data-driven decision-making, especially in the presence of human\u0026nbsp;behaviors. Her recent works address real-world problems in retailing platforms,\u0026nbsp;on-demand shared mobility systems, and supply chain management. She is a recipient of the Berkeley Fellowship, a winner of the IISA best student paper award in theory and methodology, and a finalist of the MSOM data-driven research challenge.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EWe consider intertemporal pricing in the presence of reference effects and consumer heterogeneity. Our research question encompasses how to estimate heterogeneous consumer reference effects from data and how to efficiently compute the optimal pricing policy. Understanding reference effects is essential for designing pricing policies in modern retailing. Our work contributes to this area by incorporating consumer heterogeneity under arbitrary distributions. We propose a mixed logit demand model that allows arbitrary joint distributions of valuations, responsiveness to prices, and responsiveness to reference prices among consumers. We use a nonparametric estimation method to learn consumer heterogeneity from transaction data. Further, we formulate the pricing optimization as an infinite horizon dynamic programming problem and solve it by applying a modified policy iteration algorithm. Moreover, we investigate the structure of optimal pricing policies and prove the sub-optimality of constant pricing policies even when all consumers are loss-averse according to the classical definition. Our numerical studies show that our estimation and optimization framework improves the expected revenue of retailers via accounting for heterogeneity. We validate our model using real data from JD.com, a large E-commerce retailer, and find empirical evidence of consumer heterogeneity. In practice, ignoring consumer heterogeneity may lead to a significant loss of revenue. Furthermore, heterogeneous reference effects offer\u0026nbsp;a strong motive for promotions and price fluctuations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Pricing Analytics Under Heterogeneous Consumer Behaviors"}],"uid":"34977","created_gmt":"2022-11-14 13:48:14","changed_gmt":"2022-11-14 19:54:29","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-28T11:00:00-05:00","event_time_end":"2022-11-28T12:00:00-05:00","event_time_end_last":"2022-11-28T12:00:00-05:00","gmt_time_start":"2022-11-28 16:00:00","gmt_time_end":"2022-11-28 17:00:00","gmt_time_end_last":"2022-11-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662310":{"#nid":"662310","#data":{"type":"event","title":"ISyE Statistics  Seminar - Jay Batroff","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Jay Bartroff joined the University of Texas at Austin\u0026#39;s Statistics \u0026amp; Data Sciences Department in January 2022 as Professor and Associate Chair. Prior to that he was Professor of Mathematics and Vice-Chair for Statistics at the University of Southern California for 15 years. \u0026nbsp;Before that he was an NSF postdoc in the Stanford Statistics Department, following his PhD at Caltech and his undergraduate degree at U.C. Berkeley. \u0026nbsp;His research interests include sequential analysis, multiple testing, Stein\u0026#39;s method, and a variety of biomedical applications including clinical trial design and methods for wearable alcohol biosensors. Jay\u0026#39;s research has been supported by the NSF, NIH, FDA, and NSA. \u0026nbsp;His publications include a textbook on sequential methods coauthored with Lai and Shih, published by Springer.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003EWe present an efficient method of calculating exact confidence intervals for the hypergeometric number of successes. The method inverts minimum-width acceptance intervals after shifting them to make their endpoints nondecreasing while preserving their level. The resulting set of confidence intervals achieves minimum possible average width, and even in comparison with confidence sets not required to be intervals it attains the minimum possible cardinality most of the time, and always within 1. The method compares favorably with existing methods not only in the size of the intervals but also in the time required to compute them. A similar approach can be taken for optimal confidence intervals for an unknown population size, such as in capture-recapture problems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Jay Bartroff joined the University of Texas at Austin\u0026#39;s Statistics \u0026amp; Data Sciences Department in January 2022 as Professor and Associate Chair. Prior to that he was Professor of Mathematics and Vice-Chair for Statistics at the University of Southern California for 15 years. \u0026nbsp;Before that he was an NSF postdoc in the Stanford Statistics Department, following his PhD at Caltech and his undergraduate degree at U.C. Berkeley. \u0026nbsp;His research interests include sequential analysis, multiple testing, Stein\u0026#39;s method, and a variety of biomedical applications including clinical trial design and methods for wearable alcohol biosensors. Jay\u0026#39;s research has been supported by the NSF, NIH, FDA, and NSA. \u0026nbsp;His publications include a textbook on sequential methods coauthored with Lai and Shih, published by Springer.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003EWe present an efficient method of calculating exact confidence intervals for the hypergeometric number of successes. The method inverts minimum-width acceptance intervals after shifting them to make their endpoints nondecreasing while preserving their level. The resulting set of confidence intervals achieves minimum possible average width, and even in comparison with confidence sets not required to be intervals it attains the minimum possible cardinality most of the time, and always within 1. The method compares favorably with existing methods not only in the size of the intervals but also in the time required to compute them. A similar approach can be taken for optimal confidence intervals for an unknown population size, such as in capture-recapture problems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Optimal hypergeometric confidence sets can (almost) always be intervals "}],"uid":"36358","created_gmt":"2022-10-19 14:55:02","changed_gmt":"2022-11-08 16:02:04","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-10T12:00:00-05:00","event_time_end":"2022-11-10T13:00:00-05:00","event_time_end_last":"2022-11-10T13:00:00-05:00","gmt_time_start":"2022-11-10 17:00:00","gmt_time_end":"2022-11-10 18:00:00","gmt_time_end_last":"2022-11-10 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662864":{"#nid":"662864","#data":{"type":"event","title":"ISyE Statistics Seminar- Ming Yuan","body":[{"value":"\u003Cp\u003EBio:\u0026nbsp;Ming Yuan is Professor of Statistics at Columbia University. He was previously Senior Investigator in Virology at Morgridge Institute for Research and Professor of Statistics at University of Wisconsin at Madison, and prior to that Coca-Cola Junior Professor of Industrial and Systems Engineering at Georgia Institute of Technology. His research and teaching interests lie broadly in statistics and its interface with other quantitative and computational fields such as optimization, machine learning, computational biology and financial engineering. He has over 100 scientific publications in applied mathematics, computer science, electrical engineering, financial econometrics, medical informations, optimization, and statistics among others.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHe has served as the program secretary of the Institute for Mathematical Statistics (IMS), and was a member of the advisory board for the Quality, Statistics and Reliability (QSR) section of the Institute for Operations Research and the Management Sciences (INFORMS). He is also a co-Editor of The Annals of Statistics and has been serving on numerous editorial boards. He was named a Medallion Lecturer of IMS in 2018, and a recipient of the John van Ryzin Award (2004; International Biometrics Society), CAREER Award (2009; US National Science Foundation), the Guy Medal in Bronze (2014; Royal Statistical Society), and the Leo Breiman Junior Researcher Award (2017; the Statistical Learning and Data Mining section of the American Statistical Association).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract: Matrix perturbation bounds developed by Weyl, Davis, Kahan and Wedin and others play a central role in many statistical and machine learning problems. I shall discuss some of the recent progresses in developing similar bounds for higher order tensors. I will highlight the intriguing differences from matrices, and explore their implications in spectral learning problems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBio:\u0026nbsp;Ming Yuan is Professor of Statistics at Columbia University. He was previously Senior Investigator in Virology at Morgridge Institute for Research and Professor of Statistics at University of Wisconsin at Madison, and prior to that Coca-Cola Junior Professor of Industrial and Systems Engineering at Georgia Institute of Technology. His research and teaching interests lie broadly in statistics and its interface with other quantitative and computational fields such as optimization, machine learning, computational biology and financial engineering. He has over 100 scientific publications in applied mathematics, computer science, electrical engineering, financial econometrics, medical informations, optimization, and statistics among others.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHe has served as the program secretary of the Institute for Mathematical Statistics (IMS), and was a member of the advisory board for the Quality, Statistics and Reliability (QSR) section of the Institute for Operations Research and the Management Sciences (INFORMS). He is also a co-Editor of The Annals of Statistics and has been serving on numerous editorial boards. He was named a Medallion Lecturer of IMS in 2018, and a recipient of the John van Ryzin Award (2004; International Biometrics Society), CAREER Award (2009; US National Science Foundation), the Guy Medal in Bronze (2014; Royal Statistical Society), and the Leo Breiman Junior Researcher Award (2017; the Statistical Learning and Data Mining section of the American Statistical Association).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract: Matrix perturbation bounds developed by Weyl, Davis, Kahan and Wedin and others play a central role in many statistical and machine learning problems. I shall discuss some of the recent progresses in developing similar bounds for higher order tensors. I will highlight the intriguing differences from matrices, and explore their implications in spectral learning problems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Spectral Learning for High Dimensional Tensors"}],"uid":"36358","created_gmt":"2022-11-04 16:14:10","changed_gmt":"2022-11-08 16:01:25","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-17T12:00:00-05:00","event_time_end":"2022-11-17T13:00:00-05:00","event_time_end_last":"2022-11-17T13:00:00-05:00","gmt_time_start":"2022-11-17 17:00:00","gmt_time_end":"2022-11-17 18:00:00","gmt_time_end_last":"2022-11-17 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662930":{"#nid":"662930","#data":{"type":"event","title":"ISyE Seminar - Mark Squillante","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOptimal Transport and Minimax Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe first consider a motivational perspective on the mathematical foundations of learning and decision making, spanning a broad spectrum from various fields of mathematics through various applications of learning and decision making. Within this context, we then focus on some recent advances in optimal transport, probability, minimax optimization and computational methods that support the mathematical foundations of learning. This includes a brief overview of minimax formulations and theoretical results for a couple of motivating problems related to statistical convergence and transfer learning. We next consider distributionally robust optimization formulations and solutions of motivating problems related to model generalization and input model uncertainty, together with associated theoretical results and efficient algorithms that balance fundamental tradeoffs between computation and stochastic error. Empirical results further demonstrate and quantify the significant benefits of our solution approaches over previous related work in learning model generalization and nonconvex portfolio choice modeling under cumulative prospect theory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMark S. Squillante is a Distinguished Research Staff Member and the Manager of Foundations of Probability, Dynamics, and Control within the Mathematical Sciences of IBM Research at the Thomas J. Watson Research Center. He has been an adjunct faculty member in the School of Operations Research and Information Engineering at Cornell Tech and the School of Engineering and Applied Science at Columbia University. His research interests broadly concern mathematical foundations of the analysis, modeling and optimization of the design and control of complex systems under uncertainty, and their broad applications. Mark is an elected Fellow of INFORMS, ACM, IEEE and AAIA, and recipient of the (Biennial) Best Publication in Applied Probability Award (INFORMS Applied Probability Society), the Daniel H. Wagner Prize (INFORMS), 9 best paper awards, 27 major IBM technical awards, and 40 IBM invention awards. He currently serves as Editor-in-Chief of Stochastic Models, as Chair of IFIP Working Group 7.3, on the INFORMS Subdivisions Council, and on the Board of Directors of the American Automatic Control Council. He received a Ph.D. degree from the University of Washington.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe first consider a motivational perspective on the mathematical foundations of learning and decision making, spanning a broad spectrum from various fields of mathematics through various applications of learning and decision making. Within this context, we then focus on some recent advances in optimal transport, probability, minimax optimization and computational methods that support the mathematical foundations of learning. This includes a brief overview of minimax formulations and theoretical results for a couple of motivating problems related to statistical convergence and transfer learning. We next consider distributionally robust optimization formulations and solutions of motivating problems related to model generalization and input model uncertainty, together with associated theoretical results and efficient algorithms that balance fundamental tradeoffs between computation and stochastic error. Empirical results further demonstrate and quantify the significant benefits of our solution approaches over previous related work in learning model generalization and nonconvex portfolio choice modeling under cumulative prospect theory.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Optimal Transport and Minimax Optimization"}],"uid":"36374","created_gmt":"2022-11-07 12:49:52","changed_gmt":"2022-11-07 17:24:55","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-11T11:30:00-05:00","event_time_end":"2022-11-11T12:30:00-05:00","event_time_end_last":"2022-11-11T12:30:00-05:00","gmt_time_start":"2022-11-11 16:30:00","gmt_time_end":"2022-11-11 17:30:00","gmt_time_end_last":"2022-11-11 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662932":{"#nid":"662932","#data":{"type":"event","title":"SCL Course: Category Management and Sourcing Leadership (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECategory Management and Sourcing Leadership is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, procurement professionals, project managers, finance analyst, contract managers and all procurement \u0026amp; supply management-related professionals involved with bid package development, bid package analysis, negotiations preparation, contracting and supplier selection activity.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base of solicitation options (i.e. RFI, RFP, RFQ) and which solicitation approach to apply based on your organization\u0026#39;s needs\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of sourcing process and critical steps in the Bid Package development and delivery activities\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage and utilization of solicitation tools to drive successful development of bid packages\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove set up and execution of supplier selection scorecards to aid in identifying best Total Cost of Ownership alternatives\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten understanding of executive communication to leverage leadership support throughout the organization\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBid Package Development Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ESourcing Initiative Process Roadmap\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EMarketplace Analysis Tools\u003C\/li\u003E\r\n\t\u003Cli\u003EBid Package Alternatives \u0026amp; Design\u003C\/li\u003E\r\n\t\u003Cli\u003ESupplier Selection \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026 supply management function."}],"uid":"27233","created_gmt":"2022-11-07 14:21:14","changed_gmt":"2022-11-07 14:21:24","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-03-27T14:00:00-04:00","event_time_end":"2023-03-30T15:30:00-04:00","event_time_end_last":"2023-03-30T15:30:00-04:00","gmt_time_start":"2023-03-27 18:00:00","gmt_time_end":"2023-03-30 19:30:00","gmt_time_end_last":"2023-03-30 19:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/cmsl","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EEMAIL: \u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E or CALL: (404) 385-3501 between 9:00a.m. and 4:00p.m., Eastern time.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"662469":{"#nid":"662469","#data":{"type":"event","title":"ISyE Seminar - Julie Ivy, Ph.D","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDoes your model reflect the needs of the user? Meaningful Data-driven Multi-criteria Decision Modeling: Elicitation of Preference among Multiple Criteria in Food Distribution by Food Banks\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDecision making to satisfy the basic human needs of health, food, and education is complex. In 2020, more than 38 million people, including 12 million children, in the U.S. were food insecure. By 2021, 53 million people sought help from food banks and community programs to feed their families. Food banks are nonprofit organizations that collect and distribute food donations to food-insecure populations in their service regions. Food banks are challenged with juggling multiple criteria such as equity, effectiveness, and efficiency when making distribution decisions. Models that assume predetermined weights on multiple criteria may produce inaccurate results as the preference of food banks over these criteria may vary over time, and as a function of supply and demand. In collaboration with our food bank partner in North Carolina, we develop a single-period, weighted multi-criteria optimization model that provides the decision-maker the flexibility to capture their preferences over the three criteria of equity, effectiveness, and efficiency, and explore the resulting trade-offs. We introduce a novel algorithm to elicit the inherent preference of a food bank by analyzing its actions within a single-period. The algorithm does not require direct interaction with the decision-maker. The non-interactive nature of this algorithm is especially significant for humanitarian organizations such as food banks which lack the resources to interact with modelers on a regular basis. We explore the implications of different decision-maker preferences for the criteria on distribution policies.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJulie Simmons Ivy, Ph.D., is a Professor and Fitts Faculty Fellow of Health Systems Engineering in the Edward P. Fitts Department of Industrial and Systems Engineering at North Carolina State University with extensive background in decision making under conditions of uncertainty using stochastic and statistical modeling. She received her B.S. and Ph.D. in Industrial and Operations Engineering from the University of Michigan. She also received her M.S. in Industrial and Systems Engineering from Georgia Tech. She is an active member of the Institute of Operations Research and Management Science (INFORMS), Dr. Ivy served as the 2007 Chair (President) of the INFORMS Health Applications Society and the 2012 \u0026ndash; 13 President for the INFORMS Minority Issues Forum. Recently, Dr. Ivy was elected as a 2022 INFORMS Fellow. Dr. Ivy\u0026rsquo;s research seeks to model complex interactions and quantitatively capture the impact of different factors, objectives, system dynamics, intervention options and policies on outcomes with the goal of improving decision quality. In particular, Dr. Ivy has extensive background in the application of systems science methods, including the analysis and modeling of large data sets, to hunger relief and health decision making. This research has made an impact on how researchers and practitioners address complex societal issues, such as health disparities, public health preparedness, hunger relief, student performance, and personalized medical decision-making and has been funded by the CDC, NSF, and NIH.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDecision making to satisfy the basic human needs of health, food, and education is complex. In 2020, more than 38 million people, including 12 million children, in the U.S. were food insecure. By 2021, 53 million people sought help from food banks and community programs to feed their families. Food banks are nonprofit organizations that collect and distribute food donations to food-insecure populations in their service regions. Food banks are challenged with juggling multiple criteria such as equity, effectiveness, and efficiency when making distribution decisions. Models that assume predetermined weights on multiple criteria may produce inaccurate results as the preference of food banks over these criteria may vary over time, and as a function of supply and demand. In collaboration with our food bank partner in North Carolina, we develop a single-period, weighted multi-criteria optimization model that provides the decision-maker the flexibility to capture their preferences over the three criteria of equity, effectiveness, and efficiency, and explore the resulting trade-offs. We introduce a novel algorithm to elicit the inherent preference of a food bank by analyzing its actions within a single-period. The algorithm does not require direct interaction with the decision-maker. The non-interactive nature of this algorithm is especially significant for humanitarian organizations such as food banks which lack the resources to interact with modelers on a regular basis. We explore the implications of different decision-maker preferences for the criteria on distribution policies.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Does your model reflect the needs of the user? Meaningful Data-driven Multi-criteria Decision Modeling: Elicitation of Preference among Multiple Criteria in Food Distribution by Food Banks "}],"uid":"36374","created_gmt":"2022-10-24 11:44:04","changed_gmt":"2022-10-24 11:44:04","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-28T12:30:00-04:00","event_time_end":"2022-10-28T13:30:00-04:00","event_time_end_last":"2022-10-28T13:30:00-04:00","gmt_time_start":"2022-10-28 16:30:00","gmt_time_end":"2022-10-28 17:30:00","gmt_time_end_last":"2022-10-28 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662311":{"#nid":"662311","#data":{"type":"event","title":"ISyE Statistics Seminar Speaker- Ralph C. Smith, North Carolina State University ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EFor many complex physical and biological models, the computational cost of high-fidelity simulation codes precludes their direct use for Bayesian model calibration and uncertainty propagation.\u0026nbsp; For example, nuclear power plant codes can take hours to days for a single run.\u0026nbsp; Furthermore, the models often have tens to thousands of inputs -- comprised of parameters, initial conditions, or boundary conditions -- many of which are unidentifiable in the sense that they cannot be uniquely determined using measured responses. In this presentation, we will discuss techniques to isolate influential inputs for subsequent surrogate model construction for Bayesian inference and uncertainty propagation.\u0026nbsp; For input selection, we will discuss advantages and shortcomings of global sensitivity analysis to isolate influential inputs and detail the use of parameter subset selection and active subspace techniques to determine low-dimensional input spaces.\u0026nbsp; We will also discuss the manner in which Bayesian calibration on active subspaces can be used to quantify uncertainties in physical parameters.\u0026nbsp; These techniques will be illustrated for models arising in nuclear power plant design and quantitative systems pharmacology (QSP), as well as models for transductive materials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBiography:\u003C\/strong\u003E Ralph C. Smith joined the North Carolina State University faculty in 1998 where he is presently a Distinguished University Professor of Mathematics.\u0026nbsp; He is co-author of the research monograph \u003Cem\u003ESmart Material Structures: Modeling, Estimation and Control\u003C\/em\u003E and author of the books \u003Cem\u003ESmart Material Systems: Model Development\u003C\/em\u003E and \u003Cem\u003EUncertainty Quantification: Theory, Implementation, and Applications\u003C\/em\u003E.\u0026nbsp; He is on the editorial boards of the \u003Cem\u003EJournal of Intelligent Material Systems and Structures\u003C\/em\u003E and the \u003Cem\u003ESIAM\/ASA Journal on Uncertainty Quantification\u003C\/em\u003E. He is the recipient of the 2016 ASME \u003Cem\u003EAdaptive Structures and Material Systems Prize \u003C\/em\u003Eand the SPIE 2017 \u003Cem\u003ESmart Structures and Materials Lifetime Achievement, \u003C\/em\u003Eand he was named a \u003Cem\u003ESIAM Fellow\u003C\/em\u003E in 2018\u003Cem\u003E. \u003C\/em\u003EHis research areas include mathematical modeling of smart material systems, numerical analysis and methods for physical systems, Bayesian model calibration, sensitivity analysis, control, and uncertainty quantification for physical and biological systems.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EFor many complex physical and biological models, the computational cost of high-fidelity simulation codes precludes their direct use for Bayesian model calibration and uncertainty propagation.\u0026nbsp; For example, nuclear power plant codes can take hours to days for a single run.\u0026nbsp; Furthermore, the models often have tens to thousands of inputs -- comprised of parameters, initial conditions, or boundary conditions -- many of which are unidentifiable in the sense that they cannot be uniquely determined using measured responses. In this presentation, we will discuss techniques to isolate influential inputs for subsequent surrogate model construction for Bayesian inference and uncertainty propagation.\u0026nbsp; For input selection, we will discuss advantages and shortcomings of global sensitivity analysis to isolate influential inputs and detail the use of parameter subset selection and active subspace techniques to determine low-dimensional input spaces.\u0026nbsp; We will also discuss the manner in which Bayesian calibration on active subspaces can be used to quantify uncertainties in physical parameters.\u0026nbsp; These techniques will be illustrated for models arising in nuclear power plant design and quantitative systems pharmacology (QSP), as well as models for transductive materials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBiography:\u003C\/strong\u003E Ralph C. Smith joined the North Carolina State University faculty in 1998 where he is presently a Distinguished University Professor of Mathematics.\u0026nbsp; He is co-author of the research monograph \u003Cem\u003ESmart Material Structures: Modeling, Estimation and Control\u003C\/em\u003E and author of the books \u003Cem\u003ESmart Material Systems: Model Development\u003C\/em\u003E and \u003Cem\u003EUncertainty Quantification: Theory, Implementation, and Applications\u003C\/em\u003E.\u0026nbsp; He is on the editorial boards of the \u003Cem\u003EJournal of Intelligent Material Systems and Structures\u003C\/em\u003E and the \u003Cem\u003ESIAM\/ASA Journal on Uncertainty Quantification\u003C\/em\u003E. He is the recipient of the 2016 ASME \u003Cem\u003EAdaptive Structures and Material Systems Prize \u003C\/em\u003Eand the SPIE 2017 \u003Cem\u003ESmart Structures and Materials Lifetime Achievement, \u003C\/em\u003Eand he was named a \u003Cem\u003ESIAM Fellow\u003C\/em\u003E in 2018\u003Cem\u003E. \u003C\/em\u003EHis research areas include mathematical modeling of smart material systems, numerical analysis and methods for physical systems, Bayesian model calibration, sensitivity analysis, control, and uncertainty quantification for physical and biological systems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Active Subspace Techniques to Construct Surrogate Models for Complex Simulation Codes"}],"uid":"36358","created_gmt":"2022-10-19 15:03:08","changed_gmt":"2022-10-19 15:03:08","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-03T13:00:00-04:00","event_time_end":"2022-11-03T14:00:00-04:00","event_time_end_last":"2022-11-03T14:00:00-04:00","gmt_time_start":"2022-11-03 17:00:00","gmt_time_end":"2022-11-03 18:00:00","gmt_time_end_last":"2022-11-03 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"662153":{"#nid":"662153","#data":{"type":"event","title":"SCL IRC Seminar: The Logistics of Space Exploration","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk, we will discuss the recent progress in logistics-inspired modeling and optimization for space mission design. We will demonstrate several examples of the applications of mathematical optimization to spacecraft and mission design. We will further discuss the methods to evaluate and analyze the design and operational strategies for in-space infrastructure systems in the contexts of human\/robotic space exploration, on-orbit servicing, and satellite constellation missions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKER\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/koki-ho\u0022\u003EKoki Ho\u003C\/a\u003E, \u003C\/strong\u003EAssociate\u0026nbsp;Professor, Aerospace Engineering\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person, the cost to attend is $5 per session which includes a boxed lunch*\u003C\/strong\u003E. Virtual attendance is always free.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2022-10-14 19:52:25","changed_gmt":"2022-10-18 18:58:46","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-17T12:00:00-05:00","event_time_end":"2022-11-17T13:30:00-05:00","event_time_end_last":"2022-11-17T13:30:00-05:00","gmt_time_start":"2022-11-17 17:00:00","gmt_time_end":"2022-11-17 18:30:00","gmt_time_end_last":"2022-11-17 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"662166":{"id":"662166","type":"image","title":"SCL IRC Seminar: The Logistics of Space Exploration","body":null,"created":"1665780697","gmt_created":"2022-10-14 20:51:37","changed":"1666119545","gmt_changed":"2022-10-18 18:59:05","alt":"","file":{"fid":"250825","name":"homepage-Carousel-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-Carousel-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-Carousel-600px.jpg","mime":"image\/jpeg","size":55363,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-Carousel-600px.jpg?itok=6GnX4kmk"}}},"media_ids":["662166"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"662187":{"#nid":"662187","#data":{"type":"event","title":"ISyE Seminar - Carri Chan","body":[{"value":"\u003Cp\u003ETITLE:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPrediction-Driven Surge Planning with Application in the Emergency Department\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT: Determining emergency department (ED) nurse staffing decisions to balance the quality of service and staffing cost can be extremely challenging, especially when there is a high level of uncertainty in patient-demand. Increasing data availability and continuing advancements in predictive analytics provide an opportunity to mitigate demand uncertainty by utilizing demand forecasts. In this work, we study a two-stage prediction- driven staffing framework where the prediction models are integrated with the base (made weeks in advance) and surge (made nearly real-time) staffing decisions in the ED. We quantify the benefit of having the ability to use the more expensive surge staffing and identify the importance of balancing demand uncertainty versus demand stochasticity. We also propose a near-optimal two-stage staffing policy that is straightforward to interpret and implement. Lastly, we develop a unified framework that combines parameter estimation, real- time demand forecasts, and capacity sizing in the ED. High-fidelity simulation experiments for the ED demonstrate that the proposed framework can reduce annual staffing costs by 11%\u0026ndash;16% ($2 M\u0026ndash;$3 M) while guaranteeing timely access to care. Joint work with Yue Hu and Jing Dong.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio: Carri W. Chan is the John A. Howard Professor of Business and the Faculty Director of the Healthcare and Pharmaceutical Management Program at Columbia Business School. Her research is in the area of healthcare operations management. Her primary focus is in data-driven modeling of complex stochastic systems, efficient algorithmic design for queuing systems, dynamic control of stochastic processing systems, and econometric analysis of healthcare systems. Her research combines empirical and stochastic modeling to develop evidence-based approaches to improve patient flow through hospitals. She has worked with clinicians and administrators in numerous hospital systems including Northern California Kaiser Permanente, New York Presbyterian, and Montefiore Medical Center. She is the recipient of a 2014 NSF CAREER award, the 2016 POMS Wickham Skinner Early Career Award, and the 2019 MSOM Young Scholar Prize. She currently serves as a co-Department Editor for the Healthcare Management Department at Management Science. She received her BS in electrical engineering from MIT and MS and Ph.D. in electrical engineering from Stanford University.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDetermining emergency department (ED) nurse staffing decisions to balance the quality of service and staffing cost can be extremely challenging, especially when there is a high level of uncertainty in patient-demand. Increasing data availability and continuing advancements in predictive analytics provide an opportunity to mitigate demand uncertainty by utilizing demand forecasts. In this work, we study a two-stage prediction- driven staffing framework where the prediction models are integrated with the base (made weeks in advance) and surge (made nearly real-time) staffing decisions in the ED. We quantify the benefit of having the ability to use the more expensive surge staffing and identify the importance of balancing demand uncertainty versus demand stochasticity. We also propose a near-optimal two-stage staffing policy that is straightforward to interpret and implement. Lastly, we develop a unified framework that combines parameter estimation, real- time demand forecasts, and capacity sizing in the ED. High-fidelity simulation experiments for the ED demonstrate that the proposed framework can reduce annual staffing costs by 11%\u0026ndash;16% ($2 M\u0026ndash;$3 M) while guaranteeing timely access to care. Joint work with Yue Hu and Jing Dong.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" Prediction-Driven Surge Planning with Application in the Emergency Department"}],"uid":"36374","created_gmt":"2022-10-17 13:12:41","changed_gmt":"2022-10-17 13:12:41","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-04T12:30:00-04:00","event_time_end":"2022-11-04T13:30:00-04:00","event_time_end_last":"2022-11-04T13:30:00-04:00","gmt_time_start":"2022-11-04 16:30:00","gmt_time_end":"2022-11-04 17:30:00","gmt_time_end_last":"2022-11-04 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"661891":{"#nid":"661891","#data":{"type":"event","title":"Ad Hoc Seminar - Professor Jean Pauphilet","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHospital-wide Inpatient Flow: Optimization vs. Recommendation\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;In an attempt to coordinate and optimize hospital operations across all services in real-time, we develop a multistage adaptive robust optimization model, informed by data and ML predictions, that unifies the entire bed assignment process while accounting for present and future inpatient flows, discharges, and bed requests. On simulations calibrated for a 600-bed institution, our optimization model was solved in seconds, reduced off-service placement by 24% on average, and boarding delays by 31%-46%.\u003Cbr \/\u003E\r\nIf deployed in the hospital, however, the benefit will likely be much lower. Among others, the fact that nurses can override the recommendation made by our algorithm can negatively impact performance. In the second half of the talk, we will theoretically study the extent to which this partial adherence phenomenon (a) impacts performance, and (b) should influence the design of the algorithmic recommendation in the first place. Indeed, the best decisions are not necessarily the best advice.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJean is an Assistant Professor of Management Science and Operations at London Business School. His research focuses on large-scale discrete optimization, robust optimization, and machine learning, with applications to healthcare operations. His work has been published in the likes of Operations Research, Mathematical Programming, and M\u0026amp;SOM, and recognized by many awards, including the INFORMS Pierskalla, George E. Nicholson, and Computing Society best student paper awards. Jean received a Ph.D. in Operations Research from MIT and a Dipl\u0026ocirc;me d\u0026#39;ing\u0026eacute;nieur from Ecole Polytechnique (Paris).\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;In an attempt to coordinate and optimize hospital operations across all services in real-time, we develop a multistage adaptive robust optimization model, informed by data and ML predictions, that unifies the entire bed assignment process while accounting for present and future inpatient flows, discharges, and bed requests. On simulations calibrated for a 600-bed institution, our optimization model was solved in seconds, reduced off-service placement by 24% on average, and boarding delays by 31%-46%.\u003Cbr \/\u003E\r\nIf deployed in the hospital, however, the benefit will likely be much lower. Among others, the fact that nurses can override the recommendation made by our algorithm can negatively impact performance. In the second half of the talk, we will theoretically study the extent to which this partial adherence phenomenon (a) impacts performance, and (b) should influence the design of the algorithmic recommendation in the first place. Indeed, the best decisions are not necessarily the best advice.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Hospital-wide Inpatient Flow: Optimization vs. Recommendation"}],"uid":"36374","created_gmt":"2022-10-06 16:23:29","changed_gmt":"2022-10-06 16:23:29","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-11T12:00:00-04:00","event_time_end":"2022-10-11T13:00:00-04:00","event_time_end_last":"2022-10-11T13:00:00-04:00","gmt_time_start":"2022-10-11 16:00:00","gmt_time_end":"2022-10-11 17:00:00","gmt_time_end_last":"2022-10-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"661777":{"#nid":"661777","#data":{"type":"event","title":"ISyE Seminar -  Prof. J. Cole Smith","body":[{"value":"\u003Ch3\u003ETitle:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAsymmetric Stochastic Shortest-Path Interdiction Favoring the Evader\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u0026nbsp;\u003Cbr \/\u003E\r\nAbstract:\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003EThis work was completed with Dr. Di Nguyen, a professor at University College Dublin. We discuss a two-stage shortest-path interdiction problem between an interdictor and\u0026nbsp;an evader, in which the cost for an evader to use each arc is given by the arc\u0026rsquo;s\u0026nbsp;base\u0026nbsp;cost plus an additional cost if the arc is attacked by the interdictor. The interdictor\u0026nbsp;acts first to attack a subset of arcs, and\u0026nbsp;then the evader traverses the network using a\u0026nbsp;shortest path. In the problem we study, the interdictor does not know the exact\u0026nbsp;value of\u0026nbsp;each base cost, but instead only knows the (nonnegative uniform) distributions of each\u0026nbsp;arc\u0026rsquo;s base cost. The evader\u0026nbsp;observes both the subset of arcs attacked by the interdictor\u0026nbsp;and the true base cost values before traversing the network, and is\u0026nbsp;thus at an advantage. The interdictor seeks to\u0026nbsp;maximize evader\u0026rsquo;s shortest-path costs, but the choice of objective is a key\u0026nbsp;consideration. We examine ideas underscoring how the interdictor could maximize the expected objective that an evader will incur,\u0026nbsp;and then more generally explore the maximization of the evader\u0026rsquo;s conditional value-at-risk, given some specified risk parameter.\u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\nBio sketch:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;Dr. J. Cole Smith is\u0026nbsp;Dean\u0026nbsp;of the College of Engineering and Computer Science at Syracuse University. Prior to that role,\u0026nbsp;he served as an Associate Provost for Academic Initiatives and as Department Chair of Industrial Engineering at Clemson University.\u0026nbsp;His research regards mathematical optimization models and algorithms, especially those arising in combinatorial optimization. Dr.\u0026nbsp;Smith\u0026rsquo;s awards include the Young Investigator Award from the ONR, the Hamid K. Elden Outstanding Young Industrial Engineer in\u0026nbsp;Education award, the Operations Research Division Teaching Award, the 2014 Glover-Klingman prize for best paper in Networks,\u0026nbsp;and the best paper award from IIE Transactions in 2007. He became a Fellow of IISE in 2018, and serves as the INFORMS Vice\u0026nbsp;President of Publications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis work was completed with Dr. Di Nguyen, a professor at University College Dublin. We discuss a two-stage shortest-path interdiction problem between an interdictor and\u0026nbsp;an evader, in which the cost for an evader to use each arc is given by the arc\u0026rsquo;s\u0026nbsp;base\u0026nbsp;cost plus an additional cost if the arc is attacked by the interdictor. The interdictor\u0026nbsp;acts first to attack a subset of arcs, and\u0026nbsp;then the evader traverses the network using a\u0026nbsp;shortest path. In the problem we study, the interdictor does not know the exact\u0026nbsp;value of\u0026nbsp;each base cost, but instead only knows the (nonnegative uniform) distributions of each\u0026nbsp;arc\u0026rsquo;s base cost. The evader\u0026nbsp;observes both the subset of arcs attacked by the interdictor\u0026nbsp;and the true base cost values before traversing the network, and is\u0026nbsp;thus at an advantage. The interdictor seeks to\u0026nbsp;maximize evader\u0026rsquo;s shortest-path costs, but the choice of objective is a key\u0026nbsp;consideration. We examine ideas underscoring how the interdictor could maximize the expected objective that an evader will incur,\u0026nbsp;and then more generally explore the maximization of the evader\u0026rsquo;s conditional value-at-risk, given some specified risk parameter.\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Asymmetric Stochastic Shortest-Path Interdiction Favoring the Evader"}],"uid":"36374","created_gmt":"2022-10-03 14:25:30","changed_gmt":"2022-10-06 14:46:21","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-07T12:30:00-04:00","event_time_end":"2022-10-07T13:30:00-04:00","event_time_end_last":"2022-10-07T13:30:00-04:00","gmt_time_start":"2022-10-07 16:30:00","gmt_time_end":"2022-10-07 17:30:00","gmt_time_end_last":"2022-10-07 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"661587":{"#nid":"661587","#data":{"type":"event","title":"ISyE Seminar - Vineet Goyal","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EFrom Disjoint Bilinear Optimization to Affine Policies in Dynamic Robust Optimization\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAffine policies are widely used as a solution approach in dynamic robust optimization where computing an optimal adjustable solution is usually intractable. While the worst case performance of affine policies can be significantly bad, the empirical performance is observed to be near-optimal for a large class of problem instances. This work aims to address this stark-contrast between the worst-case and the empirical performance of affine policies.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nIn particular, we study the performance of affine policies for a two-stage adjustable robust optimization problem under an important class of uncertainty sets, namely the budget of uncertainty and intersection of budget of uncertainty sets. We show that surprisingly affine policies provide nearly the best possible approximation matching the hardness of approximation for this class of uncertainty sets. Our analysis is based on first designing an LP based approximation for a general disjoint bilinear optimization problem over packing polytopes (the separation problem for our two-stage problem). Based on this, we present an LP-restriction for the two-stage problem that we relate to affine policies \u0026nbsp;and show that it gives an $O(\\log n \\log L\/(\\log\\log n \\log\\log L))$-approximation (where $n$ is the number of decision variables, and $L$ is the number of budget constraints describing the uncertainty set). This significantly improves over prior known bounds for the performance of affine policies and nearly matches the hardness of approximation. As a byproduct, we also obtain a significantly faster LP to compute near-optimal affine policies.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThis talk is based on joint work with Ayoub Foussoul and Omar El Housni.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EVineet Goyal is Associate Professor in the Industrial Engineering and Operations Research Department at Columbia University where he joined in 2010. He received his Bachelor\u0026#39;s degree in Computer Science from Indian Institute of Technology, Delhi in 2003 and his Ph.D. in Algorithms, Combinatorics and Optimization (ACO) from Carnegie Mellon University in 2008. Before coming to Columbia, he spent two years as a Postdoctoral Associate at the Operations Research Center at MIT. He is interested in the design of efficient and robust data-driven algorithms for large scale dynamic optimization problems with applications in \u0026nbsp;revenue management and healthcare. He received the 2021 INFORMS Revenue Management and Pricing Section prize and 2019 MSOM Society Best Paper in Operations Research Prize. His research has been supported by grants from NSF, DARPA and the industry including the NSF CAREER Award and faculty research awards from Google, IBM, Adobe and Amazon.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAffine policies are widely used as a solution approach in dynamic robust optimization where computing an optimal adjustable solution is usually intractable. While the worst case performance of affine policies can be significantly bad, the empirical performance is observed to be near-optimal for a large class of problem instances. This work aims to address this stark-contrast between the worst-case and the empirical performance of affine policies.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"From Disjoint Bilinear Optimization to Affine Policies in Dynamic Robust Optimization"}],"uid":"34977","created_gmt":"2022-09-28 13:26:59","changed_gmt":"2022-09-28 13:26:59","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-30T12:30:00-04:00","event_time_end":"2022-09-30T13:30:00-04:00","event_time_end_last":"2022-09-30T13:30:00-04:00","gmt_time_start":"2022-09-30 16:30:00","gmt_time_end":"2022-09-30 17:30:00","gmt_time_end_last":"2022-09-30 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"661478":{"#nid":"661478","#data":{"type":"event","title":"SCL November 2022 Supply Chain Days","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our second fall Supply Chain Days! We will be hosting both an On Campus (Nov 1) and a Virtual session\u0026nbsp;(Nov 2). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETuesday, Nov 1 | 10am - 1pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWednesday, Nov 2 |\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our spring Supply Chain Days! We will be hosting both an On Campus (Nov 1) and a Virtual session\u0026nbsp;(Nov 2). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Events where industry supply chain representatives meet with Georgia Tech Supply Chain students"}],"uid":"27233","created_gmt":"2022-09-22 22:24:15","changed_gmt":"2022-09-22 22:24:21","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-11-01T11:00:00-04:00","event_time_end":"2022-11-02T16:00:00-04:00","event_time_end_last":"2022-11-02T16:00:00-04:00","gmt_time_start":"2022-11-01 15:00:00","gmt_time_end":"2022-11-02 20:00:00","gmt_time_end_last":"2022-11-02 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"661477":{"id":"661477","type":"image","title":"SCL November 2022 Supply Chain Days","body":null,"created":"1663885303","gmt_created":"2022-09-22 22:21:43","changed":"1663885308","gmt_changed":"2022-09-22 22:21:48","alt":"","file":{"fid":"250547","name":"homepage-scday_202211-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-scday_202211-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-scday_202211-600px.jpg","mime":"image\/jpeg","size":81048,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-scday_202211-600px.jpg?itok=rY6BKZ6y"}}},"media_ids":["661477"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"661202":{"#nid":"661202","#data":{"type":"event","title":"ISyE Seminar - Angelia Nedich","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EPenalty Methods for Large-Scale Constrained Optimization Problems\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe optimization problems with a large number of constraints are emerging in many application domains such as optimal control, reinforcement learning, and statistical learning, and artificial intelligence, in general. The challenges posed by the size of the problems in these applications resulted in prolific research in the domain of optimization theory and algorithms. Many refinements and accelerations of various (mainly) first-order methods have been proposed and studied, majority of which solves a penalized re-formulation of the original problem in order to\u0026nbsp;cope with the large number of constraints. This talk will focus on problems with linear constraints and Huber-type penalty approach. Convergence behavior and efficiency of the algorithm will be addressed, as well as some supporting theory.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAngelia Nedich has a Ph.D. from Moscow State University, Moscow, Russia, in Computational Mathematics and Mathematical Physics (1994), and a Ph.D. from Massachusetts Institute of Technology, Cambridge, USA in Electrical and Computer Science Engineering (2002). She has worked as a senior engineer in BAE Systems North America, Advanced Information Technology Division at Burlington, MA. Currently, she is a faculty member of the school of Electrical, Computer and Energy Engineering at Arizona State University at Tempe. Prior to joining Arizona State University, she has been a Willard Scholar faculty member at the University of Illinois at Urbana-Champaign. She is a recipient (jointly with her co-authors) of the Best Paper Award at the Winter Simulation Conference 2013 and the Best Paper Award at the International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) 2015. Her general research interest is in optimization, large scale complex systems dynamics, variational inequalities and games.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe optimization problems with a large number of constraints are emerging in many application domains such as optimal control, reinforcement learning, and statistical learning, and artificial intelligence, in general. The challenges posed by the size of the problems in these applications resulted in prolific research in the domain of optimization theory and algorithms. Many refinements and accelerations of various (mainly) first-order methods have been proposed and studied, majority of which solves a penalized re-formulation of the original problem in order to\u0026nbsp;cope with the large number of constraints. This talk will focus on problems with linear constraints and Huber-type penalty approach. Convergence behavior and efficiency of the algorithm will be addressed, as well as some supporting theory.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Penalty Methods for Large-Scale Constrained Optimization Problems "}],"uid":"34977","created_gmt":"2022-09-15 13:10:36","changed_gmt":"2022-09-15 13:11:40","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-23T12:30:00-04:00","event_time_end":"2022-09-23T13:30:00-04:00","event_time_end_last":"2022-09-23T13:30:00-04:00","gmt_time_start":"2022-09-23 16:30:00","gmt_time_end":"2022-09-23 17:30:00","gmt_time_end_last":"2022-09-23 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660754":{"#nid":"660754","#data":{"type":"event","title":"SCL IRC Seminar: Smart Vehicle Data Collection and Spatial Analysis with ML for Green, Energy-efficient, Cost-effective and Safe Logistics","body":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested faculty, students and corporate partners as well as the general public. If you are interested in attending any of the sessions, please review the below information and register online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION OVERVIEW\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThere are great opportunities to apply emerging technologies, including smart sensors, spatial-temporal analysis, and Artificial Intelligence to provide energy-efficient, eco-friendly, and safe transportation solutions. Dr. Tsai will present his research team\u0026rsquo;s work on collaborating with federal and state transportation agencies, as well as multinational automobile and logistics companies. This work aims to provide an integrated solution to monitor, predict, and optimize vehicle logistics, energy-emission efficiency, and safety by studying the interaction between vehicles and the transportation infrastructure using the developed GT smart data collection and advanced computing framework.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESESSION SPEAKER\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/users\/yi-chang-james-tsai\u0022\u003EYi-Chang James Tsai\u003C\/a\u003E\u003C\/strong\u003E,\u0026nbsp;Professor, Civil and Environmental Engineering\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register\u0022\u003E\u003Cstrong\u003ERegister Online for upcoming SCL IRC seminars\u003C\/strong\u003E\u003C\/a\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn-person attendance to our SCL IRC sessions is complimentary for SCL corporate partners, SCL Industry Advisory Board members, SCL affiliated faculty and students, and students enrolled in the Masters in Supply Chain Engineering program.\u0026nbsp;\u003Cstrong\u003EIf you are a GT student who would like to attend in person and order lunch, we ask that you pay a $5 fee\u003C\/strong\u003E.\u0026nbsp;\u003Cstrong\u003EIf you are a member of the general public attending in-person, the cost to attend is $25 per session which includes a boxed lunch*\u003C\/strong\u003E. Virtual attendance is always free.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease see our registration page relating to taking\u0026nbsp;advantage of the\u0026nbsp;optional in-person lunch.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you have any questions, please email event@scl.gatech.edu.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe Supply Chain and Logistics Institute hosts a series of monthly seminars open to interested SCL faculty, students and corporate partners as well as the general public.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Join the Supply Chain and Logistics Institute for our monthly seminar to learn about affiliated faculty research."}],"uid":"27233","created_gmt":"2022-08-31 19:51:53","changed_gmt":"2022-08-31 20:02:02","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-29T13:00:00-04:00","event_time_end":"2022-09-29T14:30:00-04:00","event_time_end_last":"2022-09-29T14:30:00-04:00","gmt_time_start":"2022-09-29 17:00:00","gmt_time_end":"2022-09-29 18:30:00","gmt_time_end_last":"2022-09-29 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"660753":{"id":"660753","type":"image","title":"SCL IRC Seminar: Smart Vehicle Data Collection and Spatial Analysis","body":null,"created":"1661975506","gmt_created":"2022-08-31 19:51:46","changed":"1661975506","gmt_changed":"2022-08-31 19:51:46","alt":"","file":{"fid":"250349","name":"homepage-SCLIRC_202209-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-SCLIRC_202209-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-SCLIRC_202209-600px.jpg","mime":"image\/jpeg","size":71652,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-SCLIRC_202209-600px.jpg?itok=4QlCUlnr"}}},"media_ids":["660753"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/sclirc\/seminars\/register","title":"Register Online for upcoming SCLIRC seminars"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"122741","name":"physical internet"},{"id":"191205","name":"smart vehicles"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"660681":{"#nid":"660681","#data":{"type":"event","title":"ISyE Seminar - Michael Weylandt","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMultivariate Analysis of Large-Scale Network Series\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ENetworks are an increasingly common representation of real-world phenomena, able to succinctly describe social dynamics, communications infrastructure, genetic mechanisms, and more. In many applications, multiple views on the same network structure are available, each of which captures a different aspect of the same underlying phenomenon. For example, in multi-subject neuroimaging, independently estimated functional networks can be combined to identify common and generalizable patterns in the brain\u0026#39;s response to stimuli. The scope and scale of these and other types of networks give rise to a host of computational and statistical challenges, taxing classical approaches with their ultra-high-dimensionality, small sample sizes, and expensive computation. In the first part of this talk, I develop a novel framework for principal components analysis of a population of networks based on a new class of semi-symmetric tensor decompositions. This Network PCA framework allows us to identify and isolate core patterns which capture network dynamics in a significantly reduced space, enabling more efficient computation and improved statistical estimation in downstream tasks. I also develop a new proof technique for tensors and higher-order power iterations to establish statistical consistency for these challenging non-convex optimization problems. I demonstrate the utility of this framework through applications to trend identification, variance analysis, and changepoint detection on an extended analysis of voting dynamics at the US Supreme Court. In the second half of this talk, I discuss several related problems in unsupervised statistical learning for multiple networks, highlighting my current and future research directions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMichael Weylandt is currently an Intelligence Community Postdoctoral Fellow, working with George Michailidis at the University of Florida. His work focuses on statistical machine learning methodology and computation for highly-structured data, with a particular focus on network data and time series. His work has been recognized with best paper awards from the American Statistical Association Sections in Statistical Learning and Data Science and in Business \u0026amp; Economic Statistics. He has served as a mentor in the Google Summer of Code program for 7 years on behalf of the R Foundation for Statistical Computing and previously held an NSF Graduate Research Fellowship. Prior to beginning his Ph.D. studies, he worked at Morgan Stanley as a quantitative analyst, focusing on derivatives pricing and financial risk management. He received a Bachelor\u0026#39;s of Science in Engineering from Princeton University in 2008 and a Ph.D. in Statistics from Rice University in 2020.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ENetworks are an increasingly common representation of real-world phenomena, able to succinctly describe social dynamics, communications infrastructure, genetic mechanisms, and more. In many applications, multiple views on the same network structure are available, each of which captures a different aspect of the same underlying phenomenon. For example, in multi-subject neuroimaging, independently estimated functional networks can be combined to identify common and generalizable patterns in the brain\u0026#39;s response to stimuli. The scope and scale of these and other types of networks give rise to a host of computational and statistical challenges, taxing classical approaches with their ultra-high-dimensionality, small sample sizes, and expensive computation. In the first part of this talk, I develop a novel framework for principal components analysis of a population of networks based on a new class of semi-symmetric tensor decompositions. This Network PCA framework allows us to identify and isolate core patterns which capture network dynamics in a significantly reduced space, enabling more efficient computation and improved statistical estimation in downstream tasks. I also develop a new proof technique for tensors and higher-order power iterations to establish statistical consistency for these challenging non-convex optimization problems. I demonstrate the utility of this framework through applications to trend identification, variance analysis, and changepoint detection on an extended analysis of voting dynamics at the US Supreme Court. In the second half of this talk, I discuss several related problems in unsupervised statistical learning for multiple networks, highlighting my current and future research directions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Multivariate Analysis of Large-Scale Network Series"}],"uid":"34977","created_gmt":"2022-08-30 13:33:00","changed_gmt":"2022-08-30 13:33:00","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-06T12:00:00-04:00","event_time_end":"2022-09-06T13:00:00-04:00","event_time_end_last":"2022-09-06T13:00:00-04:00","gmt_time_start":"2022-09-06 16:00:00","gmt_time_end":"2022-09-06 17:00:00","gmt_time_end_last":"2022-09-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660489":{"#nid":"660489","#data":{"type":"event","title":"ISyE Statistical Seminar Speaker- Tan Bui-Thanh","body":[{"value":"\u003Cp\u003EBio\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETan Bui-Thanh is an associate professor, and the endowed William J Murray Jr. Fellow in Engineering No. 4, of the Oden Institute for Computational Engineering \u0026amp; Sciences, and the Department of Aerospace Engineering \u0026amp; Engineering mechanics at the university of Texas at Austin. Bui-Thanh obtained his PhD from the Massachusetts Institute of Technology in 2007, Master of Sciences from the Singapore MIT-Alliance in 2003, and Bachelor of Engineering from the Ho Chi Minh City University of Technology (DHBK) in 2001. He has decades of experience and expertise on multidisciplinary research across the boundaries of different branches of computational science, engineering, and mathematics. Bui-Thanh is a former elected vice president of the SIAM Texas-Louisiana Section, and currently the elected secretary of the SIAM SIAG\/CSE. Bui-Thanh was an NSF early CAREER recipient, the Oden Institute distinguished research award, and a two-time winner of the Moncrief Faculty Challenging award.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDeep Learning (DL) by design is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering problems in which underlying physical properties (such as stability, conservation, and positivity) and desired accuracy need to be achieved. DL methods in their original forms are not capable of respecting the underlying mathematical models or achieving desired accuracy even in big-data regimes. On the other hand, many data-driven science and engineering problems, such as inverse problems, typically have limited experimental or observational data, and DL would overfit the data in this case. Leveraging information encoded in the underlying mathematical models, we argue, not only compensates missing information in low data regimes but also provides opportunities to equip DL methods with the underlying physics and hence obtaining higher accuracy. This talk introduces a Tikhonov Network (TNet) that is capable of learning Tikhonov regularized inverse problems. We present and provide intuitions for our formulations for general nonlinear problems. We rigorously show that our TNet approach can learn information encoded in the underlying mathematical models, and thus can produce consistent or equivalent inverse solutions, while naive purely data-based counterparts cannot. Furthermore, we theoretically study the error estimate between TNet and Tikhhonov inverse solutions and under which conditions they are the same. Extension to statistical inverse problems will also be presented.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBio\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETan Bui-Thanh is an associate professor, and the endowed William J Murray Jr. Fellow in Engineering No. 4, of the Oden Institute for Computational Engineering \u0026amp; Sciences, and the Department of Aerospace Engineering \u0026amp; Engineering mechanics at the university of Texas at Austin. Bui-Thanh obtained his PhD from the Massachusetts Institute of Technology in 2007, Master of Sciences from the Singapore MIT-Alliance in 2003, and Bachelor of Engineering from the Ho Chi Minh City University of Technology (DHBK) in 2001. He has decades of experience and expertise on multidisciplinary research across the boundaries of different branches of computational science, engineering, and mathematics. Bui-Thanh is a former elected vice president of the SIAM Texas-Louisiana Section, and currently the elected secretary of the SIAM SIAG\/CSE. Bui-Thanh was an NSF early CAREER recipient, the Oden Institute distinguished research award, and a two-time winner of the Moncrief Faculty Challenging award.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDeep Learning (DL) by design is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering problems in which underlying physical properties (such as stability, conservation, and positivity) and desired accuracy need to be achieved. DL methods in their original forms are not capable of respecting the underlying mathematical models or achieving desired accuracy even in big-data regimes. On the other hand, many data-driven science and engineering problems, such as inverse problems, typically have limited experimental or observational data, and DL would overfit the data in this case. Leveraging information encoded in the underlying mathematical models, we argue, not only compensates missing information in low data regimes but also provides opportunities to equip DL methods with the underlying physics and hence obtaining higher accuracy. This talk introduces a Tikhonov Network (TNet) that is capable of learning Tikhonov regularized inverse problems. We present and provide intuitions for our formulations for general nonlinear problems. We rigorously show that our TNet approach can learn information encoded in the underlying mathematical models, and thus can produce consistent or equivalent inverse solutions, while naive purely data-based counterparts cannot. Furthermore, we theoretically study the error estimate between TNet and Tikhhonov inverse solutions and under which conditions they are the same. Extension to statistical inverse problems will also be presented.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A model-constrained deep learning approach for inverse problems and UQ"}],"uid":"36358","created_gmt":"2022-08-24 15:38:23","changed_gmt":"2022-08-24 15:39:39","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-15T13:00:00-04:00","event_time_end":"2022-09-15T14:00:00-04:00","event_time_end_last":"2022-09-15T14:00:00-04:00","gmt_time_start":"2022-09-15 17:00:00","gmt_time_end":"2022-09-15 18:00:00","gmt_time_end_last":"2022-09-15 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660488":{"#nid":"660488","#data":{"type":"event","title":"ISyE Statistical Seminar Speaker - Zhaoran Wang ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EZhaoran Wang is an assistant professor at Northwestern University, working at the interface of machine learning, statistics, and optimization. He is the recipient of the AISTATS (Artificial Intelligence and Statistics Conference) notable paper award, ASA (American Statistical Association) best student paper in statistical learning and data mining, INFORMS (Institute for Operations Research and the Management Sciences) best student paper finalist in data mining, Microsoft Ph.D. Fellowship, Simons-Berkeley\/J.P. Morgan AI Research Fellowship, Amazon Machine Learning Research Award, and NSF CAREER Award.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECoupled with powerful function approximators such as deep neural networks, reinforcement learning (RL) achieves tremendous empirical successes. However, its theoretical understandings lag behind. In particular, it remains unclear how to provably attain the optimal policy with a finite regret or sample complexity. In this talk, we will present the two sides of the same coin, which demonstrates an intriguing duality between optimism and pessimism.\u003Cbr \/\u003E\r\n\u0026ndash; In the online setting, we aim to learn the optimal policy by actively interacting with the environment. To strike a balance between exploration and exploitation, we propose an optimistic least-squares value iteration algorithm, which achieves a \\sqrt{T} regret in the presence of linear, kernel, and neural function approximators.\u003Cbr \/\u003E\r\n\u0026ndash; In the offline setting, we aim to learn the optimal policy based on a dataset collected a priori. Due to a lack of active interactions with the environment, we suffer from the insufficient coverage of the dataset. To maximally exploit the dataset, we propose a pessimistic least-squares value iteration algorithm, which achieves a minimax-optimal sample complexity.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EZhaoran Wang is an assistant professor at Northwestern University, working at the interface of machine learning, statistics, and optimization. He is the recipient of the AISTATS (Artificial Intelligence and Statistics Conference) notable paper award, ASA (American Statistical Association) best student paper in statistical learning and data mining, INFORMS (Institute for Operations Research and the Management Sciences) best student paper finalist in data mining, Microsoft Ph.D. Fellowship, Simons-Berkeley\/J.P. Morgan AI Research Fellowship, Amazon Machine Learning Research Award, and NSF CAREER Award.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECoupled with powerful function approximators such as deep neural networks, reinforcement learning (RL) achieves tremendous empirical successes. However, its theoretical understandings lag behind. In particular, it remains unclear how to provably attain the optimal policy with a finite regret or sample complexity. In this talk, we will present the two sides of the same coin, which demonstrates an intriguing duality between optimism and pessimism.\u003Cbr \/\u003E\r\n\u0026ndash; In the online setting, we aim to learn the optimal policy by actively interacting with the environment. To strike a balance between exploration and exploitation, we propose an optimistic least-squares value iteration algorithm, which achieves a \\sqrt{T} regret in the presence of linear, kernel, and neural function approximators.\u003Cbr \/\u003E\r\n\u0026ndash; In the offline setting, we aim to learn the optimal policy based on a dataset collected a priori. Due to a lack of active interactions with the environment, we suffer from the insufficient coverage of the dataset. To maximally exploit the dataset, we propose a pessimistic least-squares value iteration algorithm, which achieves a minimax-optimal sample complexity.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Demystifying (Deep) Reinforcement Learning with Optimism and Pessimism, ZHAORAN WANG, Northwestern University"}],"uid":"36358","created_gmt":"2022-08-24 15:33:30","changed_gmt":"2022-08-24 15:33:48","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-01T13:00:00-04:00","event_time_end":"2022-09-01T14:00:00-04:00","event_time_end_last":"2022-09-01T14:00:00-04:00","gmt_time_start":"2022-09-01 17:00:00","gmt_time_end":"2022-09-01 18:00:00","gmt_time_end_last":"2022-09-01 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660487":{"#nid":"660487","#data":{"type":"event","title":"ISyE Statistical Seminar Speaker- Fan Li","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFan Li is a professor in the Departments of Statistical Science, and Biostatistics and Bioinformatics at Duke University. Her primary research interest is statistical methods for causal inference, with applications to clinical trials, health and social sciences. She has developed the overlap weighting method. She also works on the interface of causal inference and machine learning, Bayesian analysis and missing data. She is an associate editor of Journal of the American Statistical Association, Bayesian Analysis, and Observational Studies.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn pragmatic cluster randomized experiments, units are often recruited after the random cluster assignment. This can lead to post-randomization selection bias, inducing systematic differences in baseline characteristics of the recruited patients between intervention and control arms. We clarify that in such situations there are two different causal estimands of average treatment effects, one on the overall population and one on the recruited population, which require different data and strategies to identify. We specify the conditions under which cluster randomization implies individual randomization. We show that under the assumption of ignorable recruitment, the average treatment effect on the recruited population can be consistently estimated from the recruited sample. While the average treatment effect on the overall population is generally not identifiable from the recruited sample alone, a meaningful weighted estimand on the overall population can be consistently estimated via applying a simple weighting scheme to the recruited sample. This estimand corresponds to the subpopulation of units who would be recruited into the study regardless of the assignment. We also develop a sensitivity analysis method for checking the ignorable recruitment assumption. The proposed methods are illustrated via a real world application in cardiology.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFan Li is a professor in the Departments of Statistical Science, and Biostatistics and Bioinformatics at Duke University. Her primary research interest is statistical methods for causal inference, with applications to clinical trials, health and social sciences. She has developed the overlap weighting method. She also works on the interface of causal inference and machine learning, Bayesian analysis and missing data. She is an associate editor of Journal of the American Statistical Association, Bayesian Analysis, and Observational Studies.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn pragmatic cluster randomized experiments, units are often recruited after the random cluster assignment. This can lead to post-randomization selection bias, inducing systematic differences in baseline characteristics of the recruited patients between intervention and control arms. We clarify that in such situations there are two different causal estimands of average treatment effects, one on the overall population and one on the recruited population, which require different data and strategies to identify. We specify the conditions under which cluster randomization implies individual randomization. We show that under the assumption of ignorable recruitment, the average treatment effect on the recruited population can be consistently estimated from the recruited sample. While the average treatment effect on the overall population is generally not identifiable from the recruited sample alone, a meaningful weighted estimand on the overall population can be consistently estimated via applying a simple weighting scheme to the recruited sample. This estimand corresponds to the subpopulation of units who would be recruited into the study regardless of the assignment. We also develop a sensitivity analysis method for checking the ignorable recruitment assumption. The proposed methods are illustrated via a real world application in cardiology.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Addressing selection bias in cluster randomized experiments"}],"uid":"36358","created_gmt":"2022-08-24 15:27:43","changed_gmt":"2022-08-24 15:27:43","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-27T13:00:00-04:00","event_time_end":"2022-10-27T14:00:00-04:00","event_time_end_last":"2022-10-27T14:00:00-04:00","gmt_time_start":"2022-10-27 17:00:00","gmt_time_end":"2022-10-27 18:00:00","gmt_time_end_last":"2022-10-27 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660486":{"#nid":"660486","#data":{"type":"event","title":"ISyE Statistical Seminar- Yu Yi","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI am a Reader in the Department of Statistics, University of Warwick and a Turing Fellow at the Alan Turing Institute, previously an Associate Professor in the University of Warwick, a Lecturer in the University of Bristol, a postdoc of Professor Richard Samworth and a graduate student of Professor Zhiliang Ying. I obtained my academic degrees from Fudan University (B.Sc. in Mathematics, June 2009 and Ph.D. in Mathematical Statistics, June 2013).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis paper concerns about the limiting distributions of change point\u003Cbr \/\u003E\r\nestimators, in a high-dimensional linear regression time series context, where\u003Cbr \/\u003E\r\na regression object $(y_t, X_t) \\in \\mathbb{R} \\times \\mathbb{R}^p$ is observed\u003Cbr \/\u003E\r\nat every time point $t \\in \\{1, \\ldots, n\\}$. At unknown time points, called\u003Cbr \/\u003E\r\nchange points, the regression coefficients change, with the jump sizes measured\u003Cbr \/\u003E\r\nin $\\ell_2$-norm. We provide limiting distributions of the change point\u003Cbr \/\u003E\r\nestimators in the regimes where the minimal jump size vanishes and where it\u003Cbr \/\u003E\r\nremains a constant. We allow for both the covariate and noise sequences to be\u003Cbr \/\u003E\r\ntemporally dependent, in the functional dependence framework, which is the\u003Cbr \/\u003E\r\nfirst time seen in the change point inference literature. We show that a\u003Cbr \/\u003E\r\nblock-type long-run variance estimator is consistent under the functional\u003Cbr \/\u003E\r\ndependence, which facilitates the practical implementation of our derived\u003Cbr \/\u003E\r\nlimiting distributions. We also present a few important byproducts of their own\u003Cbr \/\u003E\r\ninterest, including a novel variant of the dynamic programming algorithm to\u003Cbr \/\u003E\r\nboost the computational efficiency, consistent change point localisation rates\u003Cbr \/\u003E\r\nunder functional dependence and a new Bernstein inequality for data possessing\u003Cbr \/\u003E\r\nfunctional dependence. \u0026nbsp;The paper is available at\u0026nbsp;\u003Ca href=\u0022http:\/\/arxiv.org\/abs\/2207.12453\u0022\u003Ehttp:\/\/arxiv.org\/abs\/2207.12453\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI am a Reader in the Department of Statistics, University of Warwick and a Turing Fellow at the Alan Turing Institute, previously an Associate Professor in the University of Warwick, a Lecturer in the University of Bristol, a postdoc of Professor Richard Samworth and a graduate student of Professor Zhiliang Ying. I obtained my academic degrees from Fudan University (B.Sc. in Mathematics, June 2009 and Ph.D. in Mathematical Statistics, June 2013).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis paper concerns about the limiting distributions of change point\u003Cbr \/\u003E\r\nestimators, in a high-dimensional linear regression time series context, where\u003Cbr \/\u003E\r\na regression object $(y_t, X_t) \\in \\mathbb{R} \\times \\mathbb{R}^p$ is observed\u003Cbr \/\u003E\r\nat every time point $t \\in \\{1, \\ldots, n\\}$. At unknown time points, called\u003Cbr \/\u003E\r\nchange points, the regression coefficients change, with the jump sizes measured\u003Cbr \/\u003E\r\nin $\\ell_2$-norm. We provide limiting distributions of the change point\u003Cbr \/\u003E\r\nestimators in the regimes where the minimal jump size vanishes and where it\u003Cbr \/\u003E\r\nremains a constant. We allow for both the covariate and noise sequences to be\u003Cbr \/\u003E\r\ntemporally dependent, in the functional dependence framework, which is the\u003Cbr \/\u003E\r\nfirst time seen in the change point inference literature. We show that a\u003Cbr \/\u003E\r\nblock-type long-run variance estimator is consistent under the functional\u003Cbr \/\u003E\r\ndependence, which facilitates the practical implementation of our derived\u003Cbr \/\u003E\r\nlimiting distributions. We also present a few important byproducts of their own\u003Cbr \/\u003E\r\ninterest, including a novel variant of the dynamic programming algorithm to\u003Cbr \/\u003E\r\nboost the computational efficiency, consistent change point localisation rates\u003Cbr \/\u003E\r\nunder functional dependence and a new Bernstein inequality for data possessing\u003Cbr \/\u003E\r\nfunctional dependence. \u0026nbsp;The paper is available at\u0026nbsp;\u003Ca href=\u0022http:\/\/arxiv.org\/abs\/2207.12453\u0022\u003Ehttp:\/\/arxiv.org\/abs\/2207.12453\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" Change point inference in high-dimensional regression models under temporal dependence"}],"uid":"36358","created_gmt":"2022-08-24 15:22:02","changed_gmt":"2022-08-24 15:23:42","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-06T13:00:00-04:00","event_time_end":"2022-10-06T14:00:00-04:00","event_time_end_last":"2022-10-06T14:00:00-04:00","gmt_time_start":"2022-10-06 17:00:00","gmt_time_end":"2022-10-06 18:00:00","gmt_time_end_last":"2022-10-06 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660485":{"#nid":"660485","#data":{"type":"event","title":"ISyE Statistics Seminar- Matias Cattaneo","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;Bio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMatias D. Cattaneo is a Professor of\u0026nbsp;\u003Ca href=\u0022https:\/\/orfe.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EOperations Research and Financial Engineering\u003C\/a\u003E\u0026nbsp;(ORFE) at Princeton University, where he is also an Associated Faculty in the\u0026nbsp;\u003Ca href=\u0022https:\/\/economics.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EDepartment of Economics\u003C\/a\u003E, the\u0026nbsp;\u003Ca href=\u0022https:\/\/csml.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003ECenter for Statistics and Machine Learning\u003C\/a\u003E\u0026nbsp;(CSML), and the\u0026nbsp;\u003Ca href=\u0022https:\/\/plas.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EProgram in Latin American Studies\u003C\/a\u003E\u0026nbsp;(PLAS). His research spans econometrics, statistics, data science and decision science, with particular interests in program evaluation and causal inference. Most of his work is interdisciplinary and motivated by quantitative problems in the social, behavioral, and biomedical sciences. As part of his main research agenda, he has developed novel semi-\/non-parametric, high-dimensional, and machine learning inference procedures with demonstrably superior robustness to tuning parameter and other implementation choices. Matias was elected Fellow of the\u0026nbsp;\u003Ca href=\u0022https:\/\/imstat.org\/\u0022 target=\u0022_blank\u0022\u003EInstitute of Mathematical Statistics\u003C\/a\u003E\u0026nbsp;(IMS) in 2022. He also serves in the editorial boards of the\u0026nbsp;\u003Cem\u003EJournal of the American Statistical Association\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EEconometrica\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EOperations Research\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EEconometric Theory\u003C\/em\u003E, the\u0026nbsp;\u003Cem\u003EEconometrics Journal\u003C\/em\u003E, and the\u0026nbsp;\u003Cem\u003EJournal of Causal Inference\u003C\/em\u003E. In addition, Matias is an Amazon Scholar, and has advised several governmental, multilateral, non-profit, and for-profit organizations around the world.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nMatias earned a Ph.D. in Economics in 2008 and an M.A. in Statistics in 2005 from the University of California at Berkeley. He also completed an M.A. in Economics at Universidad Torcuato Di Tella in 2003 and a B.A. in Economics at Universidad de Buenos Aires in 2000. Prior to joining Princeton University in 2019, he was a faculty member in the departments of economics and statistics at the University of Michigan.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nMatias was born and raised in Buenos Aires, Argentina. He is married to\u0026nbsp;\u003Ca href=\u0022https:\/\/scholar.princeton.edu\/titiunik\u0022 target=\u0022_blank\u0022\u003ERocio Titiunik\u003C\/a\u003E, and they have two daughters.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003Cstrong\u003E\u0026nbsp;Abstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many other data science disciplines. We consider the problem of uniformly estimating a dyadic Lebesgue density function, focusing on nonparametric kernel-based estimators taking the form of dyadic empirical processes. Our main contributions include the minimaxoptimal uniform convergence rate of the dyadic kernel density estimator, along with strong approximation results for the associated standardized and Studentized t-processes. A consistent variance estimator enables the construction of valid and feasible uniform confidence bands for the unknown density function. A crucial feature of dyadic distributions is that they may be \u0026ldquo;degenerate\u0026rdquo; at certain points in the support of the data, a property making our analysis somewhat delicate. Nonetheless our methods for uniform inference remain robust to the potential presence of such points. For implementation purposes, we discuss procedures based on positive semi-definite covariance estimators, mean squared error optimal bandwidth selectors and robust bias-correction techniques. We illustrate the empirical finite-sample performance of our methods both in simulations and with real-world data. Our technical results concerning strong approximations and maximal inequalities are of potential independent interest. Keywords: dyadic data, networks, kernel density estimation, minimaxity, strong approximation.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;Bio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMatias D. Cattaneo is a Professor of\u0026nbsp;\u003Ca href=\u0022https:\/\/orfe.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EOperations Research and Financial Engineering\u003C\/a\u003E\u0026nbsp;(ORFE) at Princeton University, where he is also an Associated Faculty in the\u0026nbsp;\u003Ca href=\u0022https:\/\/economics.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EDepartment of Economics\u003C\/a\u003E, the\u0026nbsp;\u003Ca href=\u0022https:\/\/csml.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003ECenter for Statistics and Machine Learning\u003C\/a\u003E\u0026nbsp;(CSML), and the\u0026nbsp;\u003Ca href=\u0022https:\/\/plas.princeton.edu\/\u0022 target=\u0022_blank\u0022\u003EProgram in Latin American Studies\u003C\/a\u003E\u0026nbsp;(PLAS). His research spans econometrics, statistics, data science and decision science, with particular interests in program evaluation and causal inference. Most of his work is interdisciplinary and motivated by quantitative problems in the social, behavioral, and biomedical sciences. As part of his main research agenda, he has developed novel semi-\/non-parametric, high-dimensional, and machine learning inference procedures with demonstrably superior robustness to tuning parameter and other implementation choices. Matias was elected Fellow of the\u0026nbsp;\u003Ca href=\u0022https:\/\/imstat.org\/\u0022 target=\u0022_blank\u0022\u003EInstitute of Mathematical Statistics\u003C\/a\u003E\u0026nbsp;(IMS) in 2022. He also serves in the editorial boards of the\u0026nbsp;\u003Cem\u003EJournal of the American Statistical Association\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EEconometrica\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EOperations Research\u003C\/em\u003E,\u0026nbsp;\u003Cem\u003EEconometric Theory\u003C\/em\u003E, the\u0026nbsp;\u003Cem\u003EEconometrics Journal\u003C\/em\u003E, and the\u0026nbsp;\u003Cem\u003EJournal of Causal Inference\u003C\/em\u003E. In addition, Matias is an Amazon Scholar, and has advised several governmental, multilateral, non-profit, and for-profit organizations around the world.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nMatias earned a Ph.D. in Economics in 2008 and an M.A. in Statistics in 2005 from the University of California at Berkeley. He also completed an M.A. in Economics at Universidad Torcuato Di Tella in 2003 and a B.A. in Economics at Universidad de Buenos Aires in 2000. Prior to joining Princeton University in 2019, he was a faculty member in the departments of economics and statistics at the University of Michigan.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nMatias was born and raised in Buenos Aires, Argentina. He is married to\u0026nbsp;\u003Ca href=\u0022https:\/\/scholar.princeton.edu\/titiunik\u0022 target=\u0022_blank\u0022\u003ERocio Titiunik\u003C\/a\u003E, and they have two daughters.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003Cstrong\u003E\u0026nbsp;Abstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many other data science disciplines. We consider the problem of uniformly estimating a dyadic Lebesgue density function, focusing on nonparametric kernel-based estimators taking the form of dyadic empirical processes. Our main contributions include the minimaxoptimal uniform convergence rate of the dyadic kernel density estimator, along with strong approximation results for the associated standardized and Studentized t-processes. A consistent variance estimator enables the construction of valid and feasible uniform confidence bands for the unknown density function. A crucial feature of dyadic distributions is that they may be \u0026ldquo;degenerate\u0026rdquo; at certain points in the support of the data, a property making our analysis somewhat delicate. Nonetheless our methods for uniform inference remain robust to the potential presence of such points. For implementation purposes, we discuss procedures based on positive semi-definite covariance estimators, mean squared error optimal bandwidth selectors and robust bias-correction techniques. We illustrate the empirical finite-sample performance of our methods both in simulations and with real-world data. Our technical results concerning strong approximations and maximal inequalities are of potential independent interest. Keywords: dyadic data, networks, kernel density estimation, minimaxity, strong approximation.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Uniform Inference for Kernel Density Estimators with Dyadic Data"}],"uid":"36358","created_gmt":"2022-08-24 15:15:41","changed_gmt":"2022-08-24 15:16:32","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-22T13:00:00-04:00","event_time_end":"2022-09-22T14:00:00-04:00","event_time_end_last":"2022-09-22T14:00:00-04:00","gmt_time_start":"2022-09-22 17:00:00","gmt_time_end":"2022-09-22 18:00:00","gmt_time_end_last":"2022-09-22 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"660378":{"#nid":"660378","#data":{"type":"event","title":"LeeAnn and Walter Muller Distinguished Lecture Series - Michael I. Jordan, University of California, Berkeley","body":"","field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Thursday, October 13, 2022 - 3:00 p.m. to 4:00 p.m."}],"uid":"33939","created_gmt":"2022-08-22 17:03:42","changed_gmt":"2022-08-22 17:03:42","author":"David Mitchell","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-13T16:00:00-04:00","event_time_end":"2022-10-13T17:00:00-04:00","event_time_end_last":"2022-10-13T17:00:00-04:00","gmt_time_start":"2022-10-13 20:00:00","gmt_time_end":"2022-10-13 21:00:00","gmt_time_end_last":"2022-10-13 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"660377":{"id":"660377","type":"image","title":"Michael I. Jordan","body":null,"created":"1661187521","gmt_created":"2022-08-22 16:58:41","changed":"1661187521","gmt_changed":"2022-08-22 16:58:41","alt":"Michael I. Jordan","file":{"fid":"250260","name":"jordan_head_shot.jpg","image_path":"\/sites\/default\/files\/images\/jordan_head_shot.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/jordan_head_shot.jpg","mime":"image\/jpeg","size":3764113,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/jordan_head_shot.jpg?itok=jNo-lNcv"}}},"media_ids":["660377"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDavid Mitchell\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECommunications Manager\u003C\/p\u003E\r\n\r\n\u003Cp\u003Edavid.mitchell@isye.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"660304":{"#nid":"660304","#data":{"type":"event","title":"ISyE Statistics Seminar- Jay Bartroff","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EWe present an efficient method of calculating exact confidence intervals for the hypergeometric number of successes. The method inverts minimum-width acceptance intervals after shifting them to make their endpoints nondecreasing while preserving their level. The resulting set of confidence intervals achieves minimum possible average width, and even in comparison with confidence sets not required to be intervals it attains the minimum possible cardinality most of the time, and always within 1. The method compares favorably with existing methods not only in the size of the intervals but also in the time required to compute them. A similar approach can be taken for optimal confidence intervals for an unknown population size, such as in capture-recapture problems.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EJay Bartroff joined the University of Texas at Austin\u0026#39;s Statistics \u0026amp; Data Sciences Department in January 2022 as Professor and Associate Chair. Prior to that he was Professor of Mathematics and Vice-Chair for Statistics at the University of Southern California for 15 years. \u0026nbsp;Before that he was an NSF postdoc in the Stanford Statistics Department, following his PhD at Caltech and his undergraduate degree at U.C. Berkeley. \u0026nbsp;His research interests include sequential analysis, multiple testing, Stein\u0026#39;s method, and a variety of biomedical applications including clinical trial design and methods for wearable alcohol biosensors. Jay\u0026#39;s research has been supported by the NSF, NIH, FDA, and NSA. \u0026nbsp;His publications include a textbook on sequential methods coauthored with Lai and Shih, published by Springer.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EWe present an efficient method of calculating exact confidence intervals for the hypergeometric number of successes. The method inverts minimum-width acceptance intervals after shifting them to make their endpoints nondecreasing while preserving their level. The resulting set of confidence intervals achieves minimum possible average width, and even in comparison with confidence sets not required to be intervals it attains the minimum possible cardinality most of the time, and always within 1. The method compares favorably with existing methods not only in the size of the intervals but also in the time required to compute them. A similar approach can be taken for optimal confidence intervals for an unknown population size, such as in capture-recapture problems.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EJay Bartroff joined the University of Texas at Austin\u0026#39;s Statistics \u0026amp; Data Sciences Department in January 2022 as Professor and Associate Chair. Prior to that he was Professor of Mathematics and Vice-Chair for Statistics at the University of Southern California for 15 years. \u0026nbsp;Before that he was an NSF postdoc in the Stanford Statistics Department, following his PhD at Caltech and his undergraduate degree at U.C. Berkeley. \u0026nbsp;His research interests include sequential analysis, multiple testing, Stein\u0026#39;s method, and a variety of biomedical applications including clinical trial design and methods for wearable alcohol biosensors. Jay\u0026#39;s research has been supported by the NSF, NIH, FDA, and NSA. \u0026nbsp;His publications include a textbook on sequential methods coauthored with Lai and Shih, published by Springer.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Optimal hypergeometric confidence sets can (almost) always be intervals "}],"uid":"36358","created_gmt":"2022-08-18 12:58:28","changed_gmt":"2022-08-18 12:58:28","author":"chumphrey30","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-08-25T09:40:00-04:00","event_time_end":"2022-08-25T09:40:00-04:00","event_time_end_last":"2022-08-25T09:40:00-04:00","gmt_time_start":"2022-08-25 13:40:00","gmt_time_end":"2022-08-25 13:40:00","gmt_time_end_last":"2022-08-25 13:40:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"659995":{"#nid":"659995","#data":{"type":"event","title":"ISyE Department Seminar-Erick Moreno Centeno","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESolving sparse linear systems is core to solving linear programs and other optimization problems. Exactly solving linear programs and systems is necessary for some applications (e.g., theoretical results, feasibility problems, military applications, applications with hefty costs, ill-conditioned problems, etc.). To address this, we are developing the Sparse Exact (SPEX) Factorization Framework: a high-performance, well-documented, and highly robust suite of algorithms and software. This talk will focus on the (mostly) untold story behind this research and its theoretical foundations and briefly discuss recent developments and computational results.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Erick Moreno-Centeno is the Associate Professor and Donna and Jim Furber \u0026#39;64 Faculty Fellow at the Wm Michael Barnes \u0026#39;64 Department of Industrial and Systems Engineering and the Eppright University Professor in Undergraduate Teaching Excellence at Texas A\u0026amp;M University. He earned his M.S. and Ph.D. degrees in Industrial Engineering \u0026amp; Operations Research and his M.S. degree in Computer Science, all from the University of California at Berkeley. He received his B.S. in Industrial Physics Engineering from ITESM Campus Monterrey, Mexico. Dr. Moreno\u0026#39;s research focuses on optimization methods free of round-off errors and the design and analysis of new combinatorial optimization algorithms. He was honored with the Dr. Hamed K. Eldin Outstanding Early Career Industrial Engineer in Academia Award (2016) and the INFORMS Computing Society Prize (2021). He serves as Associate Editor for the journals \u003Cem\u003ENetworks\u003C\/em\u003E, \u003Cem\u003EIISE Transactions\u003C\/em\u003E, and \u003Cem\u003EEnergy Systems.\u003C\/em\u003E \u0026nbsp;Dr. Moreno teaches optimization courses, and his passion for teaching has been honored with numerous awards, most notably the Institute of Industrial Engineers\u0026#39; Operations Research Division Teaching Award.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESolving sparse linear systems is core to solving linear programs and other optimization problems. Exactly solving linear programs and systems is necessary for some applications (e.g., theoretical results, feasibility problems, military applications, applications with hefty costs, ill-conditioned problems, etc.). To address this, we are developing the Sparse Exact (SPEX) Factorization Framework: a high-performance, well-documented, and highly robust suite of algorithms and software. This talk will focus on the (mostly) untold story behind this research and its theoretical foundations and briefly discuss recent developments and computational results.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Erick Moreno-Centeno is the Associate Professor and Donna and Jim Furber \u0026#39;64 Faculty Fellow at the Wm Michael Barnes \u0026#39;64 Department of Industrial and Systems Engineering and the Eppright University Professor in Undergraduate Teaching Excellence at Texas A\u0026amp;M University. He earned his M.S. and Ph.D. degrees in Industrial Engineering \u0026amp; Operations Research and his M.S. degree in Computer Science, all from the University of California at Berkeley. He received his B.S. in Industrial Physics Engineering from ITESM Campus Monterrey, Mexico. Dr. Moreno\u0026#39;s research focuses on optimization methods free of round-off errors and the design and analysis of new combinatorial optimization algorithms. He was honored with the Dr. Hamed K. Eldin Outstanding Early Career Industrial Engineer in Academia Award (2016) and the INFORMS Computing Society Prize (2021). He serves as Associate Editor for the journals \u003Cem\u003ENetworks\u003C\/em\u003E, \u003Cem\u003EIISE Transactions\u003C\/em\u003E, and \u003Cem\u003EEnergy Systems.\u003C\/em\u003E \u0026nbsp;Dr. Moreno teaches optimization courses, and his passion for teaching has been honored with numerous awards, most notably the Institute of Industrial Engineers\u0026#39; Operations Research Division Teaching Award.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Towards Sparse Exact Optimization--From an undergraduate idea to a fruitful research topic"}],"uid":"36086","created_gmt":"2022-08-08 15:40:41","changed_gmt":"2022-08-08 15:40:41","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-08-26T12:30:00-04:00","event_time_end":"2022-08-26T13:30:00-04:00","event_time_end_last":"2022-08-26T13:30:00-04:00","gmt_time_start":"2022-08-26 16:30:00","gmt_time_end":"2022-08-26 17:30:00","gmt_time_end_last":"2022-08-26 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"659865":{"#nid":"659865","#data":{"type":"event","title":"SCL September 2022 Supply Chain Days","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our second fall Supply Chain Days! We will be hosting both an On Campus (Sept 8) and a Virtual session\u0026nbsp;(Sept 9). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThursday, September\u0026nbsp;8\u0026nbsp;| 10am-1pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, September 9\u0026nbsp;|\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our spring Supply Chain Days! We will be hosting both an On Campus (Sept 8) and a Virtual session\u0026nbsp;(Sept 9). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Events where industry supply chain representatives meet with Georgia Tech Supply Chain students"}],"uid":"27233","created_gmt":"2022-08-02 22:47:01","changed_gmt":"2022-08-02 22:49:18","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-08T11:00:00-04:00","event_time_end":"2022-09-09T16:00:00-04:00","event_time_end_last":"2022-09-09T16:00:00-04:00","gmt_time_start":"2022-09-08 15:00:00","gmt_time_end":"2022-09-09 20:00:00","gmt_time_end_last":"2022-09-09 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"659866":{"id":"659866","type":"image","title":"SCL September 2022 Supply Chain Days","body":null,"created":"1659480466","gmt_created":"2022-08-02 22:47:46","changed":"1659480476","gmt_changed":"2022-08-02 22:47:56","alt":"","file":{"fid":"250100","name":"homepage-scday_202209-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-scday_202209-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-scday_202209-600px.jpg","mime":"image\/jpeg","size":81138,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-scday_202209-600px.jpg?itok=U_2pPdcL"}}},"media_ids":["659866"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"659778":{"#nid":"659778","#data":{"type":"event","title":"SCL Course: Engineering the Warehouse (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003ECOURSE DESCRIPTION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThe requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. It is no longer sufficient to manage a warehouse based on a simple, arbitrary \u0026ldquo;ABC\u0026rdquo; classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision \u0026ndash; such as where to store or where to pick product \u0026ndash; must be based on careful engineering and economic analysis. Each SKU must identify its own cheapest, fastest path through the warehouse to the customer and then compete with all the other SKUs for the necessary resources. This results in warehouse operations that are finely tuned to patterns of customer orders and maximally efficient. Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEssential learning for those who are seeking cost reductions through better handling methods. Also valuable for those who must replace, upgrade, or add material handling equipment.\u0026nbsp;The two-day course will include case examples and a guided exercise to ensure mastery of the techniques presented.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\r\n\r\n\u003Cp\u003ESupply chain and logistics consultants, supply chain engineers and analysts, facility engineers, and warehouse supervisors and team leaders\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EExchange space for time (or vice versa) to better meet business objectives.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand when to use dedicated storage and when to use shared storage.\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify the most convenient locations in a warehouse based on an economic model.\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify patterns in customer orders and exploit these to speed fulfillment.\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluate warehouse performance.\u003C\/li\u003E\r\n\t\u003Cli\u003EOptimally size and stock a forward pick area.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the best practices in order-picking.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EWarehouse performance\u003C\/li\u003E\r\n\t\u003Cli\u003EModern warehouse trade-offs\u003C\/li\u003E\r\n\t\u003Cli\u003ESize and stocking optimization\u003C\/li\u003E\r\n\t\u003Cli\u003EOrder-picking best practices\u003C\/li\u003E\r\n\t\u003Cli\u003EAutomation\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ECOURSE MATERIALS\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EOnline access to course material in electronic format\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAccess to an e-copy of the book \u0026ldquo;Warehouse \u0026amp; Distribution Science\u0026rdquo;\u0026nbsp;as well as access to an accompanying suite of software to aid in warehouse analytics and optimization.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ECOURSE PREREQUISITES\u003C\/h4\u003E\r\n\r\n\u003Cp\u003ENone.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003ECERTIFICATE INFORMATION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course is part of the \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/education\/professional-education\/courses#DOAD\u0022\u003EDistribution Operations Analysis \u0026amp; Design (DOAD) Certificate\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. It is no longer sufficient to manage a warehouse based on a simple, arbitrary \u0026ldquo;ABC\u0026rdquo; classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision \u0026ndash; such as where to store or where to pick product \u0026ndash; must be based on careful engineering and economic analysis.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse."}],"uid":"27233","created_gmt":"2022-07-29 19:36:06","changed_gmt":"2022-07-29 19:36:25","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-13T11:00:00-05:00","event_time_end":"2023-02-16T17:00:00-05:00","event_time_end_last":"2023-02-16T17:00:00-05:00","gmt_time_start":"2023-02-13 16:00:00","gmt_time_end":"2023-02-16 22:00:00","gmt_time_end_last":"2023-02-16 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/engwh","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"6140","name":"warehousing"},{"id":"7149","name":"inventory"},{"id":"167167","name":"storage"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"647535":{"#nid":"647535","#data":{"type":"event","title":"SCL Course: Machine Learning Applications for Supply Chain Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the third in the four-course Supply Chain Analytics Professional certificate program. It introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You\u0026rsquo;ll use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. You\u0026rsquo;ll use Python and PowerBI to create and analyze regression, clustering, and classification models.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars\u0026nbsp;(April 18, 19, 20, 21\u0026nbsp;| 1-5pm ET) and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the role of machine learning (ML) in Supply Chain Management (SCM)\u003C\/li\u003E\r\n\t\u003Cli\u003EApply advanced analytics techniques to build planning tools that can leverage large and real-time data sets\u003C\/li\u003E\r\n\t\u003Cli\u003EApply ML in demand forecasting and predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how to assess ML model performance, improve models, and pick the best model for a decision\u003C\/li\u003E\r\n\t\u003Cli\u003EUse Python and PowerBI to build, analyze, and deploy ML models\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow ML relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EML algorithms such as regression trees, clustering techniques, decision trees, random forests, logistic regression\u003C\/li\u003E\r\n\t\u003Cli\u003EAspects of ML projects including parameter tuning, cross validation, and assess model performance\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in demand forecasting for sales and operations planning (S\u0026amp;OP) and inventory management\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of ML in predictive maintenance\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAn introduction to\u0026nbsp;the field of machine learning as it applies to supply chain management. You\u0026rsquo;ll then use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance."}],"uid":"27233","created_gmt":"2021-05-17 20:40:42","changed_gmt":"2022-06-16 19:19:34","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-08-08T14:00:00-04:00","event_time_end":"2022-08-11T18:00:00-04:00","event_time_end_last":"2022-08-11T18:00:00-04:00","gmt_time_start":"2022-08-08 18:00:00","gmt_time_end":"2022-08-11 22:00:00","gmt_time_end_last":"2022-08-11 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaml","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"648173":{"#nid":"648173","#data":{"type":"event","title":"SCL Course: Supply Chain Optimization and Prescriptive Analytics (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u0026rsquo;ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u0026rsquo;ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars (May 16, 17, 18, 19 | 1-5pm ET) and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUse mathematical optimization to transform Supply Chain Management (SCM) processes.\u003C\/li\u003E\r\n\t\u003Cli\u003EApply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize PowerBI and Python in optimization projects.\u003C\/li\u003E\r\n\t\u003Cli\u003EParticipate in a hackathon that pulls together everything learned throughout the certificate program.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ERole of mathematical optimization in addressing complex SCM challenges \u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAppropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation of production processes, distribution networks, and routes using optimization\u003C\/li\u003E\r\n\t\u003Cli\u003EAbility to pull together all content of the certificate program into a prescriptive analytics project\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn advanced analytics and mathematical optimization to find solutions for supply chain problems.\u0026nbsp;The course also serves as a capstone for the Supply Chain Analytics Professional certificate program\u0026nbsp;by culminating in a hackathon where you\u0026rsquo;ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn advanced analytics and mathematical optimization to find solutions for supply chain problems."}],"uid":"27233","created_gmt":"2021-06-16 18:27:20","changed_gmt":"2022-06-16 19:19:11","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-12T14:00:00-04:00","event_time_end":"2022-09-15T18:00:00-04:00","event_time_end_last":"2022-09-15T18:00:00-04:00","gmt_time_start":"2022-09-12 18:00:00","gmt_time_end":"2022-09-15 22:00:00","gmt_time_end_last":"2022-09-15 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaoc","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"595958":{"#nid":"595958","#data":{"type":"event","title":" Health Systems: The Next Generation Forum 2017","body":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003E\u003Cstrong\u003ECenter for Health \u0026amp; Humanitarian Systems (CHHS)\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;at Georgia Tech invites you to attend an event with professionals and scholars from across the fields of healthcare delivery, operations, and education focused on improving local and global health systems.\u0026nbsp; The goal of this event is to provide a forum for discussion to promote and maintain wellness by identifying important trends in health system applications and technologies and opportunities for collaboration.\u0026nbsp;The event will include two plenary panel sessions, rapid-fire presentations, and two poster session showcasing new approaches, technologies, and research in health systems.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EPanel sessions:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u0026nbsp;\u003Cem\u003EEnd-to-end Health Systems: From Treatment to Management to Prevention to Wellness\u0026nbsp;\u003C\/em\u003E\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Cem\u003ETechnology, Data, and Analytics for Efficient and Effective Health Systems\u003C\/em\u003E\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho should attend?\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAnyone interested in learning about recent work at Georgia Tech and opportunities for future collaboration. For additional information or questions, please contact Joscelyn Cooper (j.cooper@isye.gatech.edu).\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/registration\/\u0022\u003EREGISTER ONLINE\u003C\/a\u003E\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/\u0022 target=\u0022_blank\u0022\u003EAGENDA \u0026amp; REGISTRATION\u003C\/a\u003E\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003ETo Present a Poster at the event\u003C\/strong\u003E, \u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/posters\/\u0022\u003Eplease visit this link\u003C\/a\u003E\u003C\/strong\u003E and submit your proposal\u0026nbsp;before Tuesday,\u0026nbsp;September 19th.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EOrganizers\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#ayer\u0022\u003ETurgay Ayer\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tResearch Director of the Medical Decision-Making, Center for Health and Humanitarian Systems\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#duke\u0022\u003EJon Duke\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tDirector, Health Analytics and Informatics, College of Computing\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#farrugia\u0022\u003ESherry Farrugia\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tManaging Director, Health Research Partnerships, Institute for People and Technology\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#keskinocak\u0022\u003EPinar Keskinocak\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tDirector, Center for Health and Humanitarian Systems\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#swann\u0022\u003EJulie Swann\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tAffiliate, Center for Health and Humanitarian Systems\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003E\r\n\t\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2017\/organizers#wagner-dahl\u0022\u003EMargaret Wagner-Dahl\u003C\/a\u003E\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\tAssociate Vice President for Health IT, Enterprise Innovation Institute\u003C\/p\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ESupporters\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe event is sponsored by the Georgia Tech \u003Ca href=\u0022https:\/\/chhs.gatech.edu\/home\u0022\u003ECenter for Health \u0026amp; Humanitarian Systems\u003C\/a\u003E and the \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\u0022\u003EStewart School of Industrial \u0026amp; Systems Engineering\u003C\/a\u003E. Organizers include Georgia Tech\u0026#39;s \u003Ca href=\u0022http:\/\/innovate.gatech.edu\/\u0022\u003EEnterprise Innovation Institute\u003C\/a\u003E (EI2), \u003Ca href=\u0022http:\/\/ipat.gatech.edu\/\u0022\u003EInstitute of People and Technology\u003C\/a\u003E (IPAT), and\u0026nbsp; the \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/\u0022\u003ECollege of Computing\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003E\u003Cstrong\u003ECenter for Health \u0026amp; Humanitarian Systems (CHHS)\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;at Georgia Tech invites you to attend an event with professionals and scholars from across the fields of healthcare delivery, operations, and education focused on improving local and global health systems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The Center for Health \u0026 Humanitarian Systems (CHHS) at Georgia Tech formally invites you to attend a 1-day event focused on improving health systems."}],"uid":"27233","created_gmt":"2017-09-14 17:38:39","changed_gmt":"2022-05-18 17:08:09","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-09-22T13:30:00-04:00","event_time_end":"2017-09-22T18:15:00-04:00","event_time_end_last":"2017-09-22T18:15:00-04:00","gmt_time_start":"2017-09-22 17:30:00","gmt_time_end":"2017-09-22 22:15:00","gmt_time_end_last":"2017-09-22 22:15:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"595959":{"id":"595959","type":"image","title":"Health Systems: The Next Generation 2017","body":null,"created":"1505410750","gmt_created":"2017-09-14 17:39:10","changed":"1505410750","gmt_changed":"2017-09-14 17:39:10","alt":"Health Systems: The Next Generation 2017","file":{"fid":"227120","name":"banner-HSNG2017.png","image_path":"\/sites\/default\/files\/images\/banner-HSNG2017.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/banner-HSNG2017.png","mime":"image\/png","size":231353,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/banner-HSNG2017.png?itok=D3gVEcxA"}}},"media_ids":["595959"],"related_links":[{"url":"http:\/\/pwp.gatech.edu\/hsng2017\/","title":"Event website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:j.cooper@isye.gatech.edu?subject=HSNG2017%20Question\u0022\u003EJoscelyn Cooper\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"612456":{"#nid":"612456","#data":{"type":"event","title":" Health Systems: The Next Generation Forum 2018","body":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003E\u003Cstrong\u003ECenter for Health \u0026amp; Humanitarian Systems (CHHS)\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;at Georgia Tech invites you to attend an event with professionals and scholars from across the fields of healthcare delivery, operations and education focused on improving local and global health systems. The goal of this event is to promote and maintain wellness by identifying important trends in healthcare system applications and designs, opportunities for collaboration, and the future of health systems. Focusing on the theme of moving from sick-care to healthcare, the event will include two plenary panel sessions, presentations and a poster fair showcasing new proactive methods and research in technological applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIf you or someone you know is interested in showcasing their research during our poster session please visit our submission page - The deadline to submit is Friday10\/26\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EGuest Speakers Include:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EBridget Hurley,\u0026nbsp;\u003C\/strong\u003EVP of Clinical and Regulatory\u0026nbsp;\u003Cstrong\u003E|\u003C\/strong\u003E\u0026nbsp;Evidation Health\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EJim McClelland,\u0026nbsp;\u003C\/strong\u003EExecutive Director for Drug Prevention, Treatment, and Enforcement\u003Cstrong\u003E\u0026nbsp;|\u0026nbsp;\u003C\/strong\u003EState of Indiana\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EPatrick O\u0026rsquo;Neal, M.D.\u0026nbsp;\u003C\/strong\u003ECommissioner \u0026amp; Director of Health Protection\u0026nbsp;\u003Cstrong\u003E|\u003C\/strong\u003EGeorgia Department of Public Health (DPH)\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EVivian Singletary, JM, MBA\u0026nbsp;\u003C\/strong\u003EDirector\u0026nbsp;\u003Cstrong\u003E|\u0026nbsp;\u003C\/strong\u003EPublic Health Informatics Institute (PHII)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"a Forum for professionals and scholars across the fields of healthcare delivery, operations and education focused on improving local and global health systems. "}],"uid":"34586","created_gmt":"2018-10-08 13:01:25","changed_gmt":"2022-05-18 17:07:41","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-11-09T12:30:00-05:00","event_time_end":"2018-11-09T16:30:00-05:00","event_time_end_last":"2018-11-09T16:30:00-05:00","gmt_time_start":"2018-11-09 17:30:00","gmt_time_end":"2018-11-09 21:30:00","gmt_time_end_last":"2018-11-09 21:30:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food","freebies"],"hg_media":{"612452":{"id":"612452","type":"image","title":"Health Systems: The Next Generation 2018 Flyer","body":null,"created":"1539002328","gmt_created":"2018-10-08 12:38:48","changed":"1540175859","gmt_changed":"2018-10-22 02:37:39","alt":"","file":{"fid":"233398","name":"New_HealthSystemsRectangle.png","image_path":"\/sites\/default\/files\/images\/New_HealthSystemsRectangle.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/New_HealthSystemsRectangle.png","mime":"image\/png","size":538429,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/New_HealthSystemsRectangle.png?itok=GhldgfiO"}}},"media_ids":["612452"],"related_links":[{"url":"http:\/\/pwp.gatech.edu\/hsng2018\/","title":"Register Now To Attend!"},{"url":"http:\/\/pwp.gatech.edu\/hsng2018\/posters\/","title":"If you or someone you know wants to showcase research during our poster session please visit our submission page -Deadline 10\/26"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"398","name":"health"},{"id":"8039","name":"Humanitarian"},{"id":"167243","name":"systems"},{"id":"594","name":"college of engineering"},{"id":"426","name":"isye"},{"id":"11866","name":"Industrial Systems and Engineering"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1789","name":"Conference\/Symposium"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"627652":{"#nid":"627652","#data":{"type":"event","title":" Health Systems: The Next Generation Forum 2019","body":[{"value":"\u003Cp\u003EThis Forum provides a platform for thought leaders and field experts with local and global perspectives and knowledge. The impact of the discussions and collaborations range from local initiatives to advance healthcare systems right here in Atlanta to broader impact across the country and beyond.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EOur theme this year:\u003C\/strong\u003E\u0026nbsp;Moving from Sick-care to Healthcare -Interdisciplinary collaboration between medical and STEM fields.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2019\/agenda\/\u0022\u003EAgenda\u0026nbsp;\u003C\/a\u003EWill Include:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2019\/agenda\/\u0022\u003E\u003Cstrong\u003ERapid-fire Presentations\u003C\/strong\u003E\u003C\/a\u003E\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2019\/posters\/\u0022\u003EPoster Session\u003C\/a\u003E\u0026nbsp;(Submit Your Abstract to Participate by Nov 4th)\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003E\u003Ca href=\u0022http:\/\/pwp.gatech.edu\/hsng2019\/agenda\/\u0022\u003EPanel Session\u003C\/a\u003E\u0026nbsp;\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003EFeaturing\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003ETarun Mohan Lal,\u003C\/strong\u003E\u0026nbsp;Chief Analytics Officer and Enterprise Vice President\u0026nbsp;\u003Cstrong\u003E| Navicent Health\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EJoyce Siegele\u003C\/strong\u003E, Director of Productivity Improvement\u0026nbsp;\u003Cstrong\u003E| Northside Hospital\u0026nbsp;\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u0026nbsp;\u003Cstrong\u003EGreg Esper,\u003C\/strong\u003E\u0026nbsp;Vice Chair, Clinical Affairs, Department of Neurology |\u0026nbsp;\u003Cstrong\u003EEmory University School of Medicine\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EVictoria Jordan\u003C\/strong\u003E, Vice President, Quality\u0026nbsp;\u003Cstrong\u003E| Emory Healthcare\u0026nbsp;\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESince its inauguration in 2016, the Forum has annually brought together 120+ professionals, students and scholars from across the fields of healthcare delivery, operations and education focused on promoting and maintaining wellness by identifying important trends in healthcare system applications and designs, opportunities for collaboration, and the future of health systems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Annual Forum organized by The GT Center for Health and Humanitarian Systems (CHHS)."}],"uid":"34586","created_gmt":"2019-10-16 16:02:46","changed_gmt":"2022-05-18 17:07:09","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-11-12T12:30:00-05:00","event_time_end":"2019-11-12T17:30:00-05:00","event_time_end_last":"2019-11-12T17:30:00-05:00","gmt_time_start":"2019-11-12 17:30:00","gmt_time_end":"2019-11-12 22:30:00","gmt_time_end_last":"2019-11-12 22:30:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food","freebies"],"hg_media":{"629649":{"id":"629649","type":"image","title":"Health Systems The Next Generation - 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Email\u0026nbsp;\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"454111":{"#nid":"454111","#data":{"type":"event","title":"2015 Health \u0026 Humanitarian Logistics Conference (South Africa)","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EThe 7th annual \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/\u0022\u003EConference on Health \u0026amp; Humanitarian Logistics\u003C\/a\u003E\u003C\/strong\u003E will take place \u003Cstrong\u003ENovember 18-20th\u003C\/strong\u003E at the\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022gibs.za.co\u0022\u003EGordon Institute\u003C\/a\u003E\u0026nbsp;\u003C\/strong\u003E(GIBS) in Johannesburg, South Africa. The conference draws practitioners from private industry, non-governmental organizations (NGOs), government, and military, who are active participants or interested in health and humanitarian operations,\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E*If you are interested in presenting a\u0026nbsp;poster\u0026nbsp;at the conference,\u0026nbsp;\u003C\/strong\u003Eplease upload your submission online\u0026nbsp;\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/posters\/\u0022\u003Ehere\u003C\/a\u003E\u0026nbsp;as soon as possible or email\u0026nbsp;\u003Ca href=\u0022mailto:msmithgall@isye.gatech.edu\u0022\u003Emsmithgall@isye.gatech.edu\u003C\/a\u003E. A limited amount of funding may be available for accepted poster presenters.including both disaster response and long-term development.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/program\/agenda\/\u0022\u003EPLENARY PANEL\u003C\/a\u003E \u003C\/strong\u003Etopicsinclude:\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EPlanning for and Responding to Complex Humanitarian Emergencies\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EImproving Public Health Systems in Developing Countries\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EHealth Crisis Supply Chains: Reflections on the Ebola Response\u003C\/strong\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EInfrastructure and Capacity: Begin Today to be Ready Tomorrow\u003C\/strong\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/speakers\/\u0022\u003E\u003Cstrong\u003ESPEAKERS\u0026nbsp;\u003C\/strong\u003E\u003C\/a\u003Einclude representatives from the following organizations:\u003Cbr \/\u003E\r\nThe Bill and Melinda Gates Foundation, BI Norwegian Business School, Clinton Health Access Initiative, The Coca-Cola Company, FHI 360, GAVI- The Vaccine Alliance, Georgia Tech, Humanitarian Logistics Association, ICRC, Imperial Health Sciences, IMRES Medical Solutions, INSEAD, Johnson \u0026amp; Johnson, Last Mile Health, MIT, McKinsey \u0026amp; Company, M\u0026eacute;decins Sans Fronti\u0026egrave;res, Medic Mobile, North Star Alliance, Northeastern University, Northwestern University, OXFAM, People that Deliver, Stanford University, The Global Fund to Fight AIDS, Tuberculosis and Malaria, \u0026nbsp;UNICEF, UN Mission on Ebola Emergency Response (UNMEER), UN World Food Programme, UPS, USAID, UTi Pharmaceuticals, and the World Health Organization.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETHE GOAL of the conference\u003C\/strong\u003E is to identify challenges and solutions in logistics and supply-chain topics related to a broad range of health and humanitarian operations including preparation, response, and recovery from natural and man-made disasters and disease outbreak as well as ongoing humanitarian crises due to war, famine, infectious diseases, and chronic health problems.\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003ETHE AGENDA\u0026nbsp;\u003C\/strong\u003Efeatures \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/program\/agenda\/\u0022\u003Eplenary panels, interactive workshops\u003C\/a\u003E, and poster sessions on supply chain management and logistics in global health and humanitarian emergency response and long-term development. The program also includes ample opportunities for networking, health and humanitarian related \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/program\/site-visits\/\u0022\u003Esite visits\u003C\/a\u003E around Johannesburg, and leisure excursions in South Africa.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EOUR\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003ESPONSORS\u003C\/strong\u003E have made this year\u0026#39;s conference possible through their generous support: UPS, IMRES Netherlands\/Imperial Health Sciences, Walmart, Georgia Tech Stewart School of Industrial \u0026amp; Systems Engineering, and Johnson \u0026amp; Johnson. \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/humlog2015\/sponsors\/\u0022\u003E\u003Cstrong\u003ESponsorship\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E opportunities are available.\u0026nbsp;\u003C\/strong\u003EPlease contact Meghan Smithgaall at \u003Ca href=\u0022mailto:msmithgall@isye.gatech.edu\u0022\u003Emsmithgall@isye.gatech.edu\u003C\/a\u003E if you are interested in joining our sponsors to support the conference.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EConference Organizers\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u0026Ouml;zlem Ergun (Northeastern University; Center for Health \u0026amp; Humanitarian Systems, Georgia Tech)\u003C\/li\u003E\r\n\t\u003Cli\u003EJarrod Goentzel (Humanitarian Response Lab, MIT)\u003C\/li\u003E\r\n\t\u003Cli\u003EPinar Keskinocak and Julie Swann (Center for Health \u0026amp; Humanitarian Systems, Georgia Tech)\u003C\/li\u003E\r\n\t\u003Cli\u003ELew Roberts and Shaun Rozyn (Gordon Institute of Business Science, University of Pretoria)\u003C\/li\u003E\r\n\t\u003Cli\u003ELuk Van Wassenhove (Humanitarian Research Group, INSEAD)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EJoin Georgia Tech, INSEAD, MIT, and Northeastern as they host practitioners in global health and humaitarian logistics from across NGOs, government, private companies, and other organizations to identify challenges and solutions in health systems and emergency and long-term development.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The 7th annual Health \u0026 Humanitarian Logistics Conference will focus on topics related to supply chain management and logistics in global health and humanitarian response and development, particularly in Africa."}],"uid":"27858","created_gmt":"2015-09-30 13:43:26","changed_gmt":"2022-05-18 17:05:45","author":"Meghan 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workers","file":{"fid":"203427","name":"mit_ebola_banner.jpg","image_path":"\/sites\/default\/files\/images\/mit_ebola_banner_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/mit_ebola_banner_0.jpg","mime":"image\/jpeg","size":2132184,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/mit_ebola_banner_0.jpg?itok=TAZg_HaS"}}},"media_ids":["454151","454121","454131","454141"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/humlog2015\/","title":"Health \u0026 Humanitarian Logistics Conference"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional 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\u003Cem\u003E\u003Cstrong\u003EJuly 10-11, 2019 | Kigali, Rwanda\u0026nbsp;\u003C\/strong\u003E\u003C\/em\u003Eto provide an open forum to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery. The conference platform encourages learning and collaboration within and across institutions; promotes system-wide improvements in organizations and the sector as a whole; identifies important research issues; and establishes priorities for nongovernmental organizations (NGOs), corporations, and the government in terms of strategies, policies and investments.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERepresentatives from the humanitarian sector, government, NGOs, foundations and private industry, and academia present diverse perspectives in health and humanitarian challenges through keynote addresses, panel discussions, focused workshops, lunchtime group discussions, and interactive poster sessions covering a broad set of research topics and applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe conference is sure to bring together an abundance of professionals active in the global health and humanitarian sectors from around the world. The event is chaired annually by the\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/\u0022 target=\u0022_blank\u0022\u003EGeorgia Tech Center for Health \u0026amp; Humanitarian Systems\u003C\/a\u003E\u0026nbsp;(CHHS),\u0026nbsp;\u003Ca href=\u0022https:\/\/www.ise.ncsu.edu\/\u0022 target=\u0022_blank\u0022\u003ENCSU\u003C\/a\u003E, INSEAD\u0026nbsp;\u003Ca href=\u0022http:\/\/centres.insead.edu\/humanitarian-research-group\/\u0022\u003EHumanitarian Research Group\u003C\/a\u003E, MIT\u0026nbsp;\u003Ca href=\u0022http:\/\/humanitarian.mit.edu\/\u0022\u003EHumanitarian Response Lab\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022http:\/\/www.mie.neu.edu\/\u0022 target=\u0022_blank\u0022\u003ENortheastern University\u003C\/a\u003E.\u0026nbsp;This year\u0026rsquo;s conference is pleased to have as Co- organizers\u0026nbsp;\u003Ca href=\u0022http:\/\/iaphl.org\/\u0022\u003EThe International Association of Public Health Logisticians\u003C\/a\u003E\u0026nbsp;(IAPHL) and\u0026nbsp;\u003Ca href=\u0022https:\/\/peoplethatdeliver.org\/\u0022 target=\u0022_blank\u0022\u003EPeople that Deliver\u003C\/a\u003E, and\u0026nbsp;\u003Ca href=\u0022https:\/\/hscm.ur.ac.rw\/\u0022 target=\u0022_blank\u0022\u003EUniversity of Rwanda\u0026nbsp;Regional Center for Excellence\u003C\/a\u003E\u0026nbsp;as our Host.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe invite you to attend and particpate as a presenter in the following areas:\u0026nbsp;\u003Cstrong\u003Ecollaborative workshops\u003C\/strong\u003E,\u0026nbsp;\u003Cstrong\u003Eoral presentations\u003C\/strong\u003E\u0026nbsp;and\u0026nbsp;\u003Cstrong\u003Eposter sessions\u003C\/strong\u003E. To see our requirements and\u0026nbsp;submit a proposal visit our\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2019\/program\/presentations\/overview\u0022\u003ECall For Presentations Page\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe\u0026nbsp;\u0026nbsp;\u003Cstrong\u003E11th annual Health \u0026amp; Humanitarian Logistics (HHL) Conference\u0026nbsp;\u003C\/strong\u003Ewill take place \u003Cem\u003E\u003Cstrong\u003EJuly 10-11, 2019 | Kigali, Rwanda\u0026nbsp;\u003C\/strong\u003E\u003C\/em\u003Eto provide an open forum to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery.\u0026nbsp;We invite you to attend and particpate as a presenter in the following areas:\u0026nbsp;\u003Cstrong\u003Ecollaborative workshops\u003C\/strong\u003E,\u0026nbsp;\u003Cstrong\u003Eoral presentations\u003C\/strong\u003E\u0026nbsp;and\u0026nbsp;\u003Cstrong\u003Eposter sessions\u003C\/strong\u003E.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"July 10-11, 2019 | Kigali, Rwanda"}],"uid":"34586","created_gmt":"2019-02-22 18:50:53","changed_gmt":"2022-05-18 16:57:43","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-07-10T09:00:00-04:00","event_time_end":"2019-07-12T17:59:00-04:00","event_time_end_last":"2019-07-12T17:59:00-04:00","gmt_time_start":"2019-07-10 13:00:00","gmt_time_end":"2019-07-12 21:59:00","gmt_time_end_last":"2019-07-12 21:59:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food","freebies"],"hg_media":{"618310":{"id":"618310","type":"image","title":"HHL conference 2019 Announcement","body":null,"created":"1550854994","gmt_created":"2019-02-22 17:03:14","changed":"1550854994","gmt_changed":"2019-02-22 17:03:14","alt":"","file":{"fid":"235343","name":"HealthSystems_Flier_NotInteractive.png 2.png","image_path":"\/sites\/default\/files\/images\/HealthSystems_Flier_NotInteractive.png%202.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/HealthSystems_Flier_NotInteractive.png%202.png","mime":"image\/png","size":1256892,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/HealthSystems_Flier_NotInteractive.png%202.png?itok=Rxls3G_D"}}},"media_ids":["618310"],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/conference\/","title":"Register Now for Early Bird Rates!"},{"url":"https:\/\/chhs.gatech.edu\/conference\/2019\/program\/presentations\/overview","title":"Submit a Presentation Proposal"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"134861","name":"Institute and Campus"},{"id":"506","name":"alumni"},{"id":"1564","name":"community"},{"id":"1432","name":"education"},{"id":"63381","name":"exhibitions"},{"id":"180621","name":"Economic Development and Policy"},{"id":"2510","name":"Institute leadership"},{"id":"180622","name":"Special Events and Guest Speakers"},{"id":"167441","name":"student research"},{"id":"365","name":"Research"},{"id":"807","name":"environment"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EIf you have a question or comments for the organizers, please submit them using our\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2019\/content\/send-organizers-note\u0022\u003Econtact form\u003C\/a\u003E.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"635513":{"#nid":"635513","#data":{"type":"event","title":"2020 Health \u0026 Humanitarian Logistics Conference (Virtual)","body":[{"value":"\u003Cp\u003EThe COVID-19 Pandemic has caused uncertainty and\u0026nbsp;disruption\u0026nbsp;around the world, but the need to discuss challenges and new solutions in global health delivery, disaster preparedness and response, and long-term development still remains.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENow more than ever the world calls for our leadership, our collaboration and our innovation. That is why we\u0026rsquo;ve made the decision to host the\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022HHL 2020 conference\u0022\u003EHHL 2020 Conference\u003C\/a\u003E\u0026nbsp;online.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs we approach the conference date, we encourage you to\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/program\/presentations\/overview\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022submitting your presentations\u0022\u003ER\u003C\/a\u003E\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/registration\u0022\u003Eegister\u003C\/a\u003E\u0026nbsp;and stay up to date with new developments through our website and email communications. \u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/program\u0022\u003ELearn More About\u0026nbsp;\u003C\/a\u003E\u003C\/strong\u003E\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/program\u0022\u003E\u003Cstrong\u003EHHL\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe COVID-19 Pandemic has caused uncertainty and\u0026nbsp;disruption\u0026nbsp;around the world, but the need to discuss challenges and new solutions in global health delivery, disaster preparedness and response, and long-term development still remains.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENow more than ever the world calls for our leadership, our collaboration and our innovation. That is why we\u0026rsquo;ve made the decision to host the\u0026nbsp;\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2020\/\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022HHL 2020 conference\u0022\u003EHHL2020 Conference\u003C\/a\u003E\u0026nbsp;online. \u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Together Virtually, Impacting Reality - Pushing the Boundaries of Agility"}],"uid":"34586","created_gmt":"2020-05-19 18:21:20","changed_gmt":"2022-05-18 16:55:34","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-09-29T11:00:00-04:00","event_time_end":"2020-10-02T14:59:00-04:00","event_time_end_last":"2020-10-02T14:59:00-04:00","gmt_time_start":"2020-09-29 15:00:00","gmt_time_end":"2020-10-02 18:59:00","gmt_time_end_last":"2020-10-02 18:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"638415":{"id":"638415","type":"image","title":"12th Annual Conference on Health \u0026 Humanitarian Logistics","body":null,"created":"1598407220","gmt_created":"2020-08-26 02:00:20","changed":"1598407220","gmt_changed":"2020-08-26 02:00:20","alt":"","file":{"fid":"242773","name":"image-HHL2020_square_444px.jpg","image_path":"\/sites\/default\/files\/images\/image-HHL2020_square_444px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/image-HHL2020_square_444px.jpg","mime":"image\/jpeg","size":69883,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/image-HHL2020_square_444px.jpg?itok=GLfWObdC"}}},"media_ids":["638415"],"related_links":[{"url":"https:\/\/chhs.gatech.edu\/conference\/2020","title":"Visit the HHL2020 Conference Website"},{"url":"https:\/\/chhs.gatech.edu\/conference\/2020\/registration","title":"Register Now"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"1240","name":"humanitarian logistics"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Ehumlogconf@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"603448":{"#nid":"603448","#data":{"type":"event","title":"2018 Health \u0026 Humanitarian Logistics Conference (Dubai)","body":[{"value":"\u003Cp\u003EThe aim of the\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2018\u0022 target=\u0022_top\u0022\u003E10th annual Health \u0026amp; Humanitarian Logistics (HHL) Conference\u003C\/a\u003E\u0026nbsp;\u003C\/strong\u003Eis to provide an open forum to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery. The conference platform encourages learning and collaboration within and across institutions; promotes system-wide improvements in organizations and the sector as a whole; identifies important research issues; and establishes priorities for nongovernmental organizations (NGOs), corporations, and the government in terms of strategies, policies and investments.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERepresentatives from the humanitarian sector, government, NGOs, foundations and private industry, and academia present diverse perspectives in health and humanitarian challenges through keynote addresses, panel discussions, focused workshops, lunchtime group discussions, and interactive poster sessions covering a broad set of research topics and applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis is the first time, the conference will be hosted in Dubai, a staple humanitarian hub, and it is sure to bring together an abundance of professionals active in the global health and humanitarian sectors from around the world.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit the conference website at \u003Ca href=\u0022https:\/\/chhs.gatech.edu\/conference\/2018\u0022\u003Ehttps:\/\/chhs.gatech.edu\/conference\/2018\u003C\/a\u003E.\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003E10\u003Csup\u003Eth\u003C\/sup\u003E Health and Humanitarian Logistics Conference (logo attached)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/gtcenterforhealthhumanitariansystems.cmail19.com\/t\/r-i-jrujuro-l-d\/\u0022\u003E\u003Cstrong\u003ERegister\u0026nbsp;Now\u003C\/strong\u003E\u003C\/a\u003E for our discounted rate by: Wednesday, \u003Cstrong\u003EApril 4\u003C\/strong\u003E\u0026nbsp;2018\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe are pleased to announce registration is now open for The 10th annual \u003Ca href=\u0022http:\/\/gtcenterforhealthhumanitariansystems.cmail19.com\/t\/r-i-jrujuro-l-i\/\u0022\u003EConference on Health and Humanitarian Logistics\u003C\/a\u003E (HHL), an open forum that annually attracts 250+ professionals active in the global health and humanitarian sectors from around the world to discuss the challenges and new solutions in disaster preparedness and response, long-term development and humanitarian aid, and global health delivery.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHosted in Dubai, United Arab Emirates \u003Cstrong\u003EJuly 18-19\u003C\/strong\u003E, the agenda will feature:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Keynote addresses\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Panel discussions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Interactive workshops\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Oral Presentations\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Poster Sessions\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026middot;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;Tour\u0026nbsp;visits to local health and humanitarian logistics facilities\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EREGISTER ONLINE: \u003C\/strong\u003E\u003Ca href=\u0022http:\/\/gtcenterforhealthhumanitariansystems.cmail19.com\/t\/r-i-jrujuro-l-t\/\u0022\u003E\u003Cstrong\u003Ehttps:\/\/chhs.gatech.edu\/conference\/2018\/registration\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe look forward to seeing you at #HHL2018!\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E2018 Conference Co-organizers:\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cem\u003E\u0026Ouml;zlem Ergun, Northeastern University\u003C\/em\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003EJarrod Goentzel, Humanitarian Response Lab, MIT\u003C\/em\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003EPinar Keskinocak, Center for Health \u0026amp; Humanitarian Systems, Georgia Tech\u003C\/em\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003EJulie Swann, \u003C\/em\u003ENC State\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003ELuk Van Wassenhove, Humanitarian Research Group, INSEAD\u003C\/em\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003ELiz \u003C\/em\u003E\u0026nbsp;\u003Cem\u003EIgharo,\u003C\/em\u003E\u0026nbsp;The International Association of Public Health Logisticians (IAPHL)\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cem\u003EDominique Zwinkels,\u003C\/em\u003E\u0026nbsp;People that Deliver\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"an open forum that annually attracts 250+ professionals active in the global health and humanitarian sectors from around the world."}],"uid":"34586","created_gmt":"2018-03-07 20:07:58","changed_gmt":"2022-05-18 16:53:47","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2018-07-18T01:00:00-04:00","event_time_end":"2018-07-20T00:59:00-04:00","event_time_end_last":"2018-07-20T00:59:00-04:00","gmt_time_start":"2018-07-18 05:00:00","gmt_time_end":"2018-07-20 04:59:00","gmt_time_end_last":"2018-07-20 04:59:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food","freebies"],"hg_media":{"603447":{"id":"603447","type":"image","title":"10th Annual Health \u0026 Humanitarian Logistics Conference","body":null,"created":"1520452318","gmt_created":"2018-03-07 19:51:58","changed":"1521644296","gmt_changed":"2018-03-21 14:58:16","alt":"10th Annual Health \u0026 Humanitarian Logistics Conference logo","file":{"fid":"230249","name":"HHL2018-banner_wdate.png","image_path":"\/sites\/default\/files\/images\/HHL2018-banner_wdate.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/HHL2018-banner_wdate.png","mime":"image\/png","size":29835,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/HHL2018-banner_wdate.png?itok=og3RJZQY"}},"592779":{"id":"592779","type":"image","title":"2017 Health and Humanitarian Logistics Conference  Group Photo","body":null,"created":"1497638592","gmt_created":"2017-06-16 18:43:12","changed":"1497638592","gmt_changed":"2017-06-16 18:43:12","alt":"Group photo taken at the 2017 Health and Humanitarian Logistics conference","file":{"fid":"225939","name":"RS7759_Group Photo- 2017 HHL Conference-scr.jpg","image_path":"\/sites\/default\/files\/images\/RS7759_Group%20Photo-%202017%20HHL%20Conference-scr.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/RS7759_Group%20Photo-%202017%20HHL%20Conference-scr.jpg","mime":"image\/jpeg","size":264069,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/RS7759_Group%20Photo-%202017%20HHL%20Conference-scr.jpg?itok=-alGkjN2"}},"603449":{"id":"603449","type":"image","title":"Conference Sponsor and attendees","body":null,"created":"1520453525","gmt_created":"2018-03-07 20:12:05","changed":"1520539724","gmt_changed":"2018-03-08 20:08:44","alt":"","file":{"fid":"230010","name":"UPS Connects at HHL Conference.jpg","image_path":"\/sites\/default\/files\/images\/UPS%20Connects%20at%20HHL%20Conference.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/UPS%20Connects%20at%20HHL%20Conference.jpg","mime":"image\/jpeg","size":591562,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/UPS%20Connects%20at%20HHL%20Conference.jpg?itok=NW8q1CZf"}}},"media_ids":["603447","592779","603449"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJoscelyn D. Cooper\u003C\/strong\u003E \u003Cstrong\u003E|\u003C\/strong\u003E Program Manager\u0026nbsp;\u003Cstrong\u003E|\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology \u0026ndash; Industrial \u0026amp; Systems Engineering (ISyE)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EO:\u003C\/strong\u003E \u003Cstrong\u003E404.385.1432\u003C\/strong\u003E \u003Cstrong\u003E|\u003C\/strong\u003E \u0026nbsp;\u003Cstrong\u003EE: \u003Ca href=\u0022mailto:J.Cooper@ISYE.GaTech.edu\u0022\u003EJ.Cooper@ISYE.GaTech.edu\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"658281":{"#nid":"658281","#data":{"type":"event","title":"SCL Course: World Class Sales and Operations Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003ECOURSE DESCRIPTION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the need for an S\u0026amp;OP cycle in a company\u003C\/li\u003E\r\n\t\u003Cli\u003EApply principles key to success of an S\u0026amp;OP process\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience true market examples relevant to their businesses\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ELEARNING OBJECTIVES\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELearn how to identify and apply best fit S\u0026amp;OP process and technology enablers to your organization and make it a reality based process.\u003C\/li\u003E\r\n\t\u003Cli\u003EWalk through a complete simulated S\u0026amp;OP cycle supported by a technology enabler.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the interaction and integration between the financial and operation levels of S\u0026amp;O.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the key components of an effective S\u0026amp;OP business case through discussion of real life examples of how companies have benefited from the implementation of best practices in S\u0026amp;OP.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDefining the S\u0026amp;OP process before adopting technology\u003C\/li\u003E\r\n\t\u003Cli\u003EThe advantages of value based and reality based S\u0026amp;OP\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy S\u0026amp;OP needs to be integrated closely with operational planning\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat is the scope of each role in the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat are the most valuable outputs and results of the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EHow can technology enable companies to take performance to the next level\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience a complete simulated technology-enabled S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2022-05-17 17:58:04","changed_gmt":"2022-05-17 17:58:15","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-23T08:00:00-05:00","event_time_end":"2023-01-24T12:00:00-05:00","event_time_end_last":"2023-01-24T12:00:00-05:00","gmt_time_start":"2023-01-23 13:00:00","gmt_time_end":"2023-01-24 17:00:00","gmt_time_end_last":"2023-01-24 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.pe.gatech.edu\/courses\/world-class-sales-and-operations-planning","title":"Course registration page"},{"url":"http:\/\/www.scl.gatech.edu\/wcsop","title":"Course webpage within the SCL website"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"658257":{"#nid":"658257","#data":{"type":"event","title":"SCL Course: Financial Decision Making (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe course is designed to help\u0026nbsp;participants understand\u0026nbsp;how decisions impact\u0026nbsp;financial performance, identify\u0026nbsp;initiatives to improve company performance, and build better business cases with the overall goal of\u0026nbsp;improving financial acumen\u0026nbsp;and decision-making.\u0026nbsp;The course utilizes hands-on applications, group discussion, and exercises.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe course is comprised of (1) 60-minute pre-course introductory session (February 2 | 1:30-2:30pm ET) and (3) 90-minute instructor-led LIVE group webinars (February 9, 16, 23 | 1:30-3pm ET) with each group webinar requiring (1) 90-minute session of online pre-work to be completed before each webinar (total of 9 hours). Participants will be able to access the online \u0026quot;pre-work\u0026quot; material starting January 26.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEarly or middle stage career professionals who are or will be responsible for executing organizational strategy tied to an integrated view of the organization (including professionals from distribution and logistics, production, and operations).\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EEnhance your\u0026nbsp;financial acumen\u003C\/li\u003E\r\n\t\u003Cli\u003EGain a framework for better managing financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how faster decision-making can help more quickly capture business and financial benefits\u003C\/li\u003E\r\n\t\u003Cli\u003EObtain practical experience relating to putting together a business case for a real project\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe measures (return, cash flow, etc.) and key drivers (revenue, profitability, asset utilization) of financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EThe \u0026lsquo;Power of One\u0026rsquo; \u0026ndash; the impact of improving any financial metric by 1% (e.g. 1% increase in revenue, 1% decrease in cost of goods sold \u0026amp; 1-day reduction in inventory)\u003C\/li\u003E\r\n\t\u003Cli\u003EHow improvement in operational key performance indicators (KPIs) improves cash flow and overall financial performance, and how to better manage activities that impact operational KPIs.\u003C\/li\u003E\r\n\t\u003Cli\u003EBuilding a business case (strategic fit, critical success factors, change management, intangible benefits, financial criteria e.g., cash flow, payback, NPV and breakeven analysis) and using a business case as a project plan\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 1\u0026ndash; Managing Financial Performance\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of the importance and drivers of financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EHow it is influenced by individual decisions and collectively as a team\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReview Financial Acumen eLearning\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify the areas of financial performance they are responsible for managing\u003C\/li\u003E\r\n\t\u003Cli\u003EExamples of decisions that impact a company\u0026rsquo;s overall performance\u003C\/li\u003E\r\n\t\u003Cli\u003EAnalysis of\u0026nbsp;company\u0026nbsp;(or company of choice) financial performance using FinListics ClientIQ.\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 1 for review by facilitator.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EOverall measures of performance (return, cash flow, etc.)\u003C\/li\u003E\r\n\t\u003Cli\u003EKey drivers of financial performance\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003ERevenue\u003C\/li\u003E\r\n\t\t\u003Cli\u003EProfitability\u003C\/li\u003E\r\n\t\t\u003Cli\u003EAsset utilization\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Analyze financial performance \u0026ndash; trend, peer, and industry\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity:\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EPower of One - what are cash flow benefits from improvements in:\r\n\t\t\u003Cul\u003E\r\n\t\t\t\u003Cli\u003EFinancial metrics by 1% (e.g. 1% increase in revenue, 1% decrease in cost of goods sold)\u003C\/li\u003E\r\n\t\t\t\u003Cli\u003ECapital Utilization (e.g. 1-day reduction in inventory)\u003C\/li\u003E\r\n\t\t\u003C\/ul\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\t\u003Cli\u003EGap Analyses\r\n\t\t\u003Cul\u003E\r\n\t\t\t\u003Cli\u003EImprovement in financial metric to best performing year or best performing peer\u003C\/li\u003E\r\n\t\t\u003C\/ul\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EKey take-aways and how participants will apply what they have learned\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 2 \u0026ndash; Improving Financial Performance\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of how improvement in operational key performance indicators (KPIs) improve cash flow and overall financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EExplain how participants can better manage activities impacting operational KPIs\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIdentify operational KPIs they help manage\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify initiatives to improve operational KPIs\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 2 for review by facilitator.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EFramework for better managing financial performance\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EFinancial metrics -\u0026gt; business processes -\u0026gt; activities and tasks -\u0026gt; operational KPIs\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Identify KPIs participant\u0026rsquo;s company is most focused on improving (e.g., materials, labor, closure rate, employee turnover, etc. What lines of business would be involved? What are the initiatives? What are the business benefits?)\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Power of One and Gap Analyses \u0026ndash; what are cash flow benefits from:\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EImprove targeted operational KPIs by 1%\u003C\/li\u003E\r\n\t\t\u003Cli\u003EImprove performance to targeted performance\u003C\/li\u003E\r\n\t\t\u003Cli\u003ECost of delay in achieving improvement in performance\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EHow faster decision-making can help the company more quickly capture business and financial benefits.\u003C\/li\u003E\r\n\t\u003Cli\u003EKey take-aways and how participants will apply what they have learned\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 3 \u0026ndash; Building the Better Business Case\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop initiative that helps improve participant\u0026rsquo;s company financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of building a business case\u003C\/li\u003E\r\n\t\u003Cli\u003EUsing the business case as project plan instead of check-the-box to get approval\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReview \u003Cem\u003EBusiness Case Acumen\u003C\/em\u003E eLearning\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild on initiative identified in Webinar 2\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelop initial business case\u003C\/li\u003E\r\n\t\u003Cli\u003EConduct cash flow analysis using FinListics ClientIQ\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 3 for review by facilitator.\u0026nbsp;\u0026nbsp;\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBusiness case overview\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EQualitative \u0026ndash; e.g., strategic fit, critical success factors, change management, intangible benefits etc.\u003C\/li\u003E\r\n\t\t\u003Cli\u003EQuantitative \u0026ndash; financial criteria e.g., cash flow, payback, NPV, etc. and breakeven analysis\u003C\/li\u003E\r\n\t\t\u003Cli\u003EMonitoring and managing success\u0026nbsp;\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Present initial business case and receive feedback from peers and facilitator\u003C\/li\u003E\r\n\t\u003Cli\u003ESummary of webinar series\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EKey take-aways\u003C\/li\u003E\r\n\t\t\u003Cli\u003EHow participants will apply what they have learned\u003C\/li\u003E\r\n\t\t\u003Cli\u003EWhat \/ how will they share with others\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe course is designed to help\u0026nbsp;participants understand\u0026nbsp;how decisions impact\u0026nbsp;financial performance, identify\u0026nbsp;initiatives to improve company performance, and build better business cases with the overall goal of\u0026nbsp;improving financial acumen\u0026nbsp;and decision-making.\u0026nbsp;The course utilizes hands-on applications, group discussion, and exercises.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Improve your financial acumen\u00a0and decision-making to improve company performance"}],"uid":"27233","created_gmt":"2022-05-16 21:13:35","changed_gmt":"2022-05-16 21:13:48","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-02T13:30:00-05:00","event_time_end":"2023-02-23T15:00:00-05:00","event_time_end_last":"2023-02-23T15:00:00-05:00","gmt_time_start":"2023-02-02 18:30:00","gmt_time_end":"2023-02-23 20:00:00","gmt_time_end_last":"2023-02-23 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/fdm","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"4175","name":"finance"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"657162":{"#nid":"657162","#data":{"type":"event","title":"ISyE \/ DCL Seminar - Adam Wierman","body":[{"value":"\u003Cp\u003EAlso live streamed at \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/96813456832\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/96813456832\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EZoom Meeting ID: 968 1345 6832\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETITLE: Online Optimization and Control using Black-Box Predictions\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nABSTRACT:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMaking use of modern black-box AI tools is potentially transformational for online optimization and control. However, such machine-learned algorithms typically do not have formal guarantees on their worst-case performance, stability, or safety. So, while their performance may improve upon traditional approaches in \u0026ldquo;typical\u0026rdquo; cases, they may perform arbitrarily worse in scenarios where the training examples are not representative due to, e.g., distribution shift or unrepresentative training data. This represents a significant drawback when considering the use of AI tools for energy systems and autonomous cities, which are safety-critical. A challenging open question is thus: Is it possible to provide guarantees that allow black-box AI tools to be used in safety-critical applications? In this talk, I will introduce recent work that aims to develop algorithms that make use of black-box AI tools to provide good performance in the typical case while integrating the \u0026ldquo;untrusted advice\u0026rdquo; from these algorithms into traditional algorithms to ensure formal worst-case guarantees. Specifically, we will discuss the use of black-box untrusted advice in the context of online convex body chasing, online non-convex optimization, and linear quadratic control, identifying both novel algorithms and fundamental limits in each case.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nBIO: Adam Wierman is a Professor in the Department of Computing and Mathematical Sciences at Caltech. He received his Ph.D., M.Sc., and B.Sc. in Computer Science from Carnegie Mellon University and has been a faculty at Caltech since 2007. Adam\u0026rsquo;s research strives to make the networked systems that govern our world sustainable and resilient. He is best known for his work spearheading the design of algorithms for sustainable data centers and his co-authored book on \u0026ldquo;The Fundamentals of Heavy-tails\u0026rdquo;. He is a recipient of multiple awards, including the ACM Sigmetrics Rising Star award, the ACM Sigmetrics Test of Time award, the IEEE Communications Society William R. Bennett Prize, multiple teaching awards, and is a co-author of papers that have received \u0026ldquo;best paper\u0026rdquo; awards at a wide variety of conferences across computer science, power engineering, and operations research.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"ISyE \/ DCL Seminar - Adam Wierman"}],"uid":"34470","created_gmt":"2022-04-11 15:46:43","changed_gmt":"2022-04-13 18:39:12","author":"phand3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-19T12:00:00-04:00","event_time_end":"2022-04-19T13:00:00-04:00","event_time_end_last":"2022-04-19T13:00:00-04:00","gmt_time_start":"2022-04-19 16:00:00","gmt_time_end":"2022-04-19 17:00:00","gmt_time_end_last":"2022-04-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"657251":{"#nid":"657251","#data":{"type":"event","title":"SCL Seminar: Innovation and Digital Supply Chain at AstraZeneca","body":[{"value":"\u003Ch4\u003E\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/astrazeneca-seminar\u0022\u003ERegister to Attend the Session\u003C\/a\u003E\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWHEN\u003C\/strong\u003E\u003Cbr \/\u003E\r\nMonday, April 18, 12:30-1:45pm ET\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWHERE\u003C\/strong\u003E\u003Cbr \/\u003E\r\nVIRTUAL via BlueJeans\u0026nbsp;Events (after registration, you will receive a link to the session to the email address provided)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWHAT\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGlobal Operations at AstraZeneca plays a critical\u0026nbsp;\u200brole in the development, manufacturing, testing\u0026nbsp;\u200band delivery of our medicines around the world.\u200b With the world\u0026nbsp;around us changing rapidly,\u0026nbsp;\u200bwe are evolving our network, our technology and\u0026nbsp;our\u0026nbsp;capabilities to deliver\u0026nbsp;more\u0026nbsp;medicines, to more\u0026nbsp;patients, more quickly and\u0026nbsp;to build a better, more\u0026nbsp;sustainable future.\u0026nbsp;\u200bIn this session we will be exploring how we are embracing Digital Transformation and Pioneering High-Tech New Strategies Across the supply value chain including:\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EElevating the supply chain end-to-end to meet the needs of patients today and tomorrow in a transformational way\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAdopting digital and Industry 4.0 technologies as the next driver of innovation and patient-centricity\u003C\/li\u003E\r\n\t\u003Cli\u003EDriving ambition Zero Carbon across our value chain through flagship science-based climate strategy\u003C\/li\u003E\r\n\t\u003Cli\u003ECreating a diverse and inclusive workplace where we feel proud of the positive impact we are making to patients, society and the environment\u200b\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWHO\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EGurinder Kaur\u003C\/strong\u003E\u0026nbsp;is the vice president of Operations IT for AstraZeneca, with overall responsibility for the development and execution of end to end supply chain and manufacturing technology and digital strategies. In addition, she is responsible for ensuring the strategic development of digital, data and analytics platforms supporting the global AZ operations function. Reporting into the Chief Digital Officer, Gurinder is a member of the Global Operations and IT Senior Leadership Team.\u0026nbsp;Gurinder has more than 25 years of diverse technology and digital experience in the consumer product goods, automotive and oil and gas industries. She brings a wealth of knowledge and international experience in leveraging technology and digital to drive business results.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPrior to joining AstraZeneca, Gurinder held the role of Chief Information Officer, Coca Cola North America - driving the company\u0026rsquo;s digital transformation journey for key functions including Supply Chain, Operations, Marketing and Sales. Before Coca Cola, she served as Vice President - Global Commercial, Robotics and Analytics Solutions for Kellogg Company. Additionally, Gurinder held senior leadership roles with Diageo, Ford Motor Co and Shell Oil in Asia, Australia, UK, Germany and the US. She began her career as a Audit manager with Deloitte in Kuala Lumpur Malaysia.\u0026nbsp;Gurinder earned her Bachelor of Business degree in Accounting from The Royal Melbourne Institute of Technology University (RMIT) in Australia and her MBA from the University of Michigan. She has completed executive leadership studies at Harvard and Stanford University.\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/gurinder-kaur-bb829b3\/\u0022 rel=\u0022 noopener noreferrer\u0022 target=\u0022_blank\u0022\u003EMs. Kaur\u0026#39;s LinkedIn Profile\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELinzell Harris\u0026nbsp;\u003C\/strong\u003Eis senior vice president of Global Supply Chain and Strategy for AstraZeneca, with overall responsibility for the development and execution of the end to end supply chain platform and product supply strategies. In addition, he is responsible for ensuring the strategic development of network designs and supply chain capabilities supporting the global AZ operational network. Reporting into the EVP of Operations and Information Technology, Linzell is a member of the Global Operations Senior Leadership Team. Linzell has more than 30 years of diverse general management and global operations experience in the consumer product goods, pharmaceutical and luxury goods industries.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPrior to joining AstraZeneca, Linzell held the role of Senior Vice President, Global Supply Chain for TEVA Pharmaceuticals - supporting the company\u0026rsquo;s comprehensive global supply network for generic and specialty pharmaceuticals. \u0026nbsp;Before TEVA, he served as Head of Global Operations for Godiva Chocolatier and as a member of Godiva\u0026rsquo;s Executive Leadership team reporting to the CEO and President.\u0026nbsp;Additionally, Linzell has worked in Senior Management roles at Johnson and Johnson, Pfizer, Warner Lambert and Baxter Healthcare. He began his working career as a Supply Corp officer in the US Navy. Linzell earned a BS in Mathematics from the US Naval Academy in Annapolis, MD with graduate studies at Villanova University. He has completed executive studies at Michigan State, Columbia and Harvard Universities.\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/linzell-harris-6930997\/\u0022 rel=\u0022 noopener noreferrer\u0022 target=\u0022_blank\u0022\u003EMr. Harris\u0026#39; LinkedIn Profile\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E*Special Note\u003Cbr \/\u003E\r\nThe session is being presented as part of ISyE6340:\u0026nbsp;Global Supply Chain Seminar, but is open to the larger Georgia Tech community.\u003C\/em\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGlobal Operations at AstraZeneca plays a critical \u200brole in the development, manufacturing, testing \u200band delivery of our medicines around the world.\u200b With the world around us changing rapidly, \u200bwe are evolving our network, our technology and our capabilities to deliver more medicines, to more patients, more quickly and to build a better, more sustainable future.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Embracing Digital Transformation and Pioneering High-Tech New Strategies Across the Supply Value Chain"}],"uid":"27233","created_gmt":"2022-04-13 16:37:28","changed_gmt":"2022-04-13 16:39:23","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-18T13:30:00-04:00","event_time_end":"2022-04-18T14:45:00-04:00","event_time_end_last":"2022-04-18T14:45:00-04:00","gmt_time_start":"2022-04-18 17:30:00","gmt_time_end":"2022-04-18 18:45:00","gmt_time_end_last":"2022-04-18 18:45:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"657249":{"id":"657249","type":"image","title":"Gurinder Kaur and Linzell Harris, AstraZeneca","body":null,"created":"1649867435","gmt_created":"2022-04-13 16:30:35","changed":"1649867817","gmt_changed":"2022-04-13 16:36:57","alt":"Gurinder Kaur and Linzell Harris, AstraZeneca","file":{"fid":"249099","name":"AstraZeneca-mailer3.jpg","image_path":"\/sites\/default\/files\/images\/AstraZeneca-mailer3.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/AstraZeneca-mailer3.jpg","mime":"image\/jpeg","size":136454,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/AstraZeneca-mailer3.jpg?itok=lH6_Queu"}}},"media_ids":["657249"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/astrazeneca-seminar","title":"Register to Attend the Session"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655748":{"#nid":"655748","#data":{"type":"event","title":"Systems Operations and Strategic Interactions in Supply Chains Course (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EOften the lack of cooperation and coordination between organizations or stakeholders lead to inefficiencies, despite having common goals. A systems view is needed to ensure appropriate use of scarce resources to meet the multiple, and often conflicting, short- and long-term goals from multiple constituents. This course will focus on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EWho Should Attend\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EHow You Will Benefit\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIdentify opportunities for coordination within organizations and collaboration across organizations for increased efficiency and improved outcomes.\u003C\/li\u003E\r\n\t\u003Cli\u003EDescribe the strategic behavior of decision-makers and the impact of the market (or contract) structure on the participant\u0026#39;s actions and the overall system dynamics.\u003C\/li\u003E\r\n\t\u003Cli\u003EDefine evaluation metrics in alignment with the system goals and structure system operations and incentives that address and evaluate these metrics.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003EWhat Is Covered\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EHow coordination and collaboration can improve supply chain efficiency and effectiveness\u003C\/li\u003E\r\n\t\u003Cli\u003EHow events, decisions and actions in one part of a system, such as a supply chain, impact other parts of the system\u003C\/li\u003E\r\n\t\u003Cli\u003ESystem-wide inventory variability and costs mitigation and reduction\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation metrics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course will focus on conceptual and modeling skills to understand and effectively manage supply chains and operations from a systems perspective. Models will address system characteristics (e.g., demand dependencies) that drive system dynamics and policies to regulate performance. Course topics include methods for improving coordination and collaboration, addressing demand dependencies, and reliably measuring and evaluating system performance.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore conceptual and modeling skills to understand and effectively manage humanitarian response from a systems perspective."}],"uid":"27233","created_gmt":"2022-02-24 15:09:45","changed_gmt":"2022-03-22 11:38:13","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-05-02T10:30:00-04:00","event_time_end":"2022-05-05T14:00:00-04:00","event_time_end_last":"2022-05-05T14:00:00-04:00","gmt_time_start":"2022-05-02 14:30:00","gmt_time_end":"2022-05-05 18:00:00","gmt_time_end_last":"2022-05-05 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/systems-operations-and-strategic-interactions-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/humso","title":"Course Details via Center for Health and Humanitarian Systems website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:chhs@gatech.edu\u0022\u003Echhs@gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"625085":{"#nid":"625085","#data":{"type":"event","title":"Inventory Management and Resource Allocation in Supply Chains Course (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm EDT each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMany Supply Chain decisions are concerned with the timely and efficient procurement, allocation, and distribution of resources (e.g. funds, supplies, volunteers, money, employees) through a supply chain network. This course will explore methodologies for \u0026ldquo;medium term\u0026rdquo; decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and supply chain design.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EWho Should Attend\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EHow You Will Benefit\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help your organization and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003EWhat Is Covered\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProcurement decisions\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management techniques for a single event versus ongoing operations under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for resource allocation geographically and over time\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course will explore methodologies for tactical decision making including procurement and inventory policies, strategies for distribution and allocation of limited resources, and transportation decisions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Inventory availability is the most important aspect of customer service, and the cost of inventory is one of the most important entries on a company\u0027s balance sheet."}],"uid":"34586","created_gmt":"2019-08-23 17:51:55","changed_gmt":"2022-03-22 11:38:03","author":"jcooper90","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-25T10:30:00-04:00","event_time_end":"2022-04-28T14:00:00-04:00","event_time_end_last":"2022-04-28T14:00:00-04:00","gmt_time_start":"2022-04-25 14:30:00","gmt_time_end":"2022-04-28 18:00:00","gmt_time_end_last":"2022-04-28 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/inventory-management-and-resource-allocation-supply-chains","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/invmgmt","title":"Course Details via Center for Health and Humanitarian Systems website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655746":{"#nid":"655746","#data":{"type":"event","title":"Responsive Supply Chain Design and Operations Course (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003EClasses\u0026nbsp;will be taught by LIVE video instruction similar to the experience you would receive in person with the same interactive components.\u0026nbsp;Each course will run for 1-week Monday through Thursday from 9:30am to 1:00pm ET each day.\u003C\/h3\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMeeting demand in a timely and cost-effective manner is important both in public and private supply chains, and heavily depend on the design and operation of these supply chains. Demand is affected by ongoing factors such as local economy, infrastructure, and geographic location, as well as unexpected events such as natural or manmade disasters or other large-scale disruptions. Designing and operating responsive supply chains requires the consideration of uncertainty in timing, scope, scale, and understanding of various topics such as forecasting, distribution network design, and inventory management. This course will examine methods and models for making supply chain design and operational decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for meeting the need of customers and beneficiaries.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EWho Should Attend\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is designed for representatives from governmental or non-governmental organizations, private corporations, military, and foundations, including but not limited to senior executives overseeing administrative and operational functions of an organization, logistics and supply chain managers, program managers, directors of field operations, directors of emergency\/disaster preparedness and response, and public health professionals.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003EHow You Will Benefit\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProvide immediate impact to your organization through learnings gained from applied and real-world case studies.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn to bring NGOs, businesses, or government entities together to enhance collaboration, cooperation, and communication.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscover current trends and procedures to help organizations and team members get and stay ahead of the curve.\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a critical knowledge base to make tactical decisions around inventory, routing, and distribution.\u003C\/li\u003E\r\n\t\u003Cli\u003EDeliver best practices to measure and evaluate the efficiency, impact, and outcomes of focused initiatives or ongoing logistics and supply chain operations.\u003C\/li\u003E\r\n\t\u003Cli\u003ETransform the health and humanitarian sectors with increased capacity to participate in planning and strategic decision-making for effective supply-chain management.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003EWhat Is Covered\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENetwork modeling approaches\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStrategies for making decisions under uncertainty\u003C\/li\u003E\r\n\t\u003Cli\u003EOther data-driven analytical approaches\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course will examine methods and models for making pre-planning decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for sustaining wellness.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term development"}],"uid":"27233","created_gmt":"2022-02-24 15:01:37","changed_gmt":"2022-03-22 11:37:57","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-11T10:30:00-04:00","event_time_end":"2022-04-14T14:00:00-04:00","event_time_end_last":"2022-04-14T14:00:00-04:00","gmt_time_start":"2022-04-11 14:30:00","gmt_time_end":"2022-04-14 18:00:00","gmt_time_end_last":"2022-04-14 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/responsive-supply-chain-design-and-operations","title":"Registration link via Georgia Tech Professional Education"},{"url":"https:\/\/chhs.gatech.edu\/education\/professional-education\/course\/humpps","title":"Course Details via Center for Health and Humanitarian Systems website"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"8039","name":"Humanitarian"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echhs@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"656329":{"#nid":"656329","#data":{"type":"event","title":"ISyE Seminar Speaker- Alexandre Belloni","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe estimation of causal effects is increasingly relevant in different applied fields. In this work we consider a causal inference problem in the presence of interference. Our focus is on observational studies where interference across units is governed by a known network interference. However, the radius (and intensity) of interference is unknown and can be dependent on the observed treatment assignments in the relevant subnetwork.\u0026nbsp; We study causal estimators for average direct treatment effect given the network interference. The proposed estimators build upon a Lepski-like procedure that searches over the possible relevant radius\/assignment patterns. In the process we also obtain estimators for the radius of the interference that can be dependent on the treatment assignment of neighbors. Thus it is creating an adaptive estimation of the network interference structure. We establish oracle inequalities and corresponding adaptive rates for the direct average treatment effect estimator. The adaptive network interference can be defined over the labelled subgraphs themselves or on features of these recovering many assumptions previously used in the literature.\u0026nbsp; We present theoretical examples and numerical simulation that illustrate the performance of the proposed estimators.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Alexandre Belloni is the John D. Forsyth Professor of Business Administration and Statistical Science at Duke University, and is an Amazon Scholar at SCOT. He received his Ph.D. in Operations Research at MIT and a M.Sc. in Mathematical Economics from IMPA. He was an IBM Herman Goldstein Postdoctoral Fellowship at the IBM Thomas J. Watson Research Center. Professor Belloni\u0026rsquo;s research interests are on machine learning and statistics, mechanism design (e.g. contracts\/auctions), optimization and on their applications. His works appeared at top journals in Economics, Operations Research, and Statistics. He serves as Associate Editor to Annals of Statistics, Management Science and as the Area Editor to Operations Research (Machine Learning and Data Science).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E The estimation of causal effects is increasingly relevant in different applied fields. In this work we consider a causal inference problem in the presence of interference. Our focus is on observational studies where interference across units is governed by a known network interference. However, the radius (and intensity) of interference is unknown and can be dependent on the observed treatment assignments in the relevant subnetwork.\u0026nbsp; We study causal estimators for average direct treatment effect given the network interference. The proposed estimators build upon a Lepski-like procedure that searches over the possible relevant radius\/assignment patterns. In the process we also obtain estimators for the radius of the interference that can be dependent on the treatment assignment of neighbors. Thus it is creating an adaptive estimation of the network interference structure. We establish oracle inequalities and corresponding adaptive rates for the direct average treatment effect estimator. The adaptive network interference can be defined over the labelled subgraphs themselves or on features of these recovering many assumptions previously used in the literature.\u0026nbsp; We present theoretical examples and numerical simulation that illustrate the performance of the proposed estimators.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Alexandre Belloni is the John D. Forsyth Professor of Business Administration and Statistical Science at Duke University, and is an Amazon Scholar at SCOT. He received his Ph.D. in Operations Research at MIT and a M.Sc. in Mathematical Economics from IMPA. He was an IBM Herman Goldstein Postdoctoral Fellowship at the IBM Thomas J. Watson Research Center. Professor Belloni\u0026rsquo;s research interests are on machine learning and statistics, mechanism design (e.g. contracts\/auctions), optimization and on their applications. His works appeared at top journals in Economics, Operations Research, and Statistics. He serves as Associate Editor to Annals of Statistics, Management Science and as the Area Editor to Operations Research (Machine Learning and Data Science).\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Adaptive (interference) estimator for causal inference under network interference"}],"uid":"36086","created_gmt":"2022-03-14 17:27:48","changed_gmt":"2022-03-14 17:27:48","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-22T12:00:00-04:00","event_time_end":"2022-04-22T13:00:00-04:00","event_time_end_last":"2022-04-22T13:00:00-04:00","gmt_time_start":"2022-04-22 16:00:00","gmt_time_end":"2022-04-22 17:00:00","gmt_time_end_last":"2022-04-22 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"656306":{"#nid":"656306","#data":{"type":"event","title":"ISyE Seminar Speaker -Sanjay Mehrotra ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003EWe study a service center location problem with ambiguous utility gains and uncertain demand. The model is motivated by the problem of deciding medical clinic\/service centers, possibly in rural communities, where residents need to visit the clinics to receive health services. A resident gains his utility based on service features such as travel distance and waiting time at the facility that depend on the clinic location. The elicited location-dependent utilities are assumed to be ambiguously described by an expected value and variance constraint. We show that despite a non-convex nonlinearity, given by a constraint specified by a maximum of two second-order functions, the model admits a mixed 0-1 second-order cone (MISOCP) formulation, which leads to a two-stage-MISOCP under uncertain demand. We study the non-convex substructure of the problem, and present methods for developing its strengthened formulations by using valid tangent inequalities. We also develop a new branch-and-cut algorithm for the two-stage-MISOCP problem. Computational study shows the effectiveness of solving the strengthened formulations. Examples are used to illustrate the importance of including decision dependent ambiguity.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBiography:\u003C\/strong\u003E\u0026nbsp;Sanjay Mehrotra is a Professor of Industrial Engineering and Management Sciences at Northwestern University. He is a Fellow of the Institute for Operations Research and Management Sciences (INFORMS), and the cohort leader of 2022 INFORMS Fellow Selection Committee. He is the founding director of the Center for Engineering and Health, which is a part of the Institute for Public Health and Medicine at Northwestern University. He is an expert in methodologies for decision making under uncertainty, and its applications to problems in Health Systems Engineering. He has made major contributions to the areas of Optimization Algorithms and Health Systems Engineering, for which he is known internationally.\u0026nbsp;\u0026nbsp;Professor Mehrotra\u0026rsquo;s current methodology research is focused on robust decision making. His health systems engineering work encompasses a wide range of topics that include predictive modeling, hospital operations modeling, and policy modeling while using and developing modern operations research tools. Professor Mehrotra has made seminal contributions to the liver and kidney distribution modeling towards reducing geographic disparity. His current healthcare systems engineering research is focusing on reducing kidney discards, improving the understanding of liver cirrhosis, and developing scalable systems for infectious disease management, and patient centered care. He has been the department editor for the Optimization department and Health Systems Engineering department for the journal IIE-Transactions. He is also the founding co-Editor of Healthcare section for the journal Naval Research Logistics. In the Optimization area Mehrotra is widely known for his predictor-corrector method for solving continuous optimization problems. He has been INFORMS Optimization Society chair and has also served on INFORMS Board of Directors. His research has been funded by NIDDK, NIA, NIBIB, NSF, ONR and DOE.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003EWe study a service center location problem with ambiguous utility gains and uncertain demand. The model is motivated by the problem of deciding medical clinic\/service centers, possibly in rural communities, where residents need to visit the clinics to receive health services. A resident gains his utility based on service features such as travel distance and waiting time at the facility that depend on the clinic location. The elicited location-dependent utilities are assumed to be ambiguously described by an expected value and variance constraint. We show that despite a non-convex nonlinearity, given by a constraint specified by a maximum of two second-order functions, the model admits a mixed 0-1 second-order cone (MISOCP) formulation, which leads to a two-stage-MISOCP under uncertain demand. We study the non-convex substructure of the problem, and present methods for developing its strengthened formulations by using valid tangent inequalities. We also develop a new branch-and-cut algorithm for the two-stage-MISOCP problem. Computational study shows the effectiveness of solving the strengthened formulations. Examples are used to illustrate the importance of including decision dependent ambiguity.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBiography:\u003C\/strong\u003E\u0026nbsp;Sanjay Mehrotra is a Professor of Industrial Engineering and Management Sciences at Northwestern University. He is a Fellow of the Institute for Operations Research and Management Sciences (INFORMS), and the cohort leader of 2022 INFORMS Fellow Selection Committee. He is the founding director of the Center for Engineering and Health, which is a part of the Institute for Public Health and Medicine at Northwestern University. He is an expert in methodologies for decision making under uncertainty, and its applications to problems in Health Systems Engineering. He has made major contributions to the areas of Optimization Algorithms and Health Systems Engineering, for which he is known internationally.\u0026nbsp;\u0026nbsp;Professor Mehrotra\u0026rsquo;s current methodology research is focused on robust decision making. His health systems engineering work encompasses a wide range of topics that include predictive modeling, hospital operations modeling, and policy modeling while using and developing modern operations research tools. Professor Mehrotra has made seminal contributions to the liver and kidney distribution modeling towards reducing geographic disparity. His current healthcare systems engineering research is focusing on reducing kidney discards, improving the understanding of liver cirrhosis, and developing scalable systems for infectious disease management, and patient centered care. He has been the department editor for the Optimization department and Health Systems Engineering department for the journal IIE-Transactions. He is also the founding co-Editor of Healthcare section for the journal Naval Research Logistics. In the Optimization area Mehrotra is widely known for his predictor-corrector method for solving continuous optimization problems. He has been INFORMS Optimization Society chair and has also served on INFORMS Board of Directors. His research has been funded by NIDDK, NIA, NIBIB, NSF, ONR and DOE.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Locating Service Centers with Decision Dependent Utility and Two-Stage Mixed Integer Conic Optimization"}],"uid":"36086","created_gmt":"2022-03-14 12:35:39","changed_gmt":"2022-03-14 12:35:39","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-18T12:00:00-04:00","event_time_end":"2022-03-18T13:00:00-04:00","event_time_end_last":"2022-03-18T13:00:00-04:00","gmt_time_start":"2022-03-18 16:00:00","gmt_time_end":"2022-03-18 17:00:00","gmt_time_end_last":"2022-03-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"656305":{"#nid":"656305","#data":{"type":"event","title":"ISyE Seminar Speaker-Folashade B. Agusto","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECOVID-19 is a respiratory disease caused by a recently discovered, novel coronavirus, SARS-COV2. The disease has led to over 455 million cases, with over 6 million deaths worldwide. In any pandemic, the risk of infection is driven by people\u0026#39;s perception of risk of the infection. A number of factors drive public perception of disease risk, these include peoples\u0026rsquo; beliefs, knowledge, and information about a disease. In this seminar, I will present two different models for COVID-19 that explore peoples\u0026#39; behavior and their sentiments about the disease in the early period of the pandemic.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the first model I use game theory and appropriate payoff\u2000functions relating to the perception of risk measured using disease incidence and severity of infection to account for a series of human behaviors. Which leads to a complex interplay between the epidemiological model, that affects success of different strategies, and the game-theoretic behavioral model, which in turn affects the spread of the disease. In the second model I use tweets from Twitter to account for peoples\u0026#39; sentiments about the disease. It also takes into account negative sentiments driven by misinformation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe results from these models shows that rational behavior of susceptible individuals can lead to multiple waves of infections; these multiple waves are possible if the rate of social learning of infected individuals is sufficiently high. To reduce the burden of the disease in the community, it is necessary to ensure positive sentiments and feelings, and to incentivize altruistic behavior by infected individuals such as voluntary self-isolation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E \u0026nbsp;I\u0026#39;m a trained applied mathematician based in the department of Ecology and Evolutionary Biology at the University of Kansas.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI received\u0026nbsp;my PhD. in Mathematics from the University of Ilorin in Nigeria.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMy work focuses on designing novel models to gain insight on the emergence and re-emergence of infectious diseases of public health importance and how to mitigate the risks they pose to human health.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI\u0026#39;ve\u0026nbsp;designed and analyzed novel models for diseases like Ebola, avian influenza, bovine tuberculosis, Johnes disease, toxplasmagondii, Chikungunya, and malaria. My current works are on modeling tick-borne disease across the Great Plains and understanding the role of human behavior on the transmission of COVID-19.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI\u0026#39;m also involved in capacity building across West Africa by organizing summer schools in mathematical epidemiology and ecology. I have organized summer schools in Benin, Senegal, and Nigeria, and currently seeking funds for a school in Ghana for 2022 Summer.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECOVID-19 is a respiratory disease caused by a recently discovered, novel coronavirus, SARS-COV2. The disease has led to over 455 million cases, with over 6 million deaths worldwide. In any pandemic, the risk of infection is driven by people\u0026#39;s perception of risk of the infection. A number of factors drive public perception of disease risk, these include peoples\u0026rsquo; beliefs, knowledge, and information about a disease. In this seminar, I will present two different models for COVID-19 that explore peoples\u0026#39; behavior and their sentiments about the disease in the early period of the pandemic.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the first model I use game theory and appropriate payoff\u2000functions relating to the perception of risk measured using disease incidence and severity of infection to account for a series of human behaviors. Which leads to a complex interplay between the epidemiological model, that affects success of different strategies, and the game-theoretic behavioral model, which in turn affects the spread of the disease. In the second model I use tweets from Twitter to account for peoples\u0026#39; sentiments about the disease. It also takes into account negative sentiments driven by misinformation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe results from these models shows that rational behavior of susceptible individuals can lead to multiple waves of infections; these multiple waves are possible if the rate of social learning of infected individuals is sufficiently high. To reduce the burden of the disease in the community, it is necessary to ensure positive sentiments and feelings, and to incentivize altruistic behavior by infected individuals such as voluntary self-isolation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E \u0026nbsp;I\u0026#39;m a trained applied mathematician based in the department of Ecology and Evolutionary Biology at the University of Kansas.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI received\u0026nbsp;my PhD. in Mathematics from the University of Ilorin in Nigeria.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMy work focuses on designing novel models to gain insight on the emergence and re-emergence of infectious diseases of public health importance and how to mitigate the risks they pose to human health.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI have designed and analyzed novel models for diseases like Ebola, avian influenza, bovine tuberculosis, Johnes disease, toxplasmagondii, Chikungunya, and malaria. My current works are on modeling tick-borne disease across the Great Plains and understanding the role of human behavior on the transmission of COVID-19.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EI\u0026#39;m also involved in capacity building across West Africa by organizing summer schools in mathematical epidemiology and ecology. I have organized summer schools in Benin, Senegal, and Nigeria, and currently seeking funds for a school in Ghana for 2022 Summer.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The impact of changing behavior, and sentiments on COVID-19 transmission"}],"uid":"36086","created_gmt":"2022-03-14 12:21:22","changed_gmt":"2022-03-14 12:21:22","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-15T12:00:00-04:00","event_time_end":"2022-04-15T13:00:00-04:00","event_time_end_last":"2022-04-15T13:00:00-04:00","gmt_time_start":"2022-04-15 16:00:00","gmt_time_end":"2022-04-15 17:00:00","gmt_time_end_last":"2022-04-15 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"656118":{"#nid":"656118","#data":{"type":"event","title":"ISyE Department Seminar-Meisam Razaviyayn","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u0026ldquo;Solving\u0026rdquo; a class of nonconvx min-max optimization problems\u0026quot;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Recent applications that arise in machine learning have surged significant interest in solving min-max optimization problems. This problem has been extensively studied in the convex-concave regime for which a globally optimal solution can be computed efficiently. In the nonconvex regime, on the other hand, most problems cannot be solved to any reasonable notion of stationarity. In this talk, we present different classes of smooth nonconvex min-max problems that can be solved efficiently up to first-order stationarity of its Moreau envelope. In particular, we propose efficient algorithms for finding (first-order) stationary solutions to nonconvex min-max problems classes when the inner maximization problem is concave or when the diameter of the constraint set for the inner maximization problem is \u0026quot;small\u0026quot;. We also discuss the validity of our assumptions in various applications and evaluate the performance of our algorithms on different applications including training adversarial\u0026nbsp;robust neural networks, fair machine learning, data imputation, and training generative adversarial networks.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Meisam Razaviyayn is an assistant professor of Industrial and Systems Engineering, Electrical Engineering, and Computer Science at the University of Southern California. His research interests include the design and analysis of optimization algorithms for modern problems arising in machine learning applications. His contributions to the field of optimization were recognized through awards such as Signal Processing Society Young Author Best PaperAward, ICCM Best Paper Award in Mathematics, IEEE Data Science Workshop Best Paper Award, and the 3M NTFA award, and AFOSR Young Investigator Prize.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERecent applications that arise in machine learning have surged significant interest in solving min-max optimization problems. This problem has been extensively studied in the convex-concave regime for which a globally optimal solution can be computed efficiently. In the nonconvex regime, on the other hand, most problems cannot be solved to any reasonable notion of stationarity. In this talk, we present different classes of smooth nonconvex min-max problems that can be solved efficiently up to first-order stationarity of its Moreau envelope. In particular, we propose efficient algorithms for finding (first-order) stationary solutions to nonconvex min-max problems classes when the inner maximization problem is concave or when the diameter of the constraint set for the inner maximization problem is \u0026quot;small\u0026quot;. We also discuss the validity of our assumptions in various applications and evaluate the performance of our algorithms on different applications including training adversarial\u0026nbsp;robust neural networks, fair machine learning, data imputation, and training generative adversarial networks.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMeisam Razaviyayn is an assistant professor of Industrial and Systems Engineering, Electrical Engineering, and Computer Science at the University of Southern California. His research interests include the design and analysis of optimization algorithms for modern problems arising in machine learning applications. His contributions to the field of optimization were recognized through awards such as Signal Processing Society Young Author Best PaperAward, ICCM Best Paper Award in Mathematics, IEEE Data Science Workshop Best Paper Award, and the 3M NTFA award, and AFOSR Young Investigator Prize.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"\u201cSolving\u201d a class of nonconvx min-max optimization problems\u0022 "}],"uid":"36086","created_gmt":"2022-03-08 16:27:37","changed_gmt":"2022-03-11 22:15:02","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-16T15:00:00-04:00","event_time_end":"2022-03-16T16:00:00-04:00","event_time_end_last":"2022-03-16T16:00:00-04:00","gmt_time_start":"2022-03-16 19:00:00","gmt_time_end":"2022-03-16 20:00:00","gmt_time_end_last":"2022-03-16 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"656225":{"#nid":"656225","#data":{"type":"event","title":"ISyE Seminar Speaker-Oktay Gunluk ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E. We consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints. We formulate the problem as an integer program that maximizes classification accuracy with explicit constraints on equality of opportunity and equalized odds metrics. A column generation framework is used to efficiently search over exponentially many possible rules, eliminating the need for heuristic rule mining. Compared to other interpretable machine learning algorithms, our method produces interpretable classifiers that have superior performance with respect to the fairness metric.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Connor Lawless\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u0026nbsp;Oktay\u0026nbsp;Gunluk joined the School of Operations Research and Information Engineering faculty in January 2020. Before joining Cornell, he was the manager of the Mathematical Optimization and Algorithms group at IBM Research. He has also spent three years as a researcher in the Operations Research group in AT\u0026amp;T Labs. At both of these industrial labs, in addition to basic research in mathematical optimization, he has worked on various large-scale applied optimization projects for internal and external customers. His main research interests are related to theoretical and computational aspects of discrete optimization problems, mainly in the area of integer programing. In particular, his main body of work is in the area of cutting planes for mixed-integer sets. Some of his recent work focuses on developing integer programming-based approaches to classification problems in machine learning. He has B.S.\/M.S. degrees in Industrial Engineering from Bo\u011fazi\u0026ccedil;i University, and M.S.\/Ph.D. degrees in Operations Research) from Columbia University.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E. We consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints. We formulate the problem as an integer program that maximizes classification accuracy with explicit constraints on equality of opportunity and equalized odds metrics. A column generation framework is used to efficiently search over exponentially many possible rules, eliminating the need for heuristic rule mining. Compared to other interpretable machine learning algorithms, our method produces interpretable classifiers that have superior performance with respect to the fairness metric.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Connor Lawless.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u0026nbsp;Oktay\u0026nbsp;Gunluk joined the School of Operations Research and Information Engineering faculty in January 2020. Before joining Cornell, he was the manager of the Mathematical Optimization and Algorithms group at IBM Research. He has also spent three years as a researcher in the Operations Research group in AT\u0026amp;T Labs. At both of these industrial labs, in addition to basic research in mathematical optimization, he has worked on various large-scale applied optimization projects for internal and external customers. His main research interests are related to theoretical and computational aspects of discrete optimization problems, mainly in the area of integer programing. In particular, his main body of work is in the area of cutting planes for mixed-integer sets. Some of his recent work focuses on developing integer programming-based approaches to classification problems in machine learning. He has B.S.\/M.S. degrees in Industrial Engineering from Bo\u011fazi\u0026ccedil;i University, and M.S.\/Ph.D. degrees in Operations Research) from Columbia University.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"An integer programming approach for Fair and Interpretable Binary Classification"}],"uid":"36086","created_gmt":"2022-03-10 18:58:28","changed_gmt":"2022-03-10 18:58:28","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-08T12:00:00-04:00","event_time_end":"2022-04-08T13:00:00-04:00","event_time_end_last":"2022-04-08T13:00:00-04:00","gmt_time_start":"2022-04-08 16:00:00","gmt_time_end":"2022-04-08 17:00:00","gmt_time_end_last":"2022-04-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"656210":{"#nid":"656210","#data":{"type":"event","title":"ISyE Department Seminar- Itai Gurvich","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E We consider centralized dynamic matching markets with finitely many agent types and heterogeneous match values. A network topology determines the feasible matches in the market and the value generated from each match. An inherent trade-off arises between short- and long-term objectives. A social planner may delay match decisions to thicken the market and increase match opportunities to generate high value. This inevitably compromises short-term value, and the planner may match greedily to maximize short-term objectives.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA matching policy is hindsight optimal if the policy can (nearly) maximize the total value simultaneously at all times. We first establish that in multi-way networks, where a match can include more than two agent types, acting greedily is suboptimal, and a periodic clearing policy with a carefully chosen period length is hindsight optimal. Interestingly, in two-way networks, where any match includes two agent types, suitably designed greedy policies also achieve hindsight optimality. This implies that there is essentially no positive externality from having agents waiting to form future matches.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECentral to our results is the general position gap, \u0026epsilon;, which quantifies the stability or the imbalance in the network. No policy can achieve a regret that is lower than the order of 1\/\u0026epsilon; at all times. This lower bound is achieved by the proposed policies.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe talk is based on joint work with Suleyman Kerimov and Itai Ashlagi.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E We consider centralized dynamic matching markets with finitely many agent types and heterogeneous match values. A network topology determines the feasible matches in the market and the value generated from each match. An inherent trade-off arises between short- and long-term objectives. A social planner may delay match decisions to thicken the market and increase match opportunities to generate high value. This inevitably compromises short-term value, and the planner may match greedily to maximize short-term objectives.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA matching policy is hindsight optimal if the policy can (nearly) maximize the total value simultaneously at all times. We first establish that in multi-way networks, where a match can include more than two agent types, acting greedily is suboptimal, and a periodic clearing policy with a carefully chosen period length is hindsight optimal. Interestingly, in two-way networks, where any match includes two agent types, suitably designed greedy policies also achieve hindsight optimality. This implies that there is essentially no positive externality from having agents waiting to form future matches.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECentral to our results is the general position gap, \u0026epsilon;, which quantifies the stability or the imbalance in the network. No policy can achieve a regret that is lower than the order of 1\/\u0026epsilon; at all times. This lower bound is achieved by the proposed policies.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe talk is based on joint work with Suleyman Kerimov and Itai Ashlagi.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Near-Optimal Policies for Dynamic Matching"}],"uid":"36086","created_gmt":"2022-03-10 13:31:42","changed_gmt":"2022-03-10 16:26:34","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-01T12:00:00-04:00","event_time_end":"2022-04-01T13:00:00-04:00","event_time_end_last":"2022-04-01T13:00:00-04:00","gmt_time_start":"2022-04-01 16:00:00","gmt_time_end":"2022-04-01 17:00:00","gmt_time_end_last":"2022-04-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"645562":{"#nid":"645562","#data":{"type":"event","title":"SCL Course: Transforming Supply Chain Management and Performance Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the first in the four-course Supply Chain Analytics Professional certificate program. It prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. You\u0026rsquo;ll learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u0026rsquo;ll learn about data cleansing, exploratory data analysis, and visualization. You\u0026rsquo;ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day instructor-led LIVE group webinars (February 14, 15, 16, 17 | 1-5pm ET) and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the most relevant planning challenges across the strategic, tactical, and operational levels of supply chains\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the difference between analytics types, the links between them, and how to best use them to improve\u0026nbsp;supply chain management (SCM)\u0026nbsp;processes\u003C\/li\u003E\r\n\t\u003Cli\u003EUse\u0026nbsp;Key Performance Indicators (KPIs)\u0026nbsp;to find causes of underperformance in supply chains and to plan for analytics projects that will address strategic SCM goals\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to understand, visualize, and analyze data in order to prepare for deeper analytics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe role of analytics in SCM\u003C\/li\u003E\r\n\t\u003Cli\u003ETypes of analytics (descriptive, diagnostic, predictive, and prescriptive) and the relationships between them\u003C\/li\u003E\r\n\t\u003Cli\u003EPreprocessing (cleaning and integrating) data as it relates to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EConducting exploratory data analysis on supply chain data\u003C\/li\u003E\r\n\t\u003Cli\u003EBest practices for visualizing data and building dashboards\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentifying and analyzing KPIs of SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u0026rsquo;ll learn about data cleansing, exploratory data analysis, and visualization. You\u0026rsquo;ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to apply leading-edge analytical methods and technology enablers across the supply chain"}],"uid":"27233","created_gmt":"2021-03-19 19:51:48","changed_gmt":"2022-03-02 13:41:51","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-18T14:00:00-04:00","event_time_end":"2022-04-21T18:00:00-04:00","event_time_end_last":"2022-04-21T18:00:00-04:00","gmt_time_start":"2022-04-18 18:00:00","gmt_time_end":"2022-04-21 22:00:00","gmt_time_end_last":"2022-04-21 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scapa","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655002":{"#nid":"655002","#data":{"type":"event","title":"SCL Course: Business Case Development for Operations and Supply Chain Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe ability to write a compelling business case is a core competency for effective leaders. A business case is a critical requirement before committing to projects, new products or other investments. It is also an argument that needs to convince the recipient to invest in this undertaking rather than others. Rigorous business case preparation reduces the risk of poorly targeted or poorly executed projects, improves strategic alignment of investments and increases the probability of achieving expected returns\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis course equips participants with the necessary skills and tools to develop structured business cases. Presented techniques are field-proven and derived from successful implementation. Case exercises are adapted from real situations and projects.\u0026nbsp;\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ESupply Chain, Finance, Marketing and Sales Executives (Managers, Directors, VPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ETransportation, Logistics, and Facility Planners, Managers, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESystems, Project, and Program Managers\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop business cases with a clearer understanding of senior leadership and management expectations\u003C\/li\u003E\r\n\t\u003Cli\u003ETarget investments with reduced risk and improved strategic alignment\u003C\/li\u003E\r\n\t\u003Cli\u003EApply industry best practice steps for developing a business case that explains rationale to senior managers within organizations\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the purpose and content of a business case as it applies in different contexts\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop structured business cases for initiatives within OSM.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the business case process and how to logically address it\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify, develop, and evaluate alternative options and decision paths\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelop strong, multi-dimensional and objective-driven submissions that drive consistent rates of approval and are presented in an appropriate format\u003C\/li\u003E\r\n\t\u003Cli\u003EQuantify the various benefits of undertaking a project or task and interpret the appropriate financial data including costs, budgets and estimates for completion\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe ability to write a compelling business case is a core competency for effective leaders. A business case is a critical requirement before committing to projects, new products or other investments. It is also an argument that needs to convince the recipient to invest in this undertaking rather than others. Rigorous business case preparation reduces the risk of poorly targeted or poorly executed projects, improves strategic alignment of investments and increases the probability of achieving expected returns\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis course equips participants with the necessary skills and tools to develop structured business cases. Presented techniques are field-proven and derived from successful implementation. Case exercises are adapted from real situations and projects.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course equips participants with the necessary skills and tools to develop structured business cases."}],"uid":"27233","created_gmt":"2022-01-31 19:13:47","changed_gmt":"2022-02-24 16:23:23","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-10-26T09:00:00-04:00","event_time_end":"2022-10-27T18:00:00-04:00","event_time_end_last":"2022-10-27T18:00:00-04:00","gmt_time_start":"2022-10-26 13:00:00","gmt_time_end":"2022-10-27 22:00:00","gmt_time_end_last":"2022-10-27 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/bcd","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655468":{"#nid":"655468","#data":{"type":"event","title":"SCL Course: Contracting and Legal Oversight (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EContracting and Legal Oversight provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents. The program is geared to reinforce standards of excellence for professionals who are responsible for delivering contractual agreements and mitigating financial risk for their organization.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (3) instructor-led LIVE group webinars, homework, and pre-work (e.g. installing and testing software on your computer, testing connectivity with Canvas LMS and BlueJeans meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for contract managers, procurement professionals, sourcing initiative leaders, project managers and all procurement \u0026amp; supply management-related professionals involved with bid contract development, contract execution or supplier performance management.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base in law of agency concepts to gain more confidence with contracting.\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of industry standard contract types and contract terms for more robust contract agreements.\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage sourcing category knowledge to modify existing contract elements for more holistic contract agreements.\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove internal contract execution communication for better results.\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten sense of executive financial impact and risk needs to gain leadership early support.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELaw of Agency Overview\u003C\/li\u003E\r\n\t\u003Cli\u003EContract Agreement Types\u003C\/li\u003E\r\n\t\u003Cli\u003EDefining Key Terms\u003C\/li\u003E\r\n\t\u003Cli\u003EContract Structure \u0026amp; Drafting\u003C\/li\u003E\r\n\t\u003Cli\u003ERisk Mitigation \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents. The program is geared to reinforce standards of excellence for professionals who are responsible for delivering contractual agreements and mitigating financial risk for their organization.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course provides participants with a holistic and integrated understanding of contract law, contract types, key industry standard contract terms, and contract structure to improve their confidence when creating or modifying contract documents."}],"uid":"27233","created_gmt":"2022-02-14 22:04:32","changed_gmt":"2022-02-24 16:22:08","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-15T16:00:00-04:00","event_time_end":"2022-09-21T18:00:00-04:00","event_time_end_last":"2022-09-21T18:00:00-04:00","gmt_time_start":"2022-09-15 20:00:00","gmt_time_end":"2022-09-21 22:00:00","gmt_time_end_last":"2022-09-21 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/clo","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655469":{"#nid":"655469","#data":{"type":"event","title":"SCL Course: Essentials of Negotiations and Stakeholder Influence (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEssentials of Negotiations and Stakeholder Influence level-sets the participants\u0026#39; understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u0026ldquo;DNA\u0026rdquo; to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u0026ldquo;no judgement zone\u0026rdquo; environment.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, project leaders, business unit leaders, operations managers, sales leaders and procurement \u0026amp; supply management-related professionals who are involved with supplier selection, contract development and supplier performance management.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease emphasis negotiation conditioning and philosophy setting before and throughout the entire sourcing engagement process\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance your toolbox of industry standard negotiation prep tools like the SWOT and BATNA\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter prepare for negotiations by leveraging knowledge of key negotiation terms and counter-offer tactics\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove negotiation table techniques and soft skills to direct and redirect negotiation momentum\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten ability to successfully utilize your traditional \u0026quot;comfort zone\u0026quot; approach in combination with your negotiation team\u0026rsquo;s strengths by leveraging Personal Negotiation Styles\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ENegotiation Conditioning Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Preparation Tools\u003C\/li\u003E\r\n\t\u003Cli\u003ENegotiation Execution Techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EStakeholder Engagement \u0026amp; Team Leadership\u003C\/li\u003E\r\n\t\u003Cli\u003ELive Negotiations Simulation \u0026amp; Feedback\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;level-sets the participants\u0026#39; understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations. The program includes industry techniques and tools for traditional supplier negotiations, as well as tips for internal cross-functional leadership. Participants walk away with a standard industry and customized individual experience which includes their personal Negotiation Style \u0026ldquo;DNA\u0026rdquo; to help them embrace their own natural tendencies and strengths. The program includes mock negotiations to reinforce techniques and tactics immediately in a \u0026ldquo;no judgement zone\u0026rdquo; environment.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Level-sets the participants\u0027 understanding of negotiation influence and strengthens preparation, planning and execution activities involved with both simple and complex negotiations."}],"uid":"27233","created_gmt":"2022-02-14 22:11:00","changed_gmt":"2022-02-24 16:21:51","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-22T14:00:00-04:00","event_time_end":"2022-09-29T17:59:00-04:00","event_time_end_last":"2022-09-29T17:59:00-04:00","gmt_time_start":"2022-09-22 18:00:00","gmt_time_end":"2022-09-29 21:59:00","gmt_time_end_last":"2022-09-29 21:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/epn","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655467":{"#nid":"655467","#data":{"type":"event","title":"SCL Course: Category Management and Sourcing Leadership (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECategory Management and Sourcing Leadership is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, procurement professionals, project managers, finance analyst, contract managers and all procurement \u0026amp; supply management-related professionals involved with bid package development, bid package analysis, negotiations preparation, contracting and supplier selection activity.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base of solicitation options (i.e. RFI, RFP, RFQ) and which solicitation approach to apply based on your organization\u0026#39;s needs\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of sourcing process and critical steps in the Bid Package development and delivery activities\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage and utilization of solicitation tools to drive successful development of bid packages\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove set up and execution of supplier selection scorecards to aid in identifying best Total Cost of Ownership alternatives\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten understanding of executive communication to leverage leadership support throughout the organization\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBid Package Development Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ESourcing Initiative Process Roadmap\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EMarketplace Analysis Tools\u003C\/li\u003E\r\n\t\u003Cli\u003EBid Package Alternatives \u0026amp; Design\u003C\/li\u003E\r\n\t\u003Cli\u003ESupplier Selection \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026 supply management function."}],"uid":"27233","created_gmt":"2022-02-14 21:55:45","changed_gmt":"2022-02-24 16:19:11","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-09-12T14:00:00-04:00","event_time_end":"2022-09-15T15:30:00-04:00","event_time_end_last":"2022-09-15T15:30:00-04:00","gmt_time_start":"2022-09-12 18:00:00","gmt_time_end":"2022-09-15 19:30:00","gmt_time_end_last":"2022-09-15 19:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/cmsl","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EEMAIL: \u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E or CALL: (404) 385-3501 between 9:00a.m. and 4:00p.m., Eastern time.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"650961":{"#nid":"650961","#data":{"type":"event","title":"SCL Course: Principles of Transportation Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003E\u003Cstrong\u003ECOURSE DESCRIPTION\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course prepares students in the basics of transportation operations and analysis. \u0026nbsp;The course includes review of the key elements of transportation such as: modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms. \u0026nbsp;The course also will discuss emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWHO SHOULD ATTEND\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course is designed for Supply Chain Managers, Distribution Managers, Transportation Planners, Transportation Clerks, Transportation Analysts, and Transportation Managers and learners seeking to enter these roles. \u0026nbsp;Supply chain professionals from other domains will also benefit through gaining insights into transportation operations.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EHOW YOU WILL BENEFIT\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the characteristics and best use of specific transportation modes\u003C\/li\u003E\r\n\t\u003Cli\u003EApply transportation cost analysis techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the multimodal role of ports in global trade\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify and apply best practices in transportation procurement\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how to minimize transportation costs through consolidation techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the role of Incoterms in global trade\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand emerging techniques in logistics including techniques to reduce greenhouse gas emissions in logistics\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWHAT IS COVERED\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EComparison of characteristics of alternative transportation modes\u003C\/li\u003E\r\n\t\u003Cli\u003EComponents of Port Logistics systems\u003C\/li\u003E\r\n\t\u003Cli\u003EBest practices in transportation procurement\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of practical transportation cost analysis techniques\u003C\/li\u003E\r\n\t\u003Cli\u003EINCOTERMS purpose, types, and use\u003C\/li\u003E\r\n\t\u003Cli\u003EGreenhouse gas emission generation in logistics and mitigation strategies\u003C\/li\u003E\r\n\t\u003Cli\u003ENew business models in logistics enabled by emerging technologies\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course prepares students in the basics of transportation operations and analysis. \u0026nbsp;The course includes review of the key elements of transportation such as: modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms. \u0026nbsp;The course also will discuss emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course prepares students in the basics of transportation operations and analysis."}],"uid":"27233","created_gmt":"2021-09-21 17:15:09","changed_gmt":"2022-02-24 16:08:32","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-06-21T09:00:00-04:00","event_time_end":"2022-06-23T17:59:00-04:00","event_time_end_last":"2022-06-23T17:59:00-04:00","gmt_time_start":"2022-06-21 13:00:00","gmt_time_end":"2022-06-23 21:59:00","gmt_time_end_last":"2022-06-23 21:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/ptm","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"3843","name":"distribution"},{"id":"168044","name":"sourcing"},{"id":"168","name":"Transportation"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"650274":{"#nid":"650274","#data":{"type":"event","title":"SCL Course: Supply Chain Project Management Vendor Selection \u0026 Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ETo keep pace with the continuous moves toward outsourcing of operations and the advancement of technology, companies need to focus on selecting the right suppliers and partnerships to provide the most value to their customers and to remain profitable. This course provides a deeper understanding of the Project Management Body of Knowledge (PMBOK) areas of project integration and procurement, as applied to the supply-chain vendor-selection and management process. You will gain the knowledge, skills, and tools to ensure that you are selecting the right supply-chain partners based on your business goals. In addition, you will learn about alternative techniques for supplier selection, including applied quantitative decision-making techniques.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the supply-chain solution provider landscape and types of systems available on the market.\u003C\/li\u003E\r\n\t\u003Cli\u003EEnsure stakeholder alignment through the supply-chain project lifecycle.\u003C\/li\u003E\r\n\t\u003Cli\u003EKnow the best practices when selecting the right partners based on the PMBOK project.\u003C\/li\u003E\r\n\t\u003Cli\u003EMonitor and measure vendor performance as part of the selection process.\u003C\/li\u003E\r\n\t\u003Cli\u003EDiscuss the legal and ethical considerations for vendor selection.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReview of PMPBOK Focus Areas for the Course\u003C\/li\u003E\r\n\t\u003Cli\u003EOverview of Managing a Supply Chain Selection Project\u003C\/li\u003E\r\n\t\u003Cli\u003EThe Role of Benchmarking in Evaluating and Selecting Solutions\u003C\/li\u003E\r\n\t\u003Cli\u003EOverview of the Third Party Logistics Provider Market\u003C\/li\u003E\r\n\t\u003Cli\u003EOverview of Supply Chain Solution Providers (WMS, TMS, OMS, ERP, etc.)\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluating Cloud vs. On-Premise Solutions and Pricing Models\u003C\/li\u003E\r\n\t\u003Cli\u003EManaging the Requirements Planning \u0026amp; Stakeholder Interview Process\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstanding RFP, RFI, and RFQ\u003C\/li\u003E\r\n\t\u003Cli\u003EPlanning the Solution Evaluation and RFP Process\u003C\/li\u003E\r\n\t\u003Cli\u003EManaging the RFP Process\u003C\/li\u003E\r\n\t\u003Cli\u003EDefining Vendor Requirements\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of Decision Theory and Matrices in Driving Consensus\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Vendor Selection Best Practices\u003C\/li\u003E\r\n\t\u003Cli\u003ECommon Pitfalls in Supply Chain Vendor Selection \u0026amp; Management\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Selection Best Practices\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of Decision Theory and Matrices in Driving Consensus\u003C\/li\u003E\r\n\t\u003Cli\u003EContract Administration \u0026amp; Management\u003C\/li\u003E\r\n\t\u003Cli\u003ELegal \u0026amp; Ethical Vendor Management\/Project Considerations\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course provides a deeper understanding of the PMBOK knowledge areas of project integration and procurement applied in the supply chain vendor selection and management process. To keep pace with the continuous moves toward outsourcing of operations and the advancement of technology, companies need to focus on selecting the right suppliers and partnerships to provide the most value to their customers and to remain profitable. This course provides the knowledge, skills, and tools to ensure that you are selecting the right supply chain partners (including 3PL\u0026rsquo;s) based on your business goals. Emphasis is placed on understanding alternative techniques for supplier selection including applied quantitative decision making techniques.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Understand the alternative techniques for supplier selection including applied quantitative decision making techniques."}],"uid":"27233","created_gmt":"2021-08-31 13:40:23","changed_gmt":"2022-02-24 16:07:53","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-06-14T09:00:00-04:00","event_time_end":"2022-06-16T18:00:00-04:00","event_time_end_last":"2022-06-16T18:00:00-04:00","gmt_time_start":"2022-06-14 13:00:00","gmt_time_end":"2022-06-16 22:00:00","gmt_time_end_last":"2022-06-16 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www.scl.gatech.edu\/scpmvs","title":"Course webpage with the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"11940","name":"GTSCL course"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"650960":{"#nid":"650960","#data":{"type":"event","title":"SCL Course: Lean Warehousing (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003E\u003Cstrong\u003ECOURSE DESCRIPTION\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course will demonstrate how warehouse operations are a key enabler to a successful supply chain implementation and the starting point for a transformation. It is critical to manage safety, quality and efficiency. Learn to leverage the lean supply chain modifications to improve customer responsiveness and reduce operating costs and in doing so contributing to a supply chain that creates a competitive advantage for a company. To accomplish this goal, we must bring lean principles into the warehouse and distribution center.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWHO SHOULD ATTEND\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003ESupply chain professionals, logistics professionals, material managers, production control managers, transportation managers, warehousing managers and purchasing managers\u003C\/p\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EHOW YOU WILL BENEFIT\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIsolate the key elements of lean thinking to be used in the warehouse\u003C\/li\u003E\r\n\t\u003Cli\u003EValue stream map warehouse operations\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize lean tools to reduce waste in the warehouse\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate a warehouse operation based on visual management and real time problem solving\u003C\/li\u003E\r\n\t\u003Cli\u003EReduce inventories in warehouse operations\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate collaboration between warehousing and other functional areas\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBenefits:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReduce inventories in the warehouse\u003C\/li\u003E\r\n\t\u003Cli\u003EReduce warehousing costs by as much as 25%\u003C\/li\u003E\r\n\t\u003Cli\u003EImplement lean in the warehouse\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate logistics collaboration between warehousing and other functional areas\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003E\u003Cstrong\u003EWHAT IS COVERED\u003C\/strong\u003E\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELean Warehouse Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Implementation Framework\u003C\/li\u003E\r\n\t\u003Cli\u003ELean Storage Planning Approach\u003C\/li\u003E\r\n\t\u003Cli\u003EApplication of a Lean Storage Location Sizing Method\u003C\/li\u003E\r\n\t\u003Cli\u003EJIT Implementation Approach\u003C\/li\u003E\r\n\t\u003Cli\u003EHow To Develop Standard Work Batches\u003C\/li\u003E\r\n\t\u003Cli\u003EGeneration of an Operational Diagram\u003C\/li\u003E\r\n\t\u003Cli\u003ECreation of a Daily Operational Work Load Plan\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelopment of a Progress Control Board\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course will demonstrate how warehouse operations are a key enabler to a successful supply chain implementation and the starting point for a transformation. It is critical to manage safety, quality and efficiency. Learn to leverage the lean supply chain modifications to improve customer responsiveness and reduce operating costs and in doing so contributing to a supply chain that creates a competitive advantage for a company. To accomplish this goal, we must bring lean principles into the warehouse and distribution center.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn how warehouse operations are a key enabler to a successful supply chain implementation and the starting point for a transformation."}],"uid":"27233","created_gmt":"2021-09-21 16:41:18","changed_gmt":"2022-02-24 16:07:00","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-06-07T09:00:00-04:00","event_time_end":"2022-06-09T17:59:00-04:00","event_time_end_last":"2022-06-09T17:59:00-04:00","gmt_time_start":"2022-06-07 13:00:00","gmt_time_end":"2022-06-09 21:59:00","gmt_time_end_last":"2022-06-09 21:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/leanwh","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"1676","name":"lean"},{"id":"6140","name":"warehousing"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"646657":{"#nid":"646657","#data":{"type":"event","title":"SCL Course: Creating Business Value with Statistical Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. You\u0026rsquo;ll learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. You\u0026rsquo;ll use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars (March 14, 15, 16, 17 | 1-5pm ET) and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand why and how to align Supply Chain Management (SCM) strategy with business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn statistics techniques as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand inventory management models and how to apply statistics techniques to them\u003C\/li\u003E\r\n\t\u003Cli\u003ECreate time series forecasts based on SCM data\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize Python and PowerBI to perform statistical analyses, create time series forecasts and visualize results\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe importance of aligning SCM and business strategy\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to ask the right business questions as they relate to SCM\u003C\/li\u003E\r\n\t\u003Cli\u003EHow to use statistics to identify issues, compare data, and forecast decision outcomes\u003C\/li\u003E\r\n\t\u003Cli\u003EStatistical\u0026nbsp;concepts including variance analysis and hypothesis testing\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EApplying statistics to inventory management models\u003C\/li\u003E\r\n\t\u003Cli\u003EForecasting techniques including time series forecasting\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models to improve operational performance metrics and align supply chain management with strategic business goals.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models."}],"uid":"27233","created_gmt":"2021-04-20 13:14:04","changed_gmt":"2022-02-24 16:06:19","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-05-16T14:00:00-04:00","event_time_end":"2022-05-19T18:00:00-04:00","event_time_end_last":"2022-05-19T18:00:00-04:00","gmt_time_start":"2022-05-16 18:00:00","gmt_time_end":"2022-05-19 22:00:00","gmt_time_end_last":"2022-05-19 22:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scabv","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"651640":{"#nid":"651640","#data":{"type":"event","title":"SCL Course: Supply Chain Risk Management (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECOURSE DESCRIPTION\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn today\u0026rsquo;s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWHO SHOULD ATTEND\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHOW YOU WILL BENEFIT\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop a broader, more comprehensive understanding of how their company\u0026rsquo;s supply chain may be at risk\u003C\/li\u003E\r\n\t\u003Cli\u003EMore effectively communicate to their company\u0026rsquo;s stakeholders the realities of supply chain risks\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild a cross-functional understanding of the building blocks for an effective Supply Chain Risk Management to be used in their particular business\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove their company\u0026rsquo;s Supply Chain Risk Mitigation program\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWHAT IS COVERED\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe difference between crisis management and supply chain risk management\u003C\/li\u003E\r\n\t\u003Cli\u003EThe significant long term impact of supply chain disruptions\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy supply chain risk management activities require enterprise wide participation\u003C\/li\u003E\r\n\t\u003Cli\u003EHow companies can take proactive, actionable steps to add significant resiliency to their supply chain operation, often without requiring significant levels of investments\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn today\u0026rsquo;s global economy, operating risks are increasingly on the minds of executives. The specific context of operating risk can range from general areas of business continuity to the effects of natural disasters. In this course participants will gain a solid understanding of Supply Chain Risk Management principals including effective ways to identify, mitigate and measure the impact of potential supply chain disruptions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2021-10-13 14:08:24","changed_gmt":"2022-02-24 16:01:48","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-27T09:00:00-04:00","event_time_end":"2022-04-28T13:00:00-04:00","event_time_end_last":"2022-04-28T13:00:00-04:00","gmt_time_start":"2022-04-27 13:00:00","gmt_time_end":"2022-04-28 17:00:00","gmt_time_end_last":"2022-04-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/pe.gatech.edu\/courses\/supply-chain-risk-management","title":"Course registration page"},{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scrm","title":"Course webpage within the SCL website"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"651669":{"#nid":"651669","#data":{"type":"event","title":"SCL Course: World Class Sales and Operations Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003ECOURSE DESCRIPTION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the need for an S\u0026amp;OP cycle in a company\u003C\/li\u003E\r\n\t\u003Cli\u003EApply principles key to success of an S\u0026amp;OP process\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience true market examples relevant to their businesses\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ELEARNING OBJECTIVES\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELearn how to identify and apply best fit S\u0026amp;OP process and technology enablers to your organization and make it a reality based process.\u003C\/li\u003E\r\n\t\u003Cli\u003EWalk through a complete simulated S\u0026amp;OP cycle supported by a technology enabler.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the interaction and integration between the financial and operation levels of S\u0026amp;O.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the key components of an effective S\u0026amp;OP business case through discussion of real life examples of how companies have benefited from the implementation of best practices in S\u0026amp;OP.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDefining the S\u0026amp;OP process before adopting technology\u003C\/li\u003E\r\n\t\u003Cli\u003EThe advantages of value based and reality based S\u0026amp;OP\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy S\u0026amp;OP needs to be integrated closely with operational planning\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat is the scope of each role in the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat are the most valuable outputs and results of the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EHow can technology enable companies to take performance to the next level\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience a complete simulated technology-enabled S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2021-10-13 18:39:29","changed_gmt":"2022-02-24 16:00:57","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-28T09:00:00-04:00","event_time_end":"2022-03-29T13:00:00-04:00","event_time_end_last":"2022-03-29T13:00:00-04:00","gmt_time_start":"2022-03-28 13:00:00","gmt_time_end":"2022-03-29 17:00:00","gmt_time_end_last":"2022-03-29 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.pe.gatech.edu\/courses\/world-class-sales-and-operations-planning","title":"Course registration page"},{"url":"http:\/\/www.scl.gatech.edu\/wcsop","title":"Course webpage within the SCL website"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"646649":{"#nid":"646649","#data":{"type":"event","title":"SCL Course: Financial Decision Making (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThe course is designed to help\u0026nbsp;participants understand\u0026nbsp;how decisions impact\u0026nbsp;financial performance, identify\u0026nbsp;initiatives to improve company performance, and build better business cases with the overall goal of\u0026nbsp;improving financial acumen\u0026nbsp;and decision-making.\u0026nbsp;The course utilizes hands-on applications, group discussion, and exercises.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe course is comprised of (1) 60-minute pre-course introductory session (March 9 | 1:30-2:30pm ET) and (3) 90-minute instructor-led LIVE group webinars (March\u0026nbsp;16, 23, 30\u0026nbsp;| 1:30-3pm ET) with each group webinar requiring (1) 90-minute session of online pre-work to be completed before each webinar (total of 9 hours). Participants will be able to access the online \u0026quot;pre-work\u0026quot; material starting March 2.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EEarly or middle stage career professionals who are or will be responsible for executing organizational strategy tied to an integrated view of the organization (including professionals from distribution and logistics, production, and operations).\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EEnhance your\u0026nbsp;financial acumen\u003C\/li\u003E\r\n\t\u003Cli\u003EGain a framework for better managing financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand how faster decision-making can help more quickly capture business and financial benefits\u003C\/li\u003E\r\n\t\u003Cli\u003EObtain practical experience relating to putting together a business case for a real project\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe measures (return, cash flow, etc.) and key drivers (revenue, profitability, asset utilization) of financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EThe \u0026lsquo;Power of One\u0026rsquo; \u0026ndash; the impact of improving any financial metric by 1% (e.g. 1% increase in revenue, 1% decrease in cost of goods sold \u0026amp; 1-day reduction in inventory)\u003C\/li\u003E\r\n\t\u003Cli\u003EHow improvement in operational key performance indicators (KPIs) improves cash flow and overall financial performance, and how to better manage activities that impact operational KPIs.\u003C\/li\u003E\r\n\t\u003Cli\u003EBuilding a business case (strategic fit, critical success factors, change management, intangible benefits, financial criteria e.g., cash flow, payback, NPV and breakeven analysis) and using a business case as a project plan\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 1\u0026ndash; Managing Financial Performance\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of the importance and drivers of financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EHow it is influenced by individual decisions and collectively as a team\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReview Financial Acumen eLearning\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify the areas of financial performance they are responsible for managing\u003C\/li\u003E\r\n\t\u003Cli\u003EExamples of decisions that impact a company\u0026rsquo;s overall performance\u003C\/li\u003E\r\n\t\u003Cli\u003EAnalysis of\u0026nbsp;company\u0026nbsp;(or company of choice) financial performance using FinListics ClientIQ.\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 1 for review by facilitator.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EOverall measures of performance (return, cash flow, etc.)\u003C\/li\u003E\r\n\t\u003Cli\u003EKey drivers of financial performance\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003ERevenue\u003C\/li\u003E\r\n\t\t\u003Cli\u003EProfitability\u003C\/li\u003E\r\n\t\t\u003Cli\u003EAsset utilization\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Analyze financial performance \u0026ndash; trend, peer, and industry\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity:\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EPower of One - what are cash flow benefits from improvements in:\r\n\t\t\u003Cul\u003E\r\n\t\t\t\u003Cli\u003EFinancial metrics by 1% (e.g. 1% increase in revenue, 1% decrease in cost of goods sold)\u003C\/li\u003E\r\n\t\t\t\u003Cli\u003ECapital Utilization (e.g. 1-day reduction in inventory)\u003C\/li\u003E\r\n\t\t\u003C\/ul\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\t\u003Cli\u003EGap Analyses\r\n\t\t\u003Cul\u003E\r\n\t\t\t\u003Cli\u003EImprovement in financial metric to best performing year or best performing peer\u003C\/li\u003E\r\n\t\t\u003C\/ul\u003E\r\n\t\t\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EKey take-aways and how participants will apply what they have learned\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 2 \u0026ndash; Improving Financial Performance\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of how improvement in operational key performance indicators (KPIs) improve cash flow and overall financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EExplain how participants can better manage activities impacting operational KPIs\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIdentify operational KPIs they help manage\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify initiatives to improve operational KPIs\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 2 for review by facilitator.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EFramework for better managing financial performance\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EFinancial metrics -\u0026gt; business processes -\u0026gt; activities and tasks -\u0026gt; operational KPIs\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Identify KPIs participant\u0026rsquo;s company is most focused on improving (e.g., materials, labor, closure rate, employee turnover, etc. What lines of business would be involved? What are the initiatives? What are the business benefits?)\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Power of One and Gap Analyses \u0026ndash; what are cash flow benefits from:\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EImprove targeted operational KPIs by 1%\u003C\/li\u003E\r\n\t\t\u003Cli\u003EImprove performance to targeted performance\u003C\/li\u003E\r\n\t\t\u003Cli\u003ECost of delay in achieving improvement in performance\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EHow faster decision-making can help the company more quickly capture business and financial benefits.\u003C\/li\u003E\r\n\t\u003Cli\u003EKey take-aways and how participants will apply what they have learned\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWebinar 3 \u0026ndash; Building the Better Business Case\u003C\/h4\u003E\r\n\r\n\u003Ch5\u003EObjectives\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDevelop initiative that helps improve participant\u0026rsquo;s company financial performance\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelop deeper understanding of building a business case\u003C\/li\u003E\r\n\t\u003Cli\u003EUsing the business case as project plan instead of check-the-box to get approval\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003EPre-work\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EReview \u003Cem\u003EBusiness Case Acumen\u003C\/em\u003E eLearning\u003C\/li\u003E\r\n\t\u003Cli\u003EBuild on initiative identified in Webinar 2\u003C\/li\u003E\r\n\t\u003Cli\u003EDevelop initial business case\u003C\/li\u003E\r\n\t\u003Cli\u003EConduct cash flow analysis using FinListics ClientIQ\u003C\/li\u003E\r\n\t\u003Cli\u003EPre-work submitted prior to webinar 3 for review by facilitator.\u0026nbsp;\u0026nbsp;\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch5\u003ETopics\u003C\/h5\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBusiness case overview\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EQualitative \u0026ndash; e.g., strategic fit, critical success factors, change management, intangible benefits etc.\u003C\/li\u003E\r\n\t\t\u003Cli\u003EQuantitative \u0026ndash; financial criteria e.g., cash flow, payback, NPV, etc. and breakeven analysis\u003C\/li\u003E\r\n\t\t\u003Cli\u003EMonitoring and managing success\u0026nbsp;\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\t\u003Cli\u003EActivity: Present initial business case and receive feedback from peers and facilitator\u003C\/li\u003E\r\n\t\u003Cli\u003ESummary of webinar series\r\n\t\u003Cul\u003E\r\n\t\t\u003Cli\u003EKey take-aways\u003C\/li\u003E\r\n\t\t\u003Cli\u003EHow participants will apply what they have learned\u003C\/li\u003E\r\n\t\t\u003Cli\u003EWhat \/ how will they share with others\u003C\/li\u003E\r\n\t\u003C\/ul\u003E\r\n\t\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe course is designed to help\u0026nbsp;participants understand\u0026nbsp;how decisions impact\u0026nbsp;financial performance, identify\u0026nbsp;initiatives to improve company performance, and build better business cases with the overall goal of\u0026nbsp;improving financial acumen\u0026nbsp;and decision-making.\u0026nbsp;The course utilizes hands-on applications, group discussion, and exercises.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Improve your financial acumen\u00a0and decision-making to improve company performance"}],"uid":"27233","created_gmt":"2021-04-19 19:45:25","changed_gmt":"2022-02-24 16:00:49","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-09T13:30:00-05:00","event_time_end":"2022-03-30T15:00:00-04:00","event_time_end_last":"2022-03-30T15:00:00-04:00","gmt_time_start":"2022-03-09 18:30:00","gmt_time_end":"2022-03-30 19:00:00","gmt_time_end_last":"2022-03-30 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/fdm","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"4175","name":"finance"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"653996":{"#nid":"653996","#data":{"type":"event","title":"CANCELED - ISyE Seminar - Courtney Paquette ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EStochastic Algorithms in the Large: Exact Dynamics, Average-case Analysis, and Stepsize Criticality\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will present a framework, inspired by random matrix theory, for analyzing the dynamics of stochastic algorithms (e.g., stochastic gradient descent (SGD) and momentum) when both the number of samples and dimensions are large. Using this new framework, we show that the dynamics of stochastic algorithms on a least squares problem with random data become deterministic in the large sample and dimensional limit. Furthermore, the limiting dynamics are governed by a Volterra integral equation. This model predicts that SGD undergoes a phase transition at an explicitly given critical stepsize that ultimately affects its convergence rate, which we also verify experimentally. Finally, when input data is isotropic, we provide explicit expressions for the dynamics and average-case\u0026nbsp;convergence rates. These rates show significant improvement over the\u0026nbsp;worst-case\u0026nbsp;complexities.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECourtney Paquette is an assistant professor at McGill University and a CIFAR Canada AI chair. Paquette\u0026rsquo;s research broadly focuses on designing and analyzing algorithms for large-scale optimization problems, motivated by applications in data science. She received her PhD from the mathematics department at the University of Washington (2017), held postdoctoral positions at Lehigh University (2017-2018) and University of Waterloo (NSF postdoctoral fellowship, 2018-2019), and was a research scientist at Google Research, Brain Montreal (2019-2020).\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn this talk, I will present a framework, inspired by random matrix theory, for analyzing the dynamics of stochastic algorithms (e.g., stochastic gradient descent (SGD) and momentum) when both the number of samples and dimensions are large. Using this new framework, we show that the dynamics of stochastic algorithms on a least squares problem with random data become deterministic in the large sample and dimensional limit. Furthermore, the limiting dynamics are governed by a Volterra integral equation. This model predicts that SGD undergoes a phase transition at an explicitly given critical stepsize that ultimately affects its convergence rate, which we also verify experimentally. Finally, when input data is isotropic, we provide explicit expressions for the dynamics and average-case\u0026nbsp;convergence rates. These rates show significant improvement over the\u0026nbsp;worst-case\u0026nbsp;complexities.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Stochastic Algorithms in the Large: Exact Dynamics, Average-case Analysis, and Stepsize Criticality"}],"uid":"34977","created_gmt":"2022-01-04 13:05:21","changed_gmt":"2022-02-18 21:55:29","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-22T11:00:00-05:00","event_time_end":"2022-02-22T12:00:00-05:00","event_time_end_last":"2022-02-22T12:00:00-05:00","gmt_time_start":"2022-02-22 16:00:00","gmt_time_end":"2022-02-22 17:00:00","gmt_time_end_last":"2022-02-22 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"655446":{"#nid":"655446","#data":{"type":"event","title":"Supply Chain and Logistics in 2022 and Beyond - Learners and Leaders Breakfast Series","body":[{"value":"\u003Cp\u003ESupply chain and logistics is now a common phrase used by everyone around the world. There are many questions about how to capitalize on the expediting of technology, business model, and innovation change that has been exhibited during the past two years.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETim Brown, managing director of the Georgia Tech Supply Chain and Logistics Institute, will moderate a panel of experts with topics of discussion ranging from workforce development and future freight flows to the impact on the economic climate.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe event will be hosted in Georgia Tech Savannah, but note that this is a hybrid event (attendees can\u0026nbsp;join in-person or virtually, but you must register to attend.)\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003ETuesday, April 19, 2022\u003Cbr \/\u003E\r\nSupply Chain and Logistics in 2022 and Beyond - Learners \u0026amp; Leaders Breakfast Series at Georgia Tech-Savannah\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E7:30 am: \u003Cstrong\u003EBreakfast \u0026amp; Networking\u003C\/strong\u003E (on-site at Georgia Tech Savannah campus)\u003C\/li\u003E\r\n\t\u003Cli\u003E8:00-9:30 am: \u003Cstrong\u003EProgram \u003C\/strong\u003E(This is a hybrid event. You can join in-person or virtually.)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003ECost: \u003Cstrong\u003EFree\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERegistration:\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/2022supplychain.eventbrite.com\u0022 target=\u0022_blank\u0022\u003E2022supplychain.eventbrite.com\u003C\/a\u003E\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EModerator:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETim Brown\u003C\/strong\u003E, Managing Director, Georgia Tech\u003Cbr \/\u003E\r\n\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Supply Chain and Logistics Institute\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EPanelists:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMark Ferzacca\u003C\/strong\u003E, Vice President-Warehousing,\u0026nbsp;Matson Logistics Warehousing, Inc.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBrian Greene\u003C\/strong\u003E, Chief Supply Chain Officer, HMTX Industries\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EEric Howell\u003C\/strong\u003E, CEO, Port City Logistics\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESandy Lake\u003C\/strong\u003E, Director, Georgia Center of Innovation\u0026nbsp;for Logistics\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECliff Pyron\u003C\/strong\u003E, Chief Commercial Officer, Georgia\u0026nbsp;Ports Authority\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETim Brown, managing director of the Georgia Tech Supply Chain and Logistics Institute, will moderate a panel of experts with topics of discussion ranging from workforce development and future freight flows to the impact on the economic climate.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A hybrid event featuring a panel of supply chain experts and hosted by Georgia Tech Savannah."}],"uid":"27233","created_gmt":"2022-02-14 17:29:33","changed_gmt":"2022-02-14 18:20:50","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-19T08:30:00-04:00","event_time_end":"2022-04-19T10:30:00-04:00","event_time_end_last":"2022-04-19T10:30:00-04:00","gmt_time_start":"2022-04-19 12:30:00","gmt_time_end":"2022-04-19 14:30:00","gmt_time_end_last":"2022-04-19 14:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"655454":{"id":"655454","type":"image","title":"Supply Chain and Logistics in 2022 and Beyond","body":null,"created":"1644861371","gmt_created":"2022-02-14 17:56:11","changed":"1644861371","gmt_changed":"2022-02-14 17:56:11","alt":"","file":{"fid":"248496","name":"GTSav-LNLBS_20220419.jpg","image_path":"\/sites\/default\/files\/images\/GTSav-LNLBS_20220419.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/GTSav-LNLBS_20220419.jpg","mime":"image\/jpeg","size":239013,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/GTSav-LNLBS_20220419.jpg?itok=YKJpyIKt"}}},"media_ids":["655454"],"related_links":[{"url":"https:\/\/2022supplychain.eventbrite.com\/","title":"Register to Attend"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"1317","name":"Georgia Tech Savannah"},{"id":"167074","name":"Supply Chain"},{"id":"233","name":"Logistics"},{"id":"3984","name":"panel"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E912-966-7922\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"655430":{"#nid":"655430","#data":{"type":"event","title":" ISyE Department Seminar \u2013 Frank E. Curtis","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Algorithms for Deterministically Constrained Stochastic Optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E I will present the recent work by my research group on the design, analysis, and implementation of algorithms for solving\u0026nbsp;continuous\u0026nbsp;nonlinear optimization problems that involve a stochastic objective function and deterministic constraints.\u0026nbsp; The talk will focus on our sequential quadratic optimization (commonly known as SQP) methods for cases when the constraints are defined by nonlinear systems of equations, which arise in various applications including optimal control, PDE-constrained optimization, and network optimization problems.\u0026nbsp; One might also consider our techniques for training machine learning (e.g., deep learning) models with constraints. \u0026nbsp;Much of our recent work focuses on the \u0026quot;fully stochastic\u0026quot; regime in which only stochastic gradient estimates are employed, for which we have derived convergence in expectation results and worst-case iteration complexity bounds that are on par with stochastic gradient methods for the unconstrained setting.\u0026nbsp;\u0026nbsp;I will also discuss the various extensions that my group is exploring along with other related open questions.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio:\u003C\/strong\u003E Frank E. Curtis is a Professor in the Department of Industrial and Systems Engineering at Lehigh University. He received his Bachelor degree from the College of William and Mary with a double major in Mathematics and Computer Science, received his Master degree and Ph.D. from the Department of Industrial Engineering and Management Science at Northwestern University, and spent two years as a Postdoctoral Researcher in the Courant Institute of Mathematical Sciences at New York University. His research focuses on the design, analysis, and implementation of numerical methods for solving large-scale nonlinear optimization problems. He received an Early Career Award from the Advanced Scientific Computing Research program of the U.S. Department of Energy, and has received funding from various programs of the U.S. National Science Foundation, including through a TRIPODS Institute grant awarded to him and his collaborators at Lehigh, Northwestern, and Boston University. He received, along with Leon Bottou (Facebook AI Research) and Jorge Nocedal (Northwestern), the 2021 SIAM\/MOS Lagrange Prize in Continuous Optimization. He was awarded, with James V. Burke (U. of Washington), Adrian Lewis (Cornell), and Michael Overton (NYU), the 2018 INFORMS Computing Society Prize. He and team members Daniel Molzahn (Georgia Tech), Andreas Waechter (Northwestern), Ermin Wei (Northwestern), and Elizabeth Wong (UC San Diego) were awarded second place in the ARPA-E Grid Optimization Competition in 2020. He currently serves as an Associate Editor for Mathematical Programming, SIAM Journal on Optimization, Mathematics of Operations Research, IMA Journal of Numerical Analysis, and Mathematical Programming Computation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E I will present the recent work by my research group on the design, analysis, and implementation of algorithms for solving\u0026nbsp;continuous\u0026nbsp;nonlinear optimization problems that involve a stochastic objective function and deterministic constraints.\u0026nbsp; The talk will focus on our sequential quadratic optimization (commonly known as SQP) methods for cases when the constraints are defined by nonlinear systems of equations, which arise in various applications including optimal control, PDE-constrained optimization, and network optimization problems.\u0026nbsp; One might also consider our techniques for training machine learning (e.g., deep learning) models with constraints. \u0026nbsp;Much of our recent work focuses on the \u0026quot;fully stochastic\u0026quot; regime in which only stochastic gradient estimates are employed, for which we have derived convergence in expectation results and worst-case iteration complexity bounds that are on par with stochastic gradient methods for the unconstrained setting.\u0026nbsp;\u0026nbsp;I will also discuss the various extensions that my group is exploring along with other related open questions.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio:\u003C\/strong\u003E Frank E. Curtis is a Professor in the Department of Industrial and Systems Engineering at Lehigh University. He received his Bachelor degree from the College of William and Mary with a double major in Mathematics and Computer Science, received his Master degree and Ph.D. from the Department of Industrial Engineering and Management Science at Northwestern University, and spent two years as a Postdoctoral Researcher in the Courant Institute of Mathematical Sciences at New York University. His research focuses on the design, analysis, and implementation of numerical methods for solving large-scale nonlinear optimization problems. He received an Early Career Award from the Advanced Scientific Computing Research program of the U.S. Department of Energy, and has received funding from various programs of the U.S. National Science Foundation, including through a TRIPODS Institute grant awarded to him and his collaborators at Lehigh, Northwestern, and Boston University. He received, along with Leon Bottou (Facebook AI Research) and Jorge Nocedal (Northwestern), the 2021 SIAM\/MOS Lagrange Prize in Continuous Optimization. He was awarded, with James V. Burke (U. of Washington), Adrian Lewis (Cornell), and Michael Overton (NYU), the 2018 INFORMS Computing Society Prize. He and team members Daniel Molzahn (Georgia Tech), Andreas Waechter (Northwestern), Ermin Wei (Northwestern), and Elizabeth Wong (UC San Diego) were awarded second place in the ARPA-E Grid Optimization Competition in 2020. He currently serves as an Associate Editor for Mathematical Programming, SIAM Journal on Optimization, Mathematics of Operations Research, IMA Journal of Numerical Analysis, and Mathematical Programming Computation.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Algorithms for Deterministically Constrained Stochastic Optimization"}],"uid":"36086","created_gmt":"2022-02-11 21:45:01","changed_gmt":"2022-02-11 21:45:01","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-03-04T11:00:00-05:00","event_time_end":"2022-03-04T12:00:00-05:00","event_time_end_last":"2022-03-04T12:00:00-05:00","gmt_time_start":"2022-03-04 16:00:00","gmt_time_end":"2022-03-04 17:00:00","gmt_time_end_last":"2022-03-04 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"655265":{"#nid":"655265","#data":{"type":"event","title":"ISyE Seminar - Manuel Aprile ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExtended formulations for combinatorial optimization problems\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMixed-integer linear programming is one of the most popular and effective tools to solve optimization problems. Representing our problem of interest via a linear formulation is a key step crucially affecting the performance of the solver. When the original formulation is too large to be processed, one can resort to an extended formulation: while extra variables are added, the number of constraints can be dramatically reduced, allowing for a compact representation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk I will introduce my research on extended formulations and give some examples of how to construct such formulations for some classical combinatorial optimization problems, using tools from communication complexity, matroid theory and combinatorics. I will then highlight how these theoretical constructions can be effectively used in computational applications.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EManuel Aprile has studied mathematics and computer science in Catania (Italy) and Oxford (UK). He obtained his PhD in Discrete Optimization at EPFL (Switzerland) in 2018, under the supervision of Friedrich Eisenbrand and Yuri Faenza. He has been a post-doc in Bruxelles, and he is currently a post-doc at Padua University, Italy.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMixed-integer linear programming is one of the most popular and effective tools to solve optimization problems. Representing our problem of interest via a linear formulation is a key step crucially affecting the performance of the solver. When the original formulation is too large to be processed, one can resort to an extended formulation: while extra variables are added, the number of constraints can be dramatically reduced, allowing for a compact representation.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this talk I will introduce my research on extended formulations and give some examples of how to construct such formulations for some classical combinatorial optimization problems, using tools from communication complexity, matroid theory and combinatorics. I will then highlight how these theoretical constructions can be effectively used in computational applications.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Extended formulations for combinatorial optimization problems"}],"uid":"34977","created_gmt":"2022-02-07 17:30:40","changed_gmt":"2022-02-07 17:30:40","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-17T11:00:00-05:00","event_time_end":"2022-02-17T12:00:00-05:00","event_time_end_last":"2022-02-17T12:00:00-05:00","gmt_time_start":"2022-02-17 16:00:00","gmt_time_end":"2022-02-17 17:00:00","gmt_time_end_last":"2022-02-17 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654627":{"#nid":"654627","#data":{"type":"event","title":"ISyE Seminar - Xin Chen ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EInventory management: new models, challenges, and opportunities\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ERecent years witness novel business models and new challenges in inventory management. In this talk, I will present several research projects motivated by current practice and collaborations with industry partners: inventory models with large lead times, inventory allocation in omnichannel retailing, and operations in smart shelves. The theoretical and practical challenges and opportunities will be highlighted. I will also briefly introduce some other research projects on data-driven modeling in online platforms and retailing and the application of discrete convex analysis to operations models.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EXin Chen is a professor at the University of Illinois at Urbana-Champaign. He obtained his PhD from MIT in 2003, MS from Chinese Academy of Sciences in 1998 and BS from Xiangtan University in 1995. His research interest lies in optimization, data analytics, revenue management and supply chain management. He received the Informs revenue management and pricing section prize in 2009. He is the coauthor of the book \u0026ldquo;The Logic of Logistics: Theory, Algorithms, and Applications for Logistics and Supply Chain Management (Second Edition, 2005, \u0026amp; Third Edition, 2014)\u0026rdquo;, and serving as the department editor of logistics and supply chain management of Naval Research Logistics and an associate editor of several journals including Operations Research, Management Science, and Production and Operations Management.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ERecent years witness novel business models and new challenges in inventory management. In this talk, I will present several research projects motivated by current practice and collaborations with industry partners: inventory models with large lead times, inventory allocation in omnichannel retailing, and operations in smart shelves. The theoretical and practical challenges and opportunities will be highlighted. I will also briefly introduce some other research projects on data-driven modeling in online platforms and retailing and the application of discrete convex analysis to operations models.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Inventory management: new models, challenges, and opportunities"}],"uid":"34977","created_gmt":"2022-01-20 15:53:51","changed_gmt":"2022-01-20 15:53:51","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-31T11:00:00-05:00","event_time_end":"2022-01-31T12:00:00-05:00","event_time_end_last":"2022-01-31T12:00:00-05:00","gmt_time_start":"2022-01-31 16:00:00","gmt_time_end":"2022-01-31 17:00:00","gmt_time_end_last":"2022-01-31 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654350":{"#nid":"654350","#data":{"type":"event","title":"ISyE Seminar - Eunhye Song ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026ldquo;Selection of the most probable best\u0026rdquo;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn many business applications, simulation is the primary decision-making tool for a complex stochastic system, where an analytical expression of the problem is unavailable. Often, parameters of these simulators are unknown and must be estimated from data. When plug-in estimates of the parameters are adopted, there is a risk of making a suboptimal decision due to the estimation error in the parameter values. Under this type of model risk, this talk discusses a new decision-making framework in the context of simulation optimization, \u003Cem\u003Ethe most probable best \u003C\/em\u003E(MPB), is introduced in this talk. The MPB is defined as the solution whose posterior probability of being optimal is the largest given the data when the parameters\u0026rsquo; estimation error is modeled with a posterior distribution. Some saliant theoretical properties of the MPB will be discussed including its strong consistency to the optimum under the true parameter as the data size increases. In the second half of the talk, efficient sequential sampling algorithms to find the MPB will be introduced and their asymptotic optimality (in efficiency) will be discussed. To demonstrate business insights the MPB formulation provides, a product portfolio optimization problem, where consumer utility parameters are estimated from conjoint survey data will be presented.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEunhye Song is Harold and Inge Marcus Early Career Assistant Professor in Industrial and Manufacturing Engineering at the Penn State University and an Associate of the Institute for Computational and Data Sciences. She earned her PhD in Industrial Engineering and Management Sciences at Northwestern University in 2017 and BS and MS degrees in Industrial and Systems Engineering at KAIST in 2010 and 2012, respectively. Her research interests include simulation design of experiments, uncertainty and risk quantification, and simulation optimization. She received the National Science Foundation CAREER award in 2021 and won an honorable mention at the 2020 INFORMS Junior Faculty Interest Group paper competition. She is an active member of the INFORMS Simulation Society and had served on the society\u0026#39;s Underrepresented Minorities \u0026amp; Women committee from 2018 to 2020 and organized the 2021 I-Sim Research Workshop.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn many business applications, simulation is the primary decision-making tool for a complex stochastic system, where an analytical expression of the problem is unavailable. Often, parameters of these simulators are unknown and must be estimated from data. When plug-in estimates of the parameters are adopted, there is a risk of making a suboptimal decision due to the estimation error in the parameter values. Under this type of model risk, this talk discusses a new decision-making framework in the context of simulation optimization, \u003Cem\u003Ethe most probable best \u003C\/em\u003E(MPB), is introduced in this talk. The MPB is defined as the solution whose posterior probability of being optimal is the largest given the data when the parameters\u0026rsquo; estimation error is modeled with a posterior distribution. Some saliant theoretical properties of the MPB will be discussed including its strong consistency to the optimum under the true parameter as the data size increases. In the second half of the talk, efficient sequential sampling algorithms to find the MPB will be introduced and their asymptotic optimality (in efficiency) will be discussed. To demonstrate business insights the MPB formulation provides, a product portfolio optimization problem, where consumer utility parameters are estimated from conjoint survey data will be presented.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"\u201cSelection of the most probable best\u201d"}],"uid":"34977","created_gmt":"2022-01-12 14:39:08","changed_gmt":"2022-01-14 18:36:53","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-03T11:00:00-05:00","event_time_end":"2022-02-03T12:00:00-05:00","event_time_end_last":"2022-02-03T12:00:00-05:00","gmt_time_start":"2022-02-03 16:00:00","gmt_time_end":"2022-02-03 17:00:00","gmt_time_end_last":"2022-02-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654436":{"#nid":"654436","#data":{"type":"event","title":"ISyE Seminar - Johannes Milz ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EProperties of Monte Carlo Estimators for Risk-Neutral PDE-Constrained Optimization Problems\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EComplex systems in science and engineering can often be modeled with partial differential equations (PDEs) with uncertain parameters. In order to improve the design of such systems, we formulate a risk-neutral optimization problem with PDE constraints, an infinite-dimensional stochastic program. We apply the sample average approximation (SAA) to the risk-neutral PDE-constrained optimization problem and analyze the consistency of the SAA optimal value and solutions. Our analysis exploits hidden compactness in PDE-constrained optimization problems, allowing us to construct deterministic, compact sets containing the solutions to the risk-neutral problem and those to the SAA problems. Exploiting further problem structure, we establish nonasymptotic sample size estimates using the covering number approach, thereby we shed light on the computational resources needed to obtain accurate solutions.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EJohannes Milz is research associate at the Technical University of Munich. Johannes\u0026#39; research broadly lies in optimization under uncertainty with a current focus on complexity analysis of and algorithmic design for PDE-constrained optimization problems under uncertainty. He received his doctorate in applied mathematics from the Technical University of Munich in 2021.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EComplex systems in science and engineering can often be modeled with partial differential equations (PDEs) with uncertain parameters. In order to improve the design of such systems, we formulate a risk-neutral optimization problem with PDE constraints, an infinite-dimensional stochastic program. We apply the sample average approximation (SAA) to the risk-neutral PDE-constrained optimization problem and analyze the consistency of the SAA optimal value and solutions. Our analysis exploits hidden compactness in PDE-constrained optimization problems, allowing us to construct deterministic, compact sets containing the solutions to the risk-neutral problem and those to the SAA problems. Exploiting further problem structure, we establish nonasymptotic sample size estimates using the covering number approach, thereby we shed light on the computational resources needed to obtain accurate solutions.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Properties of Monte Carlo Estimators for Risk-Neutral PDE-Constrained Optimization Problems"}],"uid":"34977","created_gmt":"2022-01-14 15:02:41","changed_gmt":"2022-01-14 15:02:41","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-27T11:00:00-05:00","event_time_end":"2022-01-27T12:00:00-05:00","event_time_end_last":"2022-01-27T12:00:00-05:00","gmt_time_start":"2022-01-27 16:00:00","gmt_time_end":"2022-01-27 17:00:00","gmt_time_end_last":"2022-01-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654428":{"#nid":"654428","#data":{"type":"event","title":"ISyE Seminar - Gideon Weiss","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EDesign for parallel skill based service systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EService systems with several types of customers and servers subject to a bipartite compatibility graph are in general quite intractable. \u0026nbsp;I will discuss tractable examples of such systems, and their relation to the simpler tractable model of FCFS bipartite matching, and present a conjecture, and a heuristic based on it, to answer problems of design for large scale general systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio-sketch:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGideon Weiss is professor emeritus at the Department of Statistics in the University of Haifa, Israel. He has previously been on the faculty of ISYE GA Tech 1983--1994. His research interests are scheduling and control of queueing networks (recent book, Cambridge University Press), and simplex methods for continuous linear programming.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Design for parallel skill based service systems."}],"uid":"36086","created_gmt":"2022-01-13 20:25:37","changed_gmt":"2022-01-13 20:25:37","author":"yrollins3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-18T11:00:00-05:00","event_time_end":"2022-02-18T12:00:00-05:00","event_time_end_last":"2022-02-18T12:00:00-05:00","gmt_time_start":"2022-02-18 16:00:00","gmt_time_end":"2022-02-18 17:00:00","gmt_time_end_last":"2022-02-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"654008":{"#nid":"654008","#data":{"type":"event","title":"ISyE Seminar - Ryan Cory-Wright ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMixed-projection conic optimization: A new paradigm for modeling rank constraints\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMany central problems in optimization, machine learning, and control theory are equivalent to optimizing a low-rank matrix over a convex set. However, while rank constraints offer unparalleled modeling flexibility, no generic code currently solves these problems to certifiable optimality at even moderate sizes. In this talk, we propose such an approach. To model rank constraints, we introduce symmetric projection matrices that satisfy Y^2 = Y and model the row space of a matrix, the matrix analog of binary variables that satisfy z^2 = z, and model the sparsity of a vector.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe demonstrate that this modeling paradigm yields tractable convex problems over the non-convex set of projection matrices. Further, we design outer-approximation algorithms to solve low-rank problems to certifiable optimality and demonstrate their efficacy on matrix completion problems. We also study the convex relaxations of low-rank problems, and propose a new preprocessing technique for obtaining strong yet computationally affordable relaxations. The technique leads to a class of new relaxations for several widely-used low-rank models, including matrix completion problems among others.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinally, we discuss an ongoing collaboration with OCP-a large Moroccan fertilizer manufacturer-to optimally decarbonize their production process by investing in an appropriate mixture of batteries, solar panels, and transmission lines. All papers mentioned in the talk are available at\u0026nbsp;\u003Ca href=\u0022http:\/\/ryancorywright.github.io\u0022\u003Eryancorywright.github.io\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ERyan Cory-Wright is a fifth-year Ph.D. candidate at MIT\u0026rsquo;s Operations Research Center, advised by Dimitris Bertsimas. His research interests lie at the intersection of optimization, machine learning and statistics, with a focus on their application in energy systems. His current research follows two different threads. First, developing a suite of algorithms that efficiently address interpretable (e.g., sparse or low-rank) optimization problems. Second, integrating renewables within energy markets to combat climate change. He is a recipient of the INFORMS Nicholson Prize (2020), the INFORMS Pierskalla Award (2020), the INFORMS Computing Society Student Paper Award (2019), and the INFORMS Data Mining Section Student Paper Award (2021).\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMany central problems in optimization, machine learning, and control theory are equivalent to optimizing a low-rank matrix over a convex set. However, while rank constraints offer unparalleled modeling flexibility, no generic code currently solves these problems to certifiable optimality at even moderate sizes. In this talk, we propose such an approach. To model rank constraints, we introduce symmetric projection matrices that satisfy Y^2 = Y and model the row space of a matrix, the matrix analog of binary variables that satisfy z^2 = z, and model the sparsity of a vector.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe demonstrate that this modeling paradigm yields tractable convex problems over the non-convex set of projection matrices. Further, we design outer-approximation algorithms to solve low-rank problems to certifiable optimality and demonstrate their efficacy on matrix completion problems. We also study the convex relaxations of low-rank problems, and propose a new preprocessing technique for obtaining strong yet computationally affordable relaxations. The technique leads to a class of new relaxations for several widely-used low-rank models, including matrix completion problems among others.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinally, we discuss an ongoing collaboration with OCP-a large Moroccan fertilizer manufacturer-to optimally decarbonize their production process by investing in an appropriate mixture of batteries, solar panels, and transmission lines. All papers mentioned in the talk are available at\u0026nbsp;\u003Ca href=\u0022http:\/\/ryancorywright.github.io\u0022\u003Eryancorywright.github.io\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Mixed-projection conic optimization: A new paradigm for modeling rank constraints"}],"uid":"34977","created_gmt":"2022-01-04 16:07:29","changed_gmt":"2022-01-04 16:07:29","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-18T11:00:00-05:00","event_time_end":"2022-01-18T12:00:00-05:00","event_time_end_last":"2022-01-18T12:00:00-05:00","gmt_time_start":"2022-01-18 16:00:00","gmt_time_end":"2022-01-18 17:00:00","gmt_time_end_last":"2022-01-18 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"653846":{"#nid":"653846","#data":{"type":"event","title":"ISyE Seminar - Grani A. Hanasusanto ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EData-Driven Prescriptive Analytics with Side Information: A Regularized Nadaraya-Watson Approach\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EWe consider generic stochastic optimization problems in the presence of side information that enables a more insightful decision. The side information constitutes observable exogenous covariates that alter the conditional probability distribution of the random problem parameters. Decision-makers who adapt their decisions according to the observed side information solve a stochastic optimization problem where the objective function is specified by the conditional expectation of the random cost. If the joint probability distribution is unknown, then the conditional expectation can be approximated in a data-driven manner using the Nadaraya-Watson kernel regression. While the emerging approximation scheme has found successful applications in diverse decision problems under uncertainty, it is largely unknown whether the scheme can provide any reasonable out-of-sample performance guarantees. In this talk, we establish guarantees for the generic problems by leveraging techniques from moderate deviations theory. Our analysis motivates the use of a variance-based regularization scheme which, in general, leads to a non-convex optimization problem. We adopt ideas from distributionally robust optimization to obtain tractable formulations. We present numerical experiments for inventory management and wind energy commitment problems to highlight the effectiveness of our regularization scheme.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EGrani A. Hanasusanto is an Assistant Professor of Operations Research and Industrial Engineering at The University of Texas at Austin (UT). Before joining UT, he was a postdoctoral researcher at the College of Management of Technology at \u0026Eacute;cole Polytechnique F\u0026eacute;d\u0026eacute;rale de Lausanne. He holds a PhD degree in Operations Research from Imperial College London and an MSc degree in Financial Engineering from the National University of Singapore. He is the recipient of the 2018 NSF CAREER Award. His research focuses on the design and analysis of tractable solution schemes for decision-making problems under uncertainty, with applications in operations management, energy systems, finance, machine learning and data analytics.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EWe consider generic stochastic optimization problems in the presence of side information that enables a more insightful decision. The side information constitutes observable exogenous covariates that alter the conditional probability distribution of the random problem parameters. Decision-makers who adapt their decisions according to the observed side information solve a stochastic optimization problem where the objective function is specified by the conditional expectation of the random cost. If the joint probability distribution is unknown, then the conditional expectation can be approximated in a data-driven manner using the Nadaraya-Watson kernel regression. While the emerging approximation scheme has found successful applications in diverse decision problems under uncertainty, it is largely unknown whether the scheme can provide any reasonable out-of-sample performance guarantees. In this talk, we establish guarantees for the generic problems by leveraging techniques from moderate deviations theory. Our analysis motivates the use of a variance-based regularization scheme which, in general, leads to a non-convex optimization problem. We adopt ideas from distributionally robust optimization to obtain tractable formulations. We present numerical experiments for inventory management and wind energy commitment problems to highlight the effectiveness of our regularization scheme.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Data-Driven Prescriptive Analytics with Side Information: A Regularized Nadaraya-Watson Approach"}],"uid":"34977","created_gmt":"2021-12-20 13:48:30","changed_gmt":"2022-01-04 16:01:03","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-10T11:00:00-05:00","event_time_end":"2022-01-10T12:00:00-05:00","event_time_end_last":"2022-01-10T12:00:00-05:00","gmt_time_start":"2022-01-10 16:00:00","gmt_time_end":"2022-01-10 17:00:00","gmt_time_end_last":"2022-01-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"653122":{"#nid":"653122","#data":{"type":"event","title":"ISyE Seminar - Weijun Xie ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EALSO-X and ALSO-X+: Better Convex Approximations for Chance Constrained Programs\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EChance constrained programs (CCPs) are generic frameworks for decision-making under uncertain constraints. The objective of a CCP is to find the best decision that violates the uncertainty constraints within the prespecified risk level. A CCP is often nonconvex and is difficult to solve to optimality. This paper studies and generalizes the ALSO-X, originally proposed by Ahmed, Luedtke, SOng, and Xie (2017), for solving a CCP. We first show that the ALSO-X resembles a bilevel optimization, where the upper-level problem is to find the best objective function value and enforce the feasibility of a CCP for a given decision from the lower-level problem, and the lower-level problem is to minimize the expectation of constraint violations subject to the upper bound of the objective function value provided by the upper-level problem. This interpretation motivates us to prove that when uncertain constraints are convex in the decision variables, ALSO-X always outperforms the state-of-art conditional-value-ta-risk\u0026nbsp;(CVaR) approximation. We further show (i) sufficient conditions under which ALSO-X can recover an optimal solution to a CCP; (ii) an equivalent bilinear programming formulation of a CCP, inspiring us to enhance ALSO-X with a convergent alternating minimization method (ALSO-X+); (iii) extensions of ALSO-X and ALSO-X+ to solve distributionally robust chance constrained programs (DRCCPs) under Wasserstein ambiguity set. Our numerical study demonstrates the effectiveness of the proposed methods.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EDr. Weijun Xie is an Assistant Professor of Industrial and Systems Engineering, Virginia Tech. He obtained his Ph.D. from Georgia Tech in 2017. His research interests lie in theory and applications of stochastic, discrete, and convex optimization. Dr. Xie has won multiple awards including NSF Career Award, INFORMS Optimization Prize for Young Researchers, INFORMS Junior Faculty Interest Group Paper Competition (Third Place), INFORMS George Nicholson Student Paper Competition (Honorable Mention). He currently serves as the Vice Chair of Optimization under Uncertainty at INFORMS Optimization Society and is an associate editor of the Journal of Global Optimization.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EChance constrained programs (CCPs) are generic frameworks for decision-making under uncertain constraints. The objective of a CCP is to find the best decision that violates the uncertainty constraints within the prespecified risk level. A CCP is often nonconvex and is difficult to solve to optimality. This paper studies and generalizes the ALSO-X, originally proposed by Ahmed, Luedtke, SOng, and Xie (2017), for solving a CCP. We first show that the ALSO-X resembles a bilevel optimization, where the upper-level problem is to find the best objective function value and enforce the feasibility of a CCP for a given decision from the lower-level problem, and the lower-level problem is to minimize the expectation of constraint violations subject to the upper bound of the objective function value provided by the upper-level problem. This interpretation motivates us to prove that when uncertain constraints are convex in the decision variables, ALSO-X always outperforms the state-of-art conditional-value-ta-risk\u0026nbsp;(CVaR) approximation. We further show (i) sufficient conditions under which ALSO-X can recover an optimal solution to a CCP; (ii) an equivalent bilinear programming formulation of a CCP, inspiring us to enhance ALSO-X with a convergent alternating minimization method (ALSO-X+); (iii) extensions of ALSO-X and ALSO-X+ to solve distributionally robust chance constrained programs (DRCCPs) under Wasserstein ambiguity set. Our numerical study demonstrates the effectiveness of the proposed methods.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"ALSO-X and ALSO-X+: Better Convex Approximations for Chance Constrained Programs"}],"uid":"34977","created_gmt":"2021-11-23 21:34:44","changed_gmt":"2022-01-04 12:54:29","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-01-13T11:00:00-05:00","event_time_end":"2022-01-13T12:00:00-05:00","event_time_end_last":"2022-01-13T12:00:00-05:00","gmt_time_start":"2022-01-13 16:00:00","gmt_time_end":"2022-01-13 17:00:00","gmt_time_end_last":"2022-01-13 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"653474":{"#nid":"653474","#data":{"type":"event","title":"SCL February 2022 Supply Chain Days","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our second fall Supply Chain Days! We will be hosting both an On Campus (Feb 3) and a Virtual session\u0026nbsp;(Feb 4). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThursday, February 3\u0026nbsp;| 11am-2pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, February 4\u0026nbsp;|\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our spring Supply Chain Days! We will be hosting both an On Campus (Feb 3) and a Virtual session\u0026nbsp;(Feb 4). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Events where industry supply chain representatives meet with Georgia Tech Supply Chain students"}],"uid":"27233","created_gmt":"2021-12-07 21:17:56","changed_gmt":"2021-12-10 15:32:30","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-02-03T11:00:00-05:00","event_time_end":"2022-02-04T15:00:00-05:00","event_time_end_last":"2022-02-04T15:00:00-05:00","gmt_time_start":"2022-02-03 16:00:00","gmt_time_end":"2022-02-04 20:00:00","gmt_time_end_last":"2022-02-04 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"653473":{"id":"653473","type":"image","title":"SCL February 2022 Supply Chain Days","body":null,"created":"1638911868","gmt_created":"2021-12-07 21:17:48","changed":"1638911868","gmt_changed":"2021-12-07 21:17:48","alt":"","file":{"fid":"247849","name":"homepage-scday_v1-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-scday_v1-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-scday_v1-600px.jpg","mime":"image\/jpeg","size":81331,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-scday_v1-600px.jpg?itok=1OKChhHu"}}},"media_ids":["653473"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"653061":{"#nid":"653061","#data":{"type":"event","title":"ISyE Seminar - Meng Qi ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ESmarter data-driven decision-making by integrating prediction and optimization\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EBig data provides new opportunities to tackle one of the main difficulties in decision-making systems \u0026ndash; uncertain behavior driven by the unknown probability distribution. Instead of the classical two-step predict-then-optimize (PTO) procedure, we provide smarter data-driven solutions by integrating these two steps. In the first half of this talk, we focus on a multi-period inventory replenishment problem with uncertain demand and vendor lead time (VLT), with accessibility to a large quantity of historical data. Different from the traditional two-step predict-then-optimize (PTO) solution framework, we propose a one-step end-to-end (E2E) framework that uses deep-learning models to output the suggested replenishment amount directly from input features without any intermediate step. The E2E model is trained to capture the behavior of the optimal dynamic programming solution under historical observations, without any prior assumptions on the distributions of the demand and the VLT. This algorithm is currently implemented in production at JD.com to replenish thousands of products. In the second half of this talk, I will move to a more general setting of the contextual stochastic optimization problem. We propose an integrated conditional estimation-optimization (ICEO) framework that estimates the underlying conditional distribution using data while considering the structure of the downstream optimization problem. We show that our ICEO approach is asymptotically consistent and further provide finite performance guarantees in the form of generalization bounds. We also discuss the computational difficulties of performing the ICEO approach and propose a general methodology by approximating the potential non-differentiable oracle. We also provide a polynomial optimization solution approach in the semi-algebraic case. The concept of E2E, which uses the input information directly for the ultimate goal, shortens the decision process and can also be useful in practice for a wide range of circumstances beyond supply chain management.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMeng Qi is a Ph.D. Candidate in the Department of Industrial Engineering and Operations Research at University of California, Berkeley, where she is advised by Prof. Zuo-Jun (Max) Shen. Previously, she graduated from Tsinghua University with a B.S. in Physics. Her research focuses on developing more automatic and robust data-driven solutions for decision-making with uncertainty, combining tools and concepts from optimization, machine learning, and statistics. From an applications perspective, her research focuses on supply chain management and retail operations. As a part of it, she actively collaborates with industrial partners in e-commerce.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EBig data provides new opportunities to tackle one of the main difficulties in decision-making systems \u0026ndash; uncertain behavior driven by the unknown probability distribution. Instead of the classical two-step predict-then-optimize (PTO) procedure, we provide smarter data-driven solutions by integrating these two steps. In the first half of this talk, we focus on a multi-period inventory replenishment problem with uncertain demand and vendor lead time (VLT), with accessibility to a large quantity of historical data. Different from the traditional two-step predict-then-optimize (PTO) solution framework, we propose a one-step end-to-end (E2E) framework that uses deep-learning models to output the suggested replenishment amount directly from input features without any intermediate step. The E2E model is trained to capture the behavior of the optimal dynamic programming solution under historical observations, without any prior assumptions on the distributions of the demand and the VLT. This algorithm is currently implemented in production at JD.com to replenish thousands of products. In the second half of this talk, I will move to a more general setting of the contextual stochastic optimization problem. We propose an integrated conditional estimation-optimization (ICEO) framework that estimates the underlying conditional distribution using data while considering the structure of the downstream optimization problem. We show that our ICEO approach is asymptotically consistent and further provide finite performance guarantees in the form of generalization bounds. We also discuss the computational difficulties of performing the ICEO approach and propose a general methodology by approximating the potential non-differentiable oracle. We also provide a polynomial optimization solution approach in the semi-algebraic case. The concept of E2E, which uses the input information directly for the ultimate goal, shortens the decision process and can also be useful in practice for a wide range of circumstances beyond supply chain management.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Smarter data-driven decision-making by integrating prediction and optimization"}],"uid":"34977","created_gmt":"2021-11-22 13:23:18","changed_gmt":"2021-11-22 13:23:18","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-12-02T11:00:00-05:00","event_time_end":"2021-12-02T12:00:00-05:00","event_time_end_last":"2021-12-02T12:00:00-05:00","gmt_time_start":"2021-12-02 16:00:00","gmt_time_end":"2021-12-02 17:00:00","gmt_time_end_last":"2021-12-02 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652991":{"#nid":"652991","#data":{"type":"event","title":"ISyE Seminar - Chamsi Hssaine ","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EPseudo-Competitive Games and Algorithmic Pricing\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAlgorithmic pricing is increasingly a staple of e-commerce platform operations; however, while such data-driven pricing techniques are known to work well in non-strategic environments, their performance in competitive settings remains poorly understood. To this end, we investigate market outcomes that may arise when multiple competing firms deploy local price experimentation algorithms while treating their market environment as a black-box. For price-competition games induced by a broad class of well-validated customer behavior models, we demonstrate that price trajectories resulting from\u0026nbsp;natural local learning dynamics may converge to outcomes in which firms can experience unbounded losses in revenue compared to the best price equilibrium. We moreover design a novel learning algorithm to address this concern.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis work falls under a broader range of questions in people-centric operations, wherein new markets and platforms fail to fully harness advances in optimization and AI due to inadequately accounting for the utilities of agents, firms, and society as a whole. Such questions arise both in competitive settings, as discussed\u0026nbsp;above, but also in collaborative settings; I will highlight this in the latter part of my talk by briefly discussing my work on the design of multi-modal transportation systems.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EChamsi Hssaine is a final-year Ph.D. candidate in the School of Operations Research and Information Engineering at Cornell University, where she is advised by Professor Sid Banerjee. She\u0026nbsp;graduated \u003Cem\u003Emagna cum laude\u003C\/em\u003E from Princeton University in 2016, with a B.S. in Operations Research and Financial Engineering. Her research centers around algorithm and incentive design for smart societal systems, with a focus on incorporating more realistic models of behavior under incentives, and better understanding the effect of policy decisions on stakeholders. Chamsi was selected for the 2020 Rising Stars in EECS workshop at UC Berkeley, as well as the 2020 Rising Scholars conference at the Stanford Graduate School of Business. In 2019, she was a visitor at the Simons Institute for the program on Online and Matching-Based Market Design. Her paper \u0026quot;Real-Time Approximate Routing for Smart Transit Systems\u0026quot; (joint with Sid Banerjee, No\u0026eacute;mie P\u0026eacute;rivier, and Samitha Samaranayake) was a finalist for the 2021 INFORMS Minority Issues Forum Paper Competition.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAlgorithmic pricing is increasingly a staple of e-commerce platform operations; however, while such data-driven pricing techniques are known to work well in non-strategic environments, their performance in competitive settings remains poorly understood. To this end, we investigate market outcomes that may arise when multiple competing firms deploy local price experimentation algorithms while treating their market environment as a black-box. For price-competition games induced by a broad class of well-validated customer behavior models, we demonstrate that price trajectories resulting from\u0026nbsp;natural local learning dynamics may converge to outcomes in which firms can experience unbounded losses in revenue compared to the best price equilibrium. We moreover design a novel learning algorithm to address this concern.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis work falls under a broader range of questions in people-centric operations, wherein new markets and platforms fail to fully harness advances in optimization and AI due to inadequately accounting for the utilities of agents, firms, and society as a whole. Such questions arise both in competitive settings, as discussed\u0026nbsp;above, but also in collaborative settings; I will highlight this in the latter part of my talk by briefly discussing my work on the design of multi-modal transportation systems.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Pseudo-Competitive Games and Algorithmic Pricing"}],"uid":"34977","created_gmt":"2021-11-18 15:26:10","changed_gmt":"2021-11-18 15:26:10","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-30T11:00:00-05:00","event_time_end":"2021-11-30T12:00:00-05:00","event_time_end_last":"2021-11-30T12:00:00-05:00","gmt_time_start":"2021-11-30 16:00:00","gmt_time_end":"2021-11-30 17:00:00","gmt_time_end_last":"2021-11-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650239":{"#nid":"650239","#data":{"type":"event","title":"ISyE Department Seminar - Dmitriy Drusvyatskiy","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EStochastic optimization under distributional shifts\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ELearning problems commonly exhibit an interesting feedback\u003Cbr \/\u003E\r\nmechanism wherein the population data reacts to decision makers\u0026#39;\u003Cbr \/\u003E\r\nactions. This is the case for example when members of the population\u003Cbr \/\u003E\r\nrespond to a deployed classifier by manipulating their features so as\u003Cbr \/\u003E\r\nto improve the likelihood of being positively labeled. In this way,\u003Cbr \/\u003E\r\nthe population is manipulating the learning process by distorting the\u003Cbr \/\u003E\r\ndata distribution that is accessible to the\u0026nbsp;learner. In this talk, I will\u0026nbsp;present some recent modelling frameworks and algorithms for dynamic\u0026nbsp;problems of this type, rooted in stochastic optimization and game\u0026nbsp;theory.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nJoint work with Evan Faulkner (UW), Maryam Fazel (UW), Adhyyan Narang\u003Cbr \/\u003E\r\n(UW), Lillian J. Ratliff (UW), Lin Xiao (Facebook AI)\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EDmitriy Drusvyatskiy received his PhD from the Operations\u003Cbr \/\u003E\r\nResearch and Information Engineering department at Cornell University\u003Cbr \/\u003E\r\nin 2013, followed by a post doctoral appointment in the Combinatorics\u003Cbr \/\u003E\r\nand Optimization department at Waterloo, 2013-2014. He joined the\u003Cbr \/\u003E\r\nMathematics department at University of Washington as an Assistant\u003Cbr \/\u003E\r\nProfessor in 2014, and was promoted to an Associate Professor in 2019.\u003Cbr \/\u003E\r\nDmitriy\u0026#39;s research broadly focuses on designing and analyzing\u003Cbr \/\u003E\r\nalgorithms for large-scale optimization problems, primarily motivated\u003Cbr \/\u003E\r\nby applications in data science. Dmitriy has received a number of\u003Cbr \/\u003E\r\nawards, including the Air Force Office of Scientific Research (AFOSR)\u003Cbr \/\u003E\r\nYoung Investigator Program (YIP) Award, NSF CAREER, INFORMS\u003Cbr \/\u003E\r\nOptimization Society Young Researcher Prize 2019, and finalist\u003Cbr \/\u003E\r\ncitations for the Tucker Prize 2015 and the Young Researcher Best\u003Cbr \/\u003E\r\nPaper Prize at ICCOPT 2019. Dmitriy is currently a co-PI of the NSF\u003Cbr \/\u003E\r\nfunded Transdisciplinary Research in Principles of Data Science\u003Cbr \/\u003E\r\n(TRIPODS) institute at University of Washington.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nResearch currently supported by NSF CAREER DMS 1651851 and NSF CCF 1740551.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ELearning problems commonly exhibit an interesting feedback\u003Cbr \/\u003E\r\nmechanism wherein the population data reacts to decision makers\u0026#39;\u003Cbr \/\u003E\r\nactions. This is the case for example when members of the population\u003Cbr \/\u003E\r\nrespond to a deployed classifier by manipulating their features so as\u003Cbr \/\u003E\r\nto improve the likelihood of being positively labeled. In this way,\u003Cbr \/\u003E\r\nthe population is manipulating the learning process by distorting the\u003Cbr \/\u003E\r\ndata distribution that is accessible to the\u0026nbsp;learner. In this talk, I will\u003C\/p\u003E\r\n\r\n\u003Cp\u003Epresent some recent modelling frameworks and algorithms for dynamic\u003Cbr \/\u003E\r\nproblems of this type, rooted in stochastic optimization and game\u003Cbr \/\u003E\r\ntheory.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nJoint work with Evan Faulkner (UW), Maryam Fazel (UW), Adhyyan Narang\u003Cbr \/\u003E\r\n(UW), Lillian J. Ratliff (UW), Lin Xiao (Facebook AI)\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Stochastic optimization under distributional shifts"}],"uid":"34868","created_gmt":"2021-08-30 19:55:22","changed_gmt":"2021-11-16 17:43:07","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-19T11:00:00-05:00","event_time_end":"2021-11-19T12:00:00-05:00","event_time_end_last":"2021-11-19T12:00:00-05:00","gmt_time_start":"2021-11-19 16:00:00","gmt_time_end":"2021-11-19 17:00:00","gmt_time_end_last":"2021-11-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652703":{"#nid":"652703","#data":{"type":"event","title":"ISyE Seminar - Nils Boysen","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EE-commerce warehousing and some new results on picker routing\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn the wake of ever-increasing e-commerce sales, warehouses have evolved to technology-enriched, mission-critical fulfillment factories. This talk reviews suitable e-commerce warehouse structures such as scattered storage and robot-assisted order picking and investigates the routing problems that are to be solved within these novel warehouses. In the very core of traditional picker-to-parts warehouses is the classical picker routing problem, which equals the traveling salesman problem (TSP) but is well-known to be efficiently solvable in the parallel-aisle structure of warehouses. New warehouses require the solution of other well-known extended routing problems, such as the clustered TSP, the generalized TSP, and the prize collecting TSP. All these routing problems are well-known to be strongly NP-hard for general graphs. This talk shows how the warehouse structure impacts this complexity status and how the parallel-aisle structure of warehouses can be exploited to improve the efficiency of routing algorithms.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EAfter some industry practice at IBM Global Services, Nils joined the Friedrich Schiller University in Jena (Germany), where he became a full professor for operations management. His main research interests are in the fields of facility logistics, warehousing, transportation, and automobile production. To solve industry problems in these areas, Nils applies mathematical modelling and combinatorial optimization techniques, always based on a thorough analysis of computational complexity. He has published over 150 research papers in many of the top optimization and logistics journals. Among others he is a member of the editorial boards of Transportation Science and EJOR.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIn the wake of ever-increasing e-commerce sales, warehouses have evolved to technology-enriched, mission-critical fulfillment factories. This talk reviews suitable e-commerce warehouse structures such as scattered storage and robot-assisted order picking and investigates the routing problems that are to be solved within these novel warehouses. In the very core of traditional picker-to-parts warehouses is the classical picker routing problem, which equals the traveling salesman problem (TSP) but is well-known to be efficiently solvable in the parallel-aisle structure of warehouses. New warehouses require the solution of other well-known extended routing problems, such as the clustered TSP, the generalized TSP, and the prize collecting TSP. All these routing problems are well-known to be strongly NP-hard for general graphs. This talk shows how the warehouse structure impacts this complexity status and how the parallel-aisle structure of warehouses can be exploited to improve the efficiency of routing algorithms.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"E-commerce warehousing and some new results on picker routing"}],"uid":"34977","created_gmt":"2021-11-11 13:44:42","changed_gmt":"2021-11-11 13:44:42","author":"Julie Smith","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-12-06T11:00:00-05:00","event_time_end":"2021-12-06T12:00:00-05:00","event_time_end_last":"2021-12-06T12:00:00-05:00","gmt_time_start":"2021-12-06 16:00:00","gmt_time_end":"2021-12-06 17:00:00","gmt_time_end_last":"2021-12-06 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"652569":{"#nid":"652569","#data":{"type":"event","title":"DCL Seminar Speaker - Abhishek Gupta","body":[{"value":"\u003Cp\u003ETITLE: Cyberattack Detection through Dynamic Watermarking\u003C\/p\u003E\r\n\r\n\u003Cp\u003EABSTRACT:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDynamic watermarking, as an active intrusion detection technique, can potentially detect replay attacks, spoofing attacks, and deception attacks in the feedback channel for control systems. In this talk, we will discuss our recent work on a novel dynamic watermarking algorithm for finite-state finite-action Markov decision processes and present bounds on the mean time between false alarms, and the mean delay between the time an attack occurs and when it is detected. We further compute the sensitivity of the performance of the control system as a function of the watermark. We demonstrate the effectiveness of the proposed dynamic watermarking algorithm by detecting a spoofing attack in a sensor network system.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio: Abhishek Gupta is an assistant professor at Electrical and Computer Engineering at The Ohio State University. He completed his Ph.D. in Aerospace Engineering (2014), MS in Applied Mathematics (2012), and MS in Aerospace Engineering (2011), all from University of Illinois at Urbana-Champaign (UIUC). He completed his undergraduate in Aerospace Engineering from Indian Institute of Technology, Bombay, India (2005-09). His research develops new theory and algorithms for stochastic control problems, games, and optimization problems, with applications to secure cyberphysical systems and develop market mechanisms for deep renewable integration. He is a recipient of Kenneth Lee Herrick Memorial Award at UIUC and Lumley Research Award at OSU.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Cyberattack Detection through Dynamic Watermarking"}],"uid":"34470","created_gmt":"2021-11-08 20:12:23","changed_gmt":"2021-11-08 20:12:23","author":"phand3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-16T11:00:00-05:00","event_time_end":"2021-11-16T12:00:00-05:00","event_time_end_last":"2021-11-16T12:00:00-05:00","gmt_time_start":"2021-11-16 16:00:00","gmt_time_end":"2021-11-16 17:00:00","gmt_time_end_last":"2021-11-16 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650238":{"#nid":"650238","#data":{"type":"event","title":"ISyE Department Seminar- Karen Smilowitz","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EIntegrating dual scheduling modes in workforce management\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMotivated by the emergence of self-scheduling platforms for volunteers and the continued need to meet time-specific needs of nonprofit organizations, this research explores modeling approaches and scheduling policies to effectively manage workforce scheduling for organizations with dual scheduling modes.\u0026nbsp; As an illustrative example, we consider a nonprofit organization that provides relief to those impacted by disasters using both volunteers who schedule themselves and staff members who are assigned to shifts.\u0026nbsp; We explore the advantages of scheduling policies that explicitly account for the two groups, balancing the need to cover time slots to meet demand with the desire to offer meaningful and convenient opportunities to volunteers such that they maintain their engagement with the organization.\u0026nbsp; We present a case study based on operational data from our collaborators and more general insights based on synthesized data.\u0026nbsp; This is joint work with Mariana Escallon-Barrios and Reut Noham.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EDr. Karen Smilowitz is the James N. and Margie M. Krebs Professor in Industrial Engineering and Management Science at Northwestern University, with a joint appointment in the Operations group at the Kellogg School of Business.\u0026nbsp; Dr. Smilowitz is an expert in modeling and solution approaches for logistics and transportation systems in both commercial and nonprofit applications.\u0026nbsp; Dr.\u0026nbsp; Smilowitz is the founder of the Northwestern Initiative on Humanitarian and Nonprofit Logistics.\u0026nbsp; She has been instrumental in promoting the use of operations research within the humanitarian and nonpro\ufb01t sectors through the Woodrow Wilson International Center for Scholars, the American Association for the Advancement of Science, and the National Academy of Engineering, as well as various media outlets.\u0026nbsp; Dr. Smilowitz is the Editor-in-Chief of \u003Cem\u003ETransportation Science\u003C\/em\u003E.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch3\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EMotivated by the emergence of self-scheduling platforms for volunteers and the continued need to meet time-specific needs of nonprofit organizations, this research explores modeling approaches and scheduling policies to effectively manage workforce scheduling for organizations with dual scheduling modes.\u0026nbsp; As an illustrative example, we consider a nonprofit organization that provides relief to those impacted by disasters using both volunteers who schedule themselves and staff members who are assigned to shifts.\u0026nbsp; We explore the advantages of scheduling policies that explicitly account for the two groups, balancing the need to cover time slots to meet demand with the desire to offer meaningful and convenient opportunities to volunteers such that they maintain their engagement with the organization.\u0026nbsp; We present a case study based on operational data from our collaborators and more general insights based on synthesized data.\u0026nbsp; This is joint work with Mariana Escallon-Barrios and Reut Noham.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Integrating dual scheduling modes in workforce management"}],"uid":"34868","created_gmt":"2021-08-30 19:53:51","changed_gmt":"2021-11-08 19:53:05","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-12T11:00:00-05:00","event_time_end":"2021-11-12T12:00:00-05:00","event_time_end_last":"2021-11-12T12:00:00-05:00","gmt_time_start":"2021-11-12 16:00:00","gmt_time_end":"2021-11-12 17:00:00","gmt_time_end_last":"2021-11-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"651358":{"#nid":"651358","#data":{"type":"event","title":"SCL November 2021 Supply Chain Days","body":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our second fall Supply Chain Days! We will be hosting both an On Campus (Nov 11) and a Virtual session\u0026nbsp;(Nov 12). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThursday, November 11\u0026nbsp;| 11am-2pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, November 12\u0026nbsp;|\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EEVENT SPONSOR\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe event is sponsored through the generosity and support of the CSCMP Atlanta Roundtable. Students, young professionals, academics and military personnel are eligible for a discounted membership. Make sure to stop by the Atlanta CSCMP table at our on campus event and visit \u003Ca href=\u0022https:\/\/nam11.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.atlantacscmp.org%2Fjoin\u0026amp;data=04%7C01%7Ccprovost%40arcodb.com%7C34cdc3eea54b4debfdba08d99b20f203%7Cdb0fc84b83004d5a9d1800141c8513e2%7C0%7C0%7C637711388091063721%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000\u0026amp;sdata=Z%2BVb4Eo4ELSRLcuELW4IJQcskE72Tg6LVyLmwWwqYQo%3D\u0026amp;reserved=0\u0022\u003Ehttps:\/\/www.atlantacscmp.org\/join\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our second fall Supply Chain Days! We will be hosting both an On Campus (Nov 11) and a Virtual session\u0026nbsp;(Nov 12). Please note that you need to register separately for each event to attend.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Events where industry supply chain representatives meet with Georgia Tech Supply Chain students"}],"uid":"27233","created_gmt":"2021-10-04 18:51:21","changed_gmt":"2021-11-03 14:56:11","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-11T11:00:00-05:00","event_time_end":"2021-11-12T14:00:00-05:00","event_time_end_last":"2021-11-12T14:00:00-05:00","gmt_time_start":"2021-11-11 16:00:00","gmt_time_end":"2021-11-12 19:00:00","gmt_time_end_last":"2021-11-12 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"651357":{"id":"651357","type":"image","title":"SCL November 2021 Supply Chain Days","body":null,"created":"1633373432","gmt_created":"2021-10-04 18:50:32","changed":"1635951539","gmt_changed":"2021-11-03 14:58:59","alt":"SCL November 2021 Supply Chain Days","file":{"fid":"247519","name":"homepage-scday3_202111-600px.jpg","image_path":"\/sites\/default\/files\/images\/homepage-scday3_202111-600px.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/homepage-scday3_202111-600px.jpg","mime":"image\/jpeg","size":84733,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/homepage-scday3_202111-600px.jpg?itok=okMa-Yvu"}}},"media_ids":["651357"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/outreach\/supplychainday","title":"Register online to attend (for Georgia Tech students)"},{"url":"https:\/\/www.scl.gatech.edu","title":"Supply Chain and Logistics Institute website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"780","name":"employment"},{"id":"9845","name":"GTSCL"},{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"1996","name":"Recruiting"},{"id":"5172","name":"career day"},{"id":"122741","name":"physical internet"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"652053":{"#nid":"652053","#data":{"type":"event","title":"2020 Monie A. Ferst Award Symposium","body":[{"value":"\u003Cp\u003ETo view the program and event details, visit \u003Ca href=\u0022https:\/\/sites.gatech.edu\/2020-monie-a-ferst-award-symposium\/\u0022\u003Ehttps:\/\/sites.gatech.edu\/2020-monie-a-ferst-award-symposium. \u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"In Honor of C.F. Jeff Wu, Coca-Cola Chair in Engineering Statistics and Professor, H. Milton Stewart School of Industrial and Systems Engineering"}],"uid":"34760","created_gmt":"2021-10-26 12:23:16","changed_gmt":"2021-10-26 14:29:50","author":"Laurie Haigh","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-11T08:00:00-05:00","event_time_end":"2021-11-11T17:15:00-05:00","event_time_end_last":"2021-11-11T17:15:00-05:00","gmt_time_start":"2021-11-11 13:00:00","gmt_time_end":"2021-11-11 22:15:00","gmt_time_end_last":"2021-11-11 22:15:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.isye.gatech.edu\/news\/jeff-wu-receives-sigma-xis-monie-ferst-award","title":"Jeff Wu Receives Sigma Xi\u2019s Monie A. Ferst Award"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"7879","name":"Jeff Wu"},{"id":"136851","name":"Monie A. Ferst Award"},{"id":"92891","name":"Georgia Tech Sigma Xi"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1789","name":"Conference\/Symposium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:sigmaxi@me.gatech.edu?subject=2020%20Monie%20A.%20Ferst%20Award%20Symposium\u0022\u003ESigma Xi\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"651933":{"#nid":"651933","#data":{"type":"event","title":" RELEX Solutions Information Session at ISyE","body":[{"value":"\u003Cp\u003EJoin us to learn about RELEX Solutions and opportunities relating to technical and business consulting positions!\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPlease\u0026nbsp;\u003Ca href=\u0022https:\/\/georgiatechsupplychainandlogisticsinstitute.cmail19.com\/t\/r-l-trlidhht-uritiykyki-v\/\u0022\u003E\u003Cstrong\u003ERSVP to attend\u003C\/strong\u003E\u003C\/a\u003E, so we have enough representatives and food for the attendees.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EJoin us to learn about RELEX Solutions and opportunities relating to technical and business consulting positions!\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"GT Students, join us at ISyE to learn about RELEX and their open positions."}],"uid":"27233","created_gmt":"2021-10-21 18:15:41","changed_gmt":"2021-10-21 18:19:26","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-10T11:00:00-05:00","event_time_end":"2021-11-10T12:30:00-05:00","event_time_end_last":"2021-11-10T12:30:00-05:00","gmt_time_start":"2021-11-10 16:00:00","gmt_time_end":"2021-11-10 17:30:00","gmt_time_end_last":"2021-11-10 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"651934":{"id":"651934","type":"image","title":"RELEX Solutions Information Session","body":null,"created":"1634840317","gmt_created":"2021-10-21 18:18:37","changed":"1634840317","gmt_changed":"2021-10-21 18:18:37","alt":"","file":{"fid":"247345","name":"RELEX Solutions information session.jpg","image_path":"\/sites\/default\/files\/images\/RELEX%20Solutions%20information%20session.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/RELEX%20Solutions%20information%20session.jpg","mime":"image\/jpeg","size":293814,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/RELEX%20Solutions%20information%20session.jpg?itok=I3BduHr-"}}},"media_ids":["651934"],"related_links":[{"url":"https:\/\/forms.office.com\/r\/9dAXdp26GV","title":"Register Online to Attend"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/event_files\/RELEX_Solutions-InformationSession_20211110.pdf","title":"Event flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"122741","name":"physical internet"},{"id":"3615","name":"information session"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Eevent@scl.gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"650236":{"#nid":"650236","#data":{"type":"event","title":"ISyE Department Seminar- Jianqing Fan","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Understanding Deep Q-learning\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp;Despite the great empirical success of deep reinforcement learning, its theoretical foundation is less well understood. In this work, we make the first attempt to theoretically understand the deep Q-network (DQN) algorithm from both algorithmic and statistical perspectives. Specifically, we focus on a slight simplification of DQN that fully captures its key features. Under mild assumptions, we establish the algorithmic and statistical rates of convergence for the action-value functions of the iterative policy sequence obtained by DQN. In particular, the statistical error characterizes the bias and variance that arise from approximating the action-value function using a deep neural network, while the algorithmic error converges to zero at a geometric rate. As a byproduct, our analysis provides justifications for the techniques of experience replay and target network, which are crucial to the empirical success of DQN. Furthermore, as a simple extension of DQN, we propose the Minimax-DQN algorithm for zero-sum Markov game with two players. Borrowing the analysis of DQN, we also quantify the difference between the policies obtained by Minimax-DQN and the Nash equilibrium of the Markov game in terms of both the algorithmic and statistical rates of convergence.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Jianqing Fan is a statistician, financial econometrician, and data scientist. He is Frederick L. Moore \u0026#39;18 Professor of Finance, Professor of Statistics, and Professor of Operations Research and Financial Engineering at the Princeton University where he chaired the department from 2012 to 2015. He is the winner of The 2000 COPSS Presidents\u0026#39; Award, Morningside Gold Medal for Applied Mathematics (2007), Guggenheim Fellow (2009), Pao-Lu Hsu Prize (2013) and Guy Medal in Silver (2014). He got elected to Academician from Academia Sinica in 2012.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDespite the great empirical success of deep reinforcement learning, its theoretical foundation is less well understood. In this work, we make the first attempt to theoretically understand the deep Q-network (DQN) algorithm from both algorithmic and statistical perspectives. Specifically, we focus on a \u0026nbsp;slight simplification of DQN that fully captures its key features. Under mild assumptions, we establish the algorithmic and statistical rates of convergence for the action-value functions of the iterative policy sequence \u0026nbsp;obtained by DQN. In particular, the statistical error characterizes the bias and variance that arise from approximating the action-value function using deep neural network, while the algorithmic error converges to zero at a geometric rate. As a byproduct, our analysis provides justifications for the techniques of experience replay and target network, which are crucial to the empirical success of DQN. Furthermore, as a simple extension of \u0026nbsp;DQN, we \u0026nbsp; propose the Minimax-DQN algorithm for zero-sum Markov game with two players. \u0026nbsp;Borrowing the analysis of DQN, we also quantify the difference between \u0026nbsp;the \u0026nbsp; policies \u0026nbsp; obtained by Minimax-DQN \u0026nbsp;and \u0026nbsp;the Nash equilibrium of the Markov game \u0026nbsp; \u0026nbsp; in terms of both the algorithmic and statistical rates of convergence.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Understanding Deep Q-Learning "}],"uid":"34868","created_gmt":"2021-08-30 19:50:06","changed_gmt":"2021-10-18 14:26:57","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-22T12:00:00-04:00","event_time_end":"2021-10-22T13:00:00-04:00","event_time_end_last":"2021-10-22T13:00:00-04:00","gmt_time_start":"2021-10-22 16:00:00","gmt_time_end":"2021-10-22 17:00:00","gmt_time_end_last":"2021-10-22 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"651666":{"#nid":"651666","#data":{"type":"event","title":"Public Health Logistics and Supply Chain Management in the COVID-19 Era","body":[{"value":"\u003Cdiv\u003E\r\n\u003Ch2\u003EAbout this event\u003C\/h2\u003E\r\n\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cp\u003EThe ongoing pandemic is demonstrating the importance of supply chains and logistics in the distribution of healthcare resources. The lack of resilience and agility of these systems has contributed to limited and unbalanced availability of critical resources, leading to the shortage and wastage of resources in different parts of the world. The 2021 Humanitarian Forum will focus on such disparities as well as policies and operational solutions to reduce them.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EA Zoom link will be sent to you after \u003Ca href=\u0022https:\/\/www.eventbrite.com\/e\/public-health-logistics-and-supply-chain-management-in-the-covid-19-era-tickets-170201769073\u0022\u003Eregistration\u003C\/a\u003E.\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EPanelists: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003ENicole Lurie, MD, MSPH\u003C\/strong\u003E, U.S. Director and Strategic Advisor to the CEO at the \u003Ca href=\u0022https:\/\/cepi.net\/\u0022 rel=\u0022nofollow noopener noreferrer\u0022 target=\u0022_blank\u0022\u003ECoalition for Epidemic Preparedness Innovations (CEPI)\u003C\/a\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EJean-Cedric Meeus\u003C\/strong\u003E, Chief Global Transport Supply Division at \u003Ca href=\u0022https:\/\/sn.linkedin.com\/in\/jean-cedric-meeus-22950078\u0022 rel=\u0022nofollow noopener noreferrer\u0022 target=\u0022_blank\u0022\u003EUNICEF\u003C\/a\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EPrashant Yadav, PhD\u003C\/strong\u003E,\u003Cstrong\u003E \u003C\/strong\u003ESenior Fellow at the \u003Ca href=\u0022https:\/\/www.cgdev.org\/expert\/prashant-yadav\u0022 rel=\u0022nofollow noopener noreferrer\u0022 target=\u0022_blank\u0022\u003ECenter for Global Development\u003C\/a\u003E\u003C\/li\u003E\r\n\t\u003Cli\u003E\u003Cstrong\u003EModerator: Mathieu Dahan, PhD\u003C\/strong\u003E,\u003Cstrong\u003E \u003C\/strong\u003EAssistant Professor at the \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/mathieu-dahan\u0022 rel=\u0022nofollow noopener noreferrer\u0022 target=\u0022_blank\u0022\u003EGeorgia Institute of Technology\u003C\/a\u003E\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EThis event is co-organized by the Consulate General of France in Atlanta, the Center for Humanitarian Emergencies and the Office for Global Strategy and Initiatives at Emory University, and the School of Industrial and Systems Engineering and the Center for Health and Humanitarian Systems at Georgia Tech.\u003C\/em\u003E\u003C\/p\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EA discussion on speed, efficiency, and equity in the allocation of limited public health resources in the era of COVID-19 and beyond.\u003C\/strong\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A discussion on speed, efficiency, and equity in the allocation of limited public health resources in the era of COVID-19 and beyond."}],"uid":"34760","created_gmt":"2021-10-13 16:00:45","changed_gmt":"2021-10-14 19:54:48","author":"Laurie Haigh","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-15T11:00:00-04:00","event_time_end":"2021-10-15T12:00:00-04:00","event_time_end_last":"2021-10-15T12:00:00-04:00","gmt_time_start":"2021-10-15 15:00:00","gmt_time_end":"2021-10-15 16:00:00","gmt_time_end_last":"2021-10-15 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"651667":{"id":"651667","type":"image","title":"Public Health Logistics and Supply Chain Management in the COVID-19 Era","body":null,"created":"1634142910","gmt_created":"2021-10-13 16:35:10","changed":"1634142925","gmt_changed":"2021-10-13 16:35:25","alt":"Public Health Logistics and Supply Chain Management in the COVID-19 Era","file":{"fid":"247231","name":"public_Health_SCM-Covid.jpg","image_path":"\/sites\/default\/files\/images\/public_Health_SCM-Covid.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/public_Health_SCM-Covid.jpg","mime":"image\/jpeg","size":62207,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/public_Health_SCM-Covid.jpg?itok=tpAwcntu"}}},"media_ids":["651667"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"755","name":"public health"},{"id":"184289","name":"covid-19"},{"id":"167240","name":"Supply Chain Management"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650234":{"#nid":"650234","#data":{"type":"event","title":"ISyE Department Seminar- Oktay Gunluk-CANCELLED","body":"","field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EWe consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints. We formulate the problem as an integer program that maximizes classification accuracy with explicit constraints on equality of opportunity and equalized odds metrics. A column generation framework is used to efficiently search over exponentially many possible rules, eliminating the need for heuristic rule mining. Compared to other interpretable machine learning algorithms, our method produces interpretable classifiers that have superior performance with respect to the fairness metric.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Connor Lawless\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"An integer programming approach for Fair and Interpretable Binary Classification"}],"uid":"34868","created_gmt":"2021-08-30 19:47:35","changed_gmt":"2021-10-06 12:41:48","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-08T12:00:00-04:00","event_time_end":"2021-10-08T13:00:00-04:00","event_time_end_last":"2021-10-08T13:00:00-04:00","gmt_time_start":"2021-10-08 16:00:00","gmt_time_end":"2021-10-08 17:00:00","gmt_time_end_last":"2021-10-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: An integer programming approach for Fair and Interpretable Binary Classification\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E. We consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints. We formulate the problem as an integer program that maximizes classification accuracy with explicit constraints on equality of opportunity and equalized odds metrics. A column generation framework is used to efficiently search over exponentially many possible rules, eliminating the need for heuristic rule mining. Compared to other interpretable machine learning algorithms, our method produces interpretable classifiers that have superior performance with respect to the fairness metric.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Connor Lawless\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E: Oktay Gunluk joined the School of Operations Research and Information Engineering faculty in January 2020. Before joining Cornell, he was the manager of the Mathematical Optimization and Algorithms group at IBM Research. He has also spent three years as a researcher in the Operations Research group in AT\u0026amp;T Labs. At both of these industrial labs, in addition to basic research in mathematical optimization, he has worked on various large-scale applied optimization projects for internal and external customers. His main research interests are related to theoretical and computational aspects of discrete optimization problems, mainly in the area of integer programing. In particular, his main body of work is in the area of cutting planes for mixed-integer sets. Some of his recent work focuses on developing integer programming-based approaches to classification problems in machine learning. He has B.S.\/M.S. degrees in Industrial Engineering from Bo\u011fazi\u0026ccedil;i University, and M.S.\/Ph.D. degrees in Operations Research) from Columbia University.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"650233":{"#nid":"650233","#data":{"type":"event","title":"ISyE Department Seminar- Rhonda Righter","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Service and Matching Systems with Compatibility Constraints\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E In large service systems, such as cloud computing systems, there are different classes of jobs and of servers such that each job class can only be done on a subset of the server classes, due to data locality and other constraints. Similarly, there are often compatibility constraints in dynamic matching systems such as platforms for car sharing and waitlists for organ transplants. Under Markovian assumptions, the steady-state distributions for such systems have been shown to have a simple \u0026ldquo;product-form\u0026rdquo; structure.\u0026nbsp; I will describe a unified framework for these models that provides a common simple proof for the product-form results at a detailed state description and provides a simple, state-aggregated, view for analyzing waiting time distributions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Ivo Adan, Igor Kleiner, Kristen Gardner, and Gideon Weis\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Rhonda Righter is a Professor and past Chair of the Department of\u0026nbsp;Industrial Engineering and Operations Research at the University of\u0026nbsp;California, Berkeley. Before joining the faculty at Berkeley she taught at the Leavey School of Business at Santa Clara University. Her PhD is\u0026nbsp;in Industrial Engineering and Operations Research from UC Berkeley, her\u0026nbsp;BS is in applied math and business from Carnegie Mellon. Her primary\u0026nbsp;research and teaching interests are in the general area of stochastic\u0026nbsp;modeling and optimization, especially as applied to service,\u0026nbsp;manufacturing, telecommunications, and large-scale computing systems.\u0026nbsp;She is an associate editor for Queueing Systems, Probability in the\u0026nbsp;Engineering and Informational Sciences, Stochastic Models, and the\u0026nbsp;INFORMS Service Science Journal. She has also served on the editorial\u0026nbsp;boards of Management Science, Operations Research, Operations Research\u0026nbsp;Letters, the Journal of Scheduling, and Naval Research Logistics. She is\u0026nbsp;the past (founding) Chair of the Applied Probability Society (APS) of\u0026nbsp;INFORMS and is currently Chair of the APS Prize Committee.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn large service systems, such as cloud computing systems, there are different classes of jobs and of servers such that each job class can only be done on a subset of the server classes, due to data locality and other constraints. Similarly, there are often compatibility constraints in dynamic matching systems such as platforms for car sharing and waitlists for organ transplants. Under Markovian assumptions, the steady-state distributions for such systems have been shown to have a simple \u0026ldquo;product-form\u0026rdquo; structure.\u0026nbsp; I will describe a unified framework for these models that provides a common simple proof for the product-form results at a detailed state description and provides a simple, state-aggregated, view for analyzing waiting time distributions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoint work with Ivo Adan, Igor Kleiner, Kristen Gardner, and Gideon Weiss\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Service and Matching Systems with Compatibility Constraints"}],"uid":"34868","created_gmt":"2021-08-30 19:46:09","changed_gmt":"2021-09-29 15:49:27","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-01T12:00:00-04:00","event_time_end":"2021-10-01T13:00:00-04:00","event_time_end_last":"2021-10-01T13:00:00-04:00","gmt_time_start":"2021-10-01 16:00:00","gmt_time_end":"2021-10-01 17:00:00","gmt_time_end_last":"2021-10-01 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650228":{"#nid":"650228","#data":{"type":"event","title":"ISyE Seminar- Robert Nowak","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E What Kinds of Functions Do Neural Networks Learn?\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAbstract: \u003C\/strong\u003ENeural nets have made an amazing comeback during the past decade. Their empirical success has been truly phenomenal, but neural nets are poorly understood in a mathematical sense compared to classical methods like splines, kernels, and wavelets.\u0026nbsp; This talk describes recent steps towards a mathematical theory of neural networks comparable to the foundations we have for classical nonparametric methods. Surprisingly, neural nets are minimax optimal in a wide variety of classical univariate function spaces, including those handled by splines and wavelets. In multivariate settings, neural nets are\u0026nbsp; solutions to data-fitting problems cast in entirely new types of multivariate function spaces characterized through total variation (TV) measured in the Radon transform domain.\u0026nbsp; And deep (multilayer) neural nets naturally represent compositions of functions in these Radon-BV (bounded variation) spaces.\u0026nbsp; Remarkably, this theory provides novel explanations for many notable empirical discoveries in deep learning, including the benefits of \u0026ldquo;skip connections\u0026rdquo; and sparse and low-rank \u0026ldquo;weight\u0026rdquo; matrices. Radon-BV spaces set the stage for the nonparametric theory of neural nets.\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\n\u003Cstrong\u003EBio:\u003C\/strong\u003E Rob holds the Nosbusch Professorship in Engineering at the University of Wisconsin-Madison. His research focuses on signal processing, machine learning, optimization, and statistics.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENeural nets have made an amazing comeback during the past decade. Their empirical success has been truly phenomenal, but neural nets are poorly understood in a mathematical sense compared to classical methods like splines, kernels, and wavelets.\u0026nbsp; This talk describes recent steps towards a mathematical theory of neural networks comparable to the foundations we have for classical nonparametric methods. Surprisingly, neural nets are minimax optimal in a wide variety of classical univariate function spaces, including those handled by splines and wavelets. In multivariate settings, neural nets are\u0026nbsp; solutions to data-fitting problems cast in entirely new types of multivariate function spaces characterized through total variation (TV) measured in the Radon transform domain.\u0026nbsp; And deep (multilayer) neural nets naturally represent compositions of functions in these Radon-BV (bounded variation) spaces.\u0026nbsp; Remarkably, this theory provides novel explanations for many notable empirical discoveries in deep learning, including the benefits of \u0026ldquo;skip connections\u0026rdquo; and sparse and low-rank \u0026ldquo;weight\u0026rdquo; matrices. Radon-BV spaces set the stage for the nonparametric theory of neural nets.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"What Kinds of Functions Do Neural Networks Learn?"}],"uid":"34868","created_gmt":"2021-08-30 19:42:50","changed_gmt":"2021-09-07 19:11:04","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-10T12:00:00-04:00","event_time_end":"2021-09-10T13:00:00-04:00","event_time_end_last":"2021-09-10T13:00:00-04:00","gmt_time_start":"2021-09-10 16:00:00","gmt_time_end":"2021-09-10 17:00:00","gmt_time_end_last":"2021-09-10 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650227":{"#nid":"650227","#data":{"type":"event","title":"ISyE Seminar- Elisa Long","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENursing Home Staff Networks and COVID-19\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESkilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EElisa Long is an Associate Professor of Decisions, Operations, and Technology Management at UCLA Anderson, and was previously on the faculty at the Yale School of Management. Her research spans topics in healthcare operations, including epidemic control, hospital resource allocation, breast cancer decision-making, and most recently, nursing home staff networks during the COVID pandemic. She teaches courses on Data \u0026amp; Decisions and Healthcare Analytics, and has received several teaching and research awards. She earned a PhD in Management Science \u0026amp; Engineering from Stanford, and a BS in Operations Research from Cornell.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESkilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Nursing Home Staff Networks and COVID-19"}],"uid":"34868","created_gmt":"2021-08-30 19:40:38","changed_gmt":"2021-09-01 15:58:44","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-03T12:00:00-04:00","event_time_end":"2021-09-03T13:00:00-04:00","event_time_end_last":"2021-09-03T13:00:00-04:00","gmt_time_start":"2021-09-03 16:00:00","gmt_time_end":"2021-09-03 17:00:00","gmt_time_end_last":"2021-09-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"650080":{"#nid":"650080","#data":{"type":"event","title":"Kohler Co. Information Session at ISyE","body":[{"value":"\u003Cp\u003ELearn about Kohler Co. and its Supply Chain Rotational Program, Internships and Co-op Opportunities! Please also note Kohler will be represented at both the On Campus and Virtual Supply Chain Day Recruiting events as well as the GT All Majors Career Fair.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn about Kohler Co. and its Supply Chain Rotational Program, Internships and Co-op Opportunities!\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"GT Students, join us at ISyE to learn about Kohler Co."}],"uid":"27233","created_gmt":"2021-08-25 16:53:05","changed_gmt":"2021-09-01 15:32:12","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-08T12:00:00-04:00","event_time_end":"2021-09-08T13:00:00-04:00","event_time_end_last":"2021-09-08T13:00:00-04:00","gmt_time_start":"2021-09-08 16:00:00","gmt_time_end":"2021-09-08 17:00:00","gmt_time_end_last":"2021-09-08 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"650079":{"id":"650079","type":"image","title":"Kohler Co. 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19:44:21","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-24T12:00:00-04:00","event_time_end":"2021-09-24T13:00:00-04:00","event_time_end_last":"2021-09-24T13:00:00-04:00","gmt_time_start":"2021-09-24 16:00:00","gmt_time_end":"2021-09-24 17:00:00","gmt_time_end_last":"2021-09-24 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate 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We will be hosting both On Campus (Sept 9) and Virtual (Sept 10) sessions. Please note that you will need to register separately for each session to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWe strongly encourage students to act now to seek full-time employment\u003C\/strong\u003E, \u003Cstrong\u003Einternships, and projects\u003C\/strong\u003E (rather than waiting until the end of the semester).\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EEVENT DETAILS\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Ch4\u003EOn Campus\/In-Person (ISyE Main Building Atrium)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThursday, September 9 | 10am-3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EVirtual\/Online\u0026nbsp;(Career Fair Plus)\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, September\u0026nbsp;10 |\u0026nbsp;9am - 3pm ET\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMORE INFORMATION AND EVENT REGISTRATION\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EVisit\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/outreach\/supplychainday\u003C\/a\u003E\u003C\/strong\u003E for a list of attending organizations and links to register.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EEVENT SPONSOR\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe event is sponsored through the generosity and support of the Association of Supply Chain Management. \u003Ca href=\u0022https:\/\/www.ascm.org\/membership-product\/\u0022\u003EJoin today\u003C\/a\u003E and start networking at local \u003Ca href=\u0022https:\/\/www.atlanta.ascm.org\/\u0022\u003EASCM Atlanta Chapter\u003C\/a\u003E events. Also\u0026nbsp;make sure to stop by the ASCM Atlanta Chapter table at the event.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech Supply Chain\u0026nbsp;students, please join us for our fall Supply Chain Days! We will be hosting both an On Campus (Sept 9) and a Virtual session\u0026nbsp;(Sept 10). 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It is no longer sufficient to manage a warehouse based on a simple, arbitrary \u0026ldquo;ABC\u0026rdquo; classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision \u0026ndash; such as where to store or where to pick product \u0026ndash; must be based on careful engineering and economic analysis. Each SKU must identify its own cheapest, fastest path through the warehouse to the customer and then compete with all the other SKUs for the necessary resources. This results in warehouse operations that are finely tuned to patterns of customer orders and maximally efficient. Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEssential learning for those who are seeking cost reductions through better handling methods. Also valuable for those who must replace, upgrade, or add material handling equipment.\u0026nbsp;The two-day course will include case examples and a guided exercise to ensure mastery of the techniques presented.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\r\n\r\n\u003Cp\u003ESupply chain and logistics consultants, supply chain engineers and analysts, facility engineers, and warehouse supervisors and team leaders\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EExchange space for time (or vice versa) to better meet business objectives.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand when to use dedicated storage and when to use shared storage.\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify the most convenient locations in a warehouse based on an economic model.\u003C\/li\u003E\r\n\t\u003Cli\u003EIdentify patterns in customer orders and exploit these to speed fulfillment.\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluate warehouse performance.\u003C\/li\u003E\r\n\t\u003Cli\u003EOptimally size and stock a forward pick area.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the best practices in order-picking.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EWarehouse performance\u003C\/li\u003E\r\n\t\u003Cli\u003EModern warehouse trade-offs\u003C\/li\u003E\r\n\t\u003Cli\u003ESize and stocking optimization\u003C\/li\u003E\r\n\t\u003Cli\u003EOrder-picking best practices\u003C\/li\u003E\r\n\t\u003Cli\u003EAutomation\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ECOURSE MATERIALS\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EOnline access to course material in electronic format\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAccess to an e-copy of the book \u0026ldquo;Warehouse \u0026amp; Distribution Science\u0026rdquo;\u0026nbsp;as well as access to an accompanying suite of software to aid in warehouse analytics and optimization.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ECOURSE PREREQUISITES\u003C\/h4\u003E\r\n\r\n\u003Cp\u003ENone.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003ECERTIFICATE INFORMATION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course is part of the \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/education\/professional-education\/courses#DOAD\u0022\u003EDistribution Operations Analysis \u0026amp; Design (DOAD) Certificate\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. 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The program is driven by key competency areas (contract development, negotiation and influence, financial analysis, etc..) and embeds team leadership and stakeholder management into every competency, case study, and class challenge.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERegister online at\u0026nbsp;\u003Ca href=\u0022https:\/\/bit.ly\/psmcert2021\u0022\u003Ehttps:\/\/bit.ly\/psmcert2021\u003C\/a\u003E to attend.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWHO SHOULD ATTEND\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EProcurement and supply management senior managers, directors and VPs with direct reports looking to deepen application skills and sharpen procurement leadership tools. ABOUT THE PRESENTER G\u0026rsquo;Sean Williams is a Lead Instructor for the Georgia Tech Supply Chain and Logistics Institute\u0026#39;s Procurement \u0026amp; Supply Management (PSM) Leadership Certificate courses where he leverages his experience in negotiating deals, managing contracts and leading global procurement teams. He is also Executive Director of SMS-Advisors\u0026rsquo; Supply Chain and Supplier Performance group. Prior to becoming a Partner at SMS-Advisors, G. Sean held various Procurement \u0026amp; Supply Management Manager and Director level positions in Corporate America for companies including\u0026nbsp;Intel, WestRock, and Bristol Myers Squibb. He is currently\u0026nbsp;Senior Director \/ Head of Indirect Procurement at Floor \u0026amp; Decor.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EPSM COURSE SERIES\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOffered throughout September 2021 virtually\/online. Learn more at\u0026nbsp; \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/PSM\u0022\u003Ehttps:\/\/www.scl.gatech.edu\/PSM\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EA free, half-hour informational webinar relating to our PSM Leadership program designed to accelerate the leadership and executive presence of professionals responsible for driving cost management and category sourcing excellence.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Attend this free webinar and receive a *discount code towards our \u0022Supply Chain Project Management: Fundamentals\u0022 course being held in Savannah, GA April 10-12, 2018."}],"uid":"27233","created_gmt":"2021-08-11 14:45:46","changed_gmt":"2021-08-11 17:53:33","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-08-20T14:00:00-04:00","event_time_end":"2021-08-20T14:30:00-04:00","event_time_end_last":"2021-08-20T14:30:00-04:00","gmt_time_start":"2021-08-20 18:00:00","gmt_time_end":"2021-08-20 18:30:00","gmt_time_end_last":"2021-08-20 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"649402":{"id":"649402","type":"image","title":"FREE Webinar: Procurement and Supply Management (PSM) Leadership Certificate Program, Fri, Aug 20, 1PM ET","body":null,"created":"1628692751","gmt_created":"2021-08-11 14:39:11","changed":"1628693250","gmt_changed":"2021-08-11 14:47:30","alt":"FREE Webinar: Procurement and Supply Management (PSM) Leadership Certificate Program, Fri, Aug 20, 1PM ET","file":{"fid":"246554","name":"webinar-PSM2021_403x403.jpg","image_path":"\/sites\/default\/files\/images\/webinar-PSM2021_403x403.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/webinar-PSM2021_403x403.jpg","mime":"image\/jpeg","size":47759,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/webinar-PSM2021_403x403.jpg?itok=bS45D0RK"}}},"media_ids":["649402"],"related_links":[{"url":"https:\/\/bit.ly\/psmcert2021","title":"Register Online to Attend"},{"url":"https:\/\/www.scl.gatech.edu\/PSM","title":"Course details within the SCL website"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-catalog.pdf","title":"SCL Course Catalog (PDF)"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"233","name":"Logistics"},{"id":"167074","name":"Supply Chain"},{"id":"634","name":"webinar"},{"id":"7695","name":"Procurement"},{"id":"110501","name":"purchasing"},{"id":"127851","name":"Negotiating"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:webinar@scl.gatech.edu\u0022\u003Ewebinar@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"648656":{"#nid":"648656","#data":{"type":"event","title":"SCL Course: World Class Sales and Operations Planning","body":[{"value":"\u003Ch4\u003ECOURSE DESCRIPTION\u003C\/h4\u003E\r\n\r\n\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n\r\n\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EChief Operating Officers, Supply Chain, Sales, Marketing and Finance Management Executives (Directors, VPs, EVPs)\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain and Logistics Managers, Consultants, Supervisors, Planners, and Engineers\u003C\/li\u003E\r\n\t\u003Cli\u003ESupply Chain Education and Human Resource Management personnel\u003C\/li\u003E\r\n\t\u003Cli\u003EInventory and Demand Planners\u003C\/li\u003E\r\n\t\u003Cli\u003EProcurement and Sourcing Analysts and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003EManufacturing Planners, Analysts, and Managers\u003C\/li\u003E\r\n\t\u003Cli\u003ESales Operations Managers, Analysts, Planners, Supervisors, Directors\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUnderstand the need for an S\u0026amp;OP cycle in a company\u003C\/li\u003E\r\n\t\u003Cli\u003EApply principles key to success of an S\u0026amp;OP process\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience true market examples relevant to their businesses\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003ELEARNING OBJECTIVES\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ELearn how to identify and apply best fit S\u0026amp;OP process and technology enablers to your organization and make it a reality based process.\u003C\/li\u003E\r\n\t\u003Cli\u003EWalk through a complete simulated S\u0026amp;OP cycle supported by a technology enabler.\u003C\/li\u003E\r\n\t\u003Cli\u003EUnderstand the interaction and integration between the financial and operation levels of S\u0026amp;O.\u003C\/li\u003E\r\n\t\u003Cli\u003ELearn the key components of an effective S\u0026amp;OP business case through discussion of real life examples of how companies have benefited from the implementation of best practices in S\u0026amp;OP.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EDefining the S\u0026amp;OP process before adopting technology\u003C\/li\u003E\r\n\t\u003Cli\u003EThe advantages of value based and reality based S\u0026amp;OP\u003C\/li\u003E\r\n\t\u003Cli\u003EWhy S\u0026amp;OP needs to be integrated closely with operational planning\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat is the scope of each role in the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EWhat are the most valuable outputs and results of the S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\t\u003Cli\u003EHow can technology enable companies to take performance to the next level\u003C\/li\u003E\r\n\t\u003Cli\u003EExperience a complete simulated technology-enabled S\u0026amp;OP Cycle\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course focuses on defining, executing, and improving the S\u0026amp;OP process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of visionary technology to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course focuses on defining, executing, and improving the S\u0026OP process."}],"uid":"27233","created_gmt":"2021-07-08 21:02:08","changed_gmt":"2021-07-08 21:03:23","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-10-18T09:00:00-04:00","event_time_end":"2021-10-19T13:00:00-04:00","event_time_end_last":"2021-10-19T13:00:00-04:00","gmt_time_start":"2021-10-18 13:00:00","gmt_time_end":"2021-10-19 17:00:00","gmt_time_end_last":"2021-10-19 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.pe.gatech.edu\/courses\/world-class-sales-and-operations-planning","title":"Course registration page"},{"url":"http:\/\/www.scl.gatech.edu\/wcsop","title":"Course webpage within the SCL website"},{"url":"https:\/\/www.scl.gatech.edu\/sites\/default\/files\/downloads\/gtscl-sdpbrochure.pdf","title":"Supply \u0026 Demand Planning Certificate Course Series Flyer"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"646650":{"#nid":"646650","#data":{"type":"event","title":"SCL Course: Category Management and Sourcing Leadership","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003ECategory Management and Sourcing Leadership is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe online version of the course is comprised of (3) instructor-led LIVE group webinars, homework, and pre-work (e.g. installing and testing software on your computer, testing connectivity with Canvas LMS and BlueJeans meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is ideal for sourcing initiative leaders, procurement professionals, project managers, finance analyst, contract managers and all procurement \u0026amp; supply management-related professionals involved with bid package development, bid package analysis, negotiations preparation, contracting and supplier selection activity.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EIncrease knowledge base of solicitation options (i.e. RFI, RFP, RFQ) and which solicitation approach to apply based on your organization\u0026#39;s needs\u003C\/li\u003E\r\n\t\u003Cli\u003EEnhance understanding of sourcing process and critical steps in the Bid Package development and delivery activities\u003C\/li\u003E\r\n\t\u003Cli\u003EBetter leverage and utilization of solicitation tools to drive successful development of bid packages\u003C\/li\u003E\r\n\t\u003Cli\u003EImprove set up and execution of supplier selection scorecards to aid in identifying best Total Cost of Ownership alternatives\u003C\/li\u003E\r\n\t\u003Cli\u003EHeighten understanding of executive communication to leverage leadership support throughout the organization\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EBid Package Development Overview\u003C\/li\u003E\r\n\t\u003Cli\u003ESourcing Initiative Process Roadmap\u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EMarketplace Analysis Tools\u003C\/li\u003E\r\n\t\u003Cli\u003EBid Package Alternatives \u0026amp; Design\u003C\/li\u003E\r\n\t\u003Cli\u003ESupplier Selection \u0026amp; Communication\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis course\u0026nbsp;is designed to deepen participants\u0026#39; knowledge base of core activities in the procurement \u0026amp; supply management function. The program covers the sourcing process, specifications gathering, common bid package alternatives, cross-functional collaboration and supplier evaluation \u0026amp; selection. Participants will walk away ready to develop bid packages more thoroughly to help drive sourcing decisions for their organizations. This \u0026quot;hands on\u0026quot; delivery focuses on the professional serving as the main liaison between the buying organization and the selling organization in the company sourcing process.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This course is designed to deepen participants\u0027 knowledge base of core activities in the procurement \u0026 supply management function."}],"uid":"27233","created_gmt":"2021-04-19 20:23:26","changed_gmt":"2021-06-16 18:33:59","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-13T14:00:00-04:00","event_time_end":"2021-09-16T15:30:00-04:00","event_time_end_last":"2021-09-16T15:30:00-04:00","gmt_time_start":"2021-09-13 18:00:00","gmt_time_end":"2021-09-16 19:30:00","gmt_time_end_last":"2021-09-16 19:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/cmsl","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EEMAIL: \u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E or CALL: (404) 385-3501 between 9:00a.m. and 4:00p.m., Eastern time.\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"631238":{"#nid":"631238","#data":{"type":"event","title":"2021 LeeAnn and Walter Muller Distinguished Lecture - S. Jack Hu","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EIndustrial Internet of Things and Smart Personalized Manufacturing\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe Industrial Internet of Things enables the connection of sensors, devices, and systems, and the rapid communication of data among them. Such data provide unprecedented opportunities for smart manufacturing, including real-time monitoring and optimal decision making. This talk will reflect on the advances of manufacturing in response to several technological revolutions. An example of lithium-ion battery manufacturing will be used to discuss the characteristics of smart manufacturing and the need for data analytics research. In addition, connection among customers, manufacturers, and suppliers is also creating a new paradigm of personalized manufacturing where customers actively participate in the design and fabrication of products or product components. Recent research activities in personalized manufacturing will also be highlighted.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E S. Jack Hu joined the University of Georgia (UGA) as the UGA Foundation Distinguished Professor of Engineering and Senior Vice President for Academic Affairs and Provost on July 1, 2019. As Provost he oversees instruction, research, public service and outreach, and information technology. Prior to joining UGA, he was the Vice President for Research, the J. Reid and Polly Anderson Professor of Manufacturing, Professor of Mechanical Engineering, and Professor of Industrial and Operations Engineering at the University of Michigan.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHu has authored or co-authored nearly 200 peer-reviewed journal articles related to his research in manufacturing systems, assembly, and engineering statistics. He holds six patents and has worked closely with several industry partners to enhance manufacturing quality and productivity.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHu is a member of the U.S. National Academy of Engineering and a foreign member of the Chinese Academy of Engineering. He is a Fellow of the American Society of Mechanical Engineers (ASME), the Society of Manufacturing Engineers (SME), and the International Academy for Production Engineering (CIRP). He is the recipient of the ASME William T. Ennor Manufacturing Technology Award, the SME Gold Medal, and several best paper awards.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EReception immediately following the lecture.\u003C\/strong\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIndustrial Internet of Things and Smart, Personalized Manufacturing\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Industrial Internet of Things and Smart Personalized Manufacturing"}],"uid":"27764","created_gmt":"2020-01-16 18:54:42","changed_gmt":"2021-05-27 13:47:04","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-09-23T16:00:00-04:00","event_time_end":"2021-09-23T17:00:00-04:00","event_time_end_last":"2021-09-23T17:00:00-04:00","gmt_time_start":"2021-09-23 20:00:00","gmt_time_end":"2021-09-23 21:00:00","gmt_time_end_last":"2021-09-23 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"631237":{"id":"631237","type":"image","title":"S. Jack Hu","body":null,"created":"1579200371","gmt_created":"2020-01-16 18:46:11","changed":"1579200371","gmt_changed":"2020-01-16 18:46:11","alt":"S. Jack Hu","file":{"fid":"240228","name":"s-jack-hu.png","image_path":"\/sites\/default\/files\/images\/s-jack-hu.png","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/s-jack-hu.png","mime":"image\/png","size":1320406,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/s-jack-hu.png?itok=58cfwfuX"}}},"media_ids":["631237"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"640848":{"#nid":"640848","#data":{"type":"event","title":"Supply Chain Optimization and Prescriptive Analytics","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u0026rsquo;ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u0026rsquo;ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EUse mathematical optimization to transform Supply Chain Management (SCM) processes.\u003C\/li\u003E\r\n\t\u003Cli\u003EApply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.\u003C\/li\u003E\r\n\t\u003Cli\u003EUtilize PowerBI and Python in optimization projects.\u003C\/li\u003E\r\n\t\u003Cli\u003EParticipate in a hackathon that pulls together everything learned throughout the certificate program.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003ERole of mathematical optimization in addressing complex SCM challenges \u0026nbsp;\u003C\/li\u003E\r\n\t\u003Cli\u003EAppropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics\u003C\/li\u003E\r\n\t\u003Cli\u003EEvaluation of production processes, distribution networks, and routes using optimization\u003C\/li\u003E\r\n\t\u003Cli\u003EAbility to pull together all content of the certificate program into a prescriptive analytics project\u003C\/li\u003E\r\n\t\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn advanced analytics and mathematical optimization to find solutions for supply chain problems.\u0026nbsp;The course also serves as a capstone for the Supply Chain Analytics Professional certificate program\u0026nbsp;by culminating in a hackathon where you\u0026rsquo;ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn advanced analytics and mathematical optimization to find solutions for supply chain problems."}],"uid":"27233","created_gmt":"2020-10-30 22:15:27","changed_gmt":"2021-05-27 13:40:23","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-06-21T14:00:00-04:00","event_time_end":"2021-06-24T17:59:00-04:00","event_time_end_last":"2021-06-24T17:59:00-04:00","gmt_time_start":"2021-06-21 18:00:00","gmt_time_end":"2021-06-24 21:59:00","gmt_time_end_last":"2021-06-24 21:59:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaoc","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"646663":{"#nid":"646663","#data":{"type":"event","title":"ISyE Seminar- Benny Van Houdt ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERandomized Load Balancing: the queue at the cavity at work\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERandomized load balancing algorithms in large-scale computing systems have received a lot of attention in the last few years. In this seminar we illustrate that the performance of many of these algorithms can be accessed using \u0026quot;the queue at the cavity approach\u0026quot;. This approach is an approximation method that is known to yield exact results in the large-system limit in some particular cases. Apart from illustrating how this approach works on a number of algorithms, we also touch upon some open problems in this area.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EShort Bio\u003C\/strong\u003E:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBenny Van Houdt is a professor at the department of Mathematics and Computer Science at the University of Antwerp (Belgium), where he also obtained his \u003Ca href=\u0022https:\/\/win.uantwerpen.be\/~vanhoudt\/papers\/thesis.pdf\u0022\u003EPhd\u003C\/a\u003E in 2001. He has been a post-doctoral fellow of the \u003Ca href=\u0022http:\/\/www.fwo.be\/en\/\u0022\u003EFWO-Flanders\u003C\/a\u003E from October 2001 until October 2007. He is currently the Editor-in-Chief of the \u003Ca href=\u0022http:\/\/www.journals.elsevier.com\/performance-evaluation\/\u0022\u003EPerformance Evaluation\u003C\/a\u003E journal (since Jan 2018), a senior associate editor of \u003Ca href=\u0022http:\/\/tompecs.acm.org\/board.html\u0022\u003EACM ToMPECS\u003C\/a\u003E (since 2014) and an editorial board member of \u003Ca href=\u0022http:\/\/www.tandfonline.com\/loi\/lstm20\u0022\u003EStochastic Models\u003C\/a\u003E (since 2016). He has been a member of the editorial board of \u003Ca href=\u0022http:\/\/www.journals.elsevier.com\/operations-research-letters\/\u0022\u003EOperations Research Letters\u003C\/a\u003E (2007-2017) and \u003Ca href=\u0022http:\/\/www.journals.elsevier.com\/performance-evaluation\/\u0022\u003EPerformance Evaluation\u003C\/a\u003E (2011-2017).\u003Cbr \/\u003E\r\nBenny is the (co)recipient of various awards including best paper awards at ACM Sigmetrics, IFIP Performance, ITC, QEST and Valuetools. He is an elected member and officer of the \u003Ca href=\u0022http:\/\/www.ifip.org\/bulletin\/bulltcs\/memtc07.htm#wg73\u0022\u003EIFIP working group 7.3 on Computer System Modeling\u003C\/a\u003E and has published papers in a variety of journals such as IEEE\/ACM Trans. on Networking, IEEE Trans. on Information Theory, Communications, IEEE JSAC, IEEE\/OSA JOCN, Performance Evaluation, QUESTA, Journal of Applied Probability, Adv. In Applied Probability, Operations Research Letters, INFORMS JOC, EJOR, Stochastic Models, Computer Networks, Naval Research Logistics, etc.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ERandomized load balancing algorithms in large-scale computing systems have received a lot of attention in the last few years. In this seminar we illustrate that the performance of many of these algorithms can be accessed using \u0026quot;the queue at the cavity approach\u0026quot;. This approach is an approximation method that is known to yield exact results in the large-system limit in some particular cases. Apart from illustrating how this approach works on a number of algorithms, we also touch upon some open problems in this area.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Randomized Load Balancing: the queue at the cavity at work"}],"uid":"34868","created_gmt":"2021-04-20 14:16:16","changed_gmt":"2021-04-20 14:16:16","author":"sbryantturner3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-04-27T12:00:00-04:00","event_time_end":"2021-04-27T13:00:00-04:00","event_time_end_last":"2021-04-27T13:00:00-04:00","gmt_time_start":"2021-04-27 16:00:00","gmt_time_end":"2021-04-27 17:00:00","gmt_time_end_last":"2021-04-27 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}