To honor this event, Justin Betancourt, an alumnus of the Master’s in Supply Chain program and former VP of Operations and Finance at the American Production and Inventory Control Society (APICS), offered a treasure trove of insights and reflections about his impactful journey that started at ISyE. 

Currently, Betancourt works at Delta Air Lines as a Project Manager in Workforce Planning and Analytics, where he applies his supply chain expertise from ISyE in a distinctive manner. 

Automating the Aviation Workforce 

“I like to think of my role as managing the supply chain of manpower. My job revolves around staffing at various airports, ensuring we maintain a harmoniously balanced staffing system throughout the country”. 

Highlighting the significant improvements in efficiency brought about by automation, Betancourt believes that removing repetitive and manual tasks from the equation streamlines processes and substantially lowers the chances of human error. 

This change allows staff to engage in more meaningful work, thereby enhancing overall operational efficiency. 

Betancourt shared his insights on the transformative impact of data analytics and automation. "Sometimes, the airline industry is perceived as slow to adapt due to its complexity and regulatory environment, but what's truly revolutionizing our sector is the investment in data analytics and automation." 

In his vision, the future of the aviation industry, and indeed many other sectors, lies in the harmonious integration of automation with human ingenuity.  

Betancourt’s insights into APICS 

As a founding member of APICS at Georgia Tech, Betancourt's contributions were instrumental in shaping the then-nascent organization.  

While reflecting on his motivation for joining the organization, Betancourt reminisced, “I wanted to be involved in APICS to get people in the same room and get them talking about what they're learning in school, challenge each other and grow together by networking.” 

Faced with the unforeseen challenges posed by COVID-19, Betancourt and his team demonstrated remarkable resilience and ingenuity by combining virtual and in-person engagements to adapt to the new circumstances. 

During his time at APICS, Betancourt was notably involved in strategic collaborations, particularly with the Supply Chain Institute and its director Tim Brown, under whom he also served as a teaching assistant.  

Their synergy facilitated a series of insightful seminars and discussions, enriching the learning experience for students. APICS capitalized on these opportunities, ensuring students had access to cutting-edge knowledge in supply chain advancements and research. 

Betancourt fondly recalls a key event during his APICS tenure: hosting the founder of the Project Management Institute. This seminar, primarily a success due to the Supply Chain and Logistics Institute and Tim Brown, highlighted crucial project management principles  

Beyond academic enrichment, these initiatives served as dynamic platforms for student networking, connecting them with industry leaders, faculty, and fellow students, thereby nurturing a community dedicated to collective learning and development. 

SCL Career Fair’s Networking Power 

Betancourt recalls the SCL Career Fair, as a standout event for networking, especially for those pursuing careers in supply chain management.  

“The SCL Career fair is probably the best opportunity to network with Industry professionals. Since it’s specific to supply chain roles and companies, it feels a lot more unique and intimate” Betancourt said.  

Giving thought on his journey, Betancourt shares how the career fair's specialized focus on supply chain allowed for engaging, in-depth discussions with company delegates. He credits the fair for facilitating valuable professional relationships, which notably played a role in his eventual position at Delta. 

Regarding guidance for students aspiring to careers in supply chain management, Betancourt stresses the necessity of being forward-thinking and adaptable. He asserts, "Plan ahead, think critically, and stay resilient. These qualities are indispensable in navigating the complexities of supply chain logistics." 

_______

Author: Atharva Anand Dave 

References: 

Justin Betancourt, PMP - Procter & Gamble | LinkedIn. (n.d.). https://www.linkedin.com/in/justinbetancourt 

In sharing his perspective, he seeks to guide recent graduates on the realities of experiencing their first job postgraduation.  

Originating from India, Shah embarked on his academic journey in Mechanical Engineering at the Vellore Institute of Technology. After dedicating four and a half years to honing his skills in Supply Chain and Network Design he made a strategic decision to further his expertise by pursuing a master’s degree from Georgia Tech. 

Following graduation, Shah embarked on a career at Amazon, where he is currently flourishing as an Innovation and Design Engineer.  

His journey at Amazon began with an internship through the SCL Amazon Scholars Program, a pivotal experience that laid the groundwork for his transition to a full-time role.  

Shah offers the following tips, tricks and insights on how recent graduates can make the most out of their first job: 

• Take full advantage of company-provided resources for continuous skill enhancement, such as free online certifications and training 

• Seize every chance to network within and beyond one's industry, one can never know which of these connections might offer assistance in the future 

When prompted for insights into prudent financial strategies, Shah recommends: 

• Read the book “I Will Teach You To Be Rich” by Ramit Sethi, it’s ideal for fresh graduates to start their financial savings journey early 

Finally, when inquired about her networking strategies, Shah suggests: 

• Apart from the career fairs, students should take advantage of the various ISyE internal and affiliated chapters, they can connect you with working professionals who are able to guide you on your career path or refer you for future opportunities 

• Try finding conferences near you, these are the best networking opportunities where you are likely to be able to have conversations with well positioned leadership from multiple companies 

• While networking, keep the conversation light and include mix of both technical and non-technical topics 

__________

Author: Atharva A. Dave

Yuming Sun, a Ph.D. student studying Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering, has been honored with the 2023 Seth Bonder Scholarship for Applied Operations Research in Health Services.

The Seth Bonder scholarship is a prestigious student award in the INFORMS Health Applications Society, that promotes the development and application of process modeling and operations research analysis to healthcare design, delivery, and operations.

Officially unveiled on Sunday, October 15th at the INFORMS Annual Meeting Awards Banquet, Sun was recognized for his exceptional research addressing the urgent need to focus on the threats posed by “circulating vaccine-derived poliovirus” (cVDPV).

Pioneering Solutions in Polio Eradication

Sun’s research proposal emphasized the ongoing challenges in reducing polio transmission on a global scale and mitigating vaccine-derived poliovirus outbreaks -- offering hope for a polio-free world.

His work consists of modeling the spread of poliovirus in high-risk spaces, while investigating cost-effective options to stop, prevent, and end polio outbreaks.

“Vaccine-derived poliovirus outbreaks are a result of the live-attenuated viruses used in the oral polio vaccine (OPV) reverting to cVDPV in under-vaccinated communities. cVDPV leads to poliovirus transmission and potentially paralysis among infected individuals.”

A Visionary Collaboration

With his research advancement, Sun emerges as a trailblazer, potentially being the first ISyE student in over two decades to receive this revered award.

Under the guidance of his advisors, Pinar Keskinocak and Lauren Steimle, Sun has “closely collaborated with researchers in the Global Immunization Division at the CDC, and regularly incorporates their feedback into his models.”

The invaluable feedback from the CDC team has enriched the impact, positioning Yuming at the forefront of this critical research.

Hailing from Panama, Avila pursued her Bachelor of Science in Logistics and Supply chain at the Technological University of Panama. Along this remarkable path, she nurtured her skills and expertise through invaluable experiences at renowned organizations like GlaxoSmithKline and Grainger.

Avila currently shines as a Business Operations Analyst in the Global Production Planning department at Dell Technologies, contributing her talents to shape the future of supply chain operations.

Avila’s dedication towards academia was further bolstered when she was awarded a scholarship to pursue her master's degree at Georgia Tech. Like many of her peers, Avila navigated the intricate path of securing her inaugural job with unwavering determination.

Avila shares some tips, tricks and insights on how recent graduates can make the most out of their first job:

• Create a list of companies they’re interested in working with

• Having an open-minded approach and emphasizing that fresh graduates secure multiple learning opportunity

When prompted for insights into prudent financial strategies tailored for recent graduates, Avila recommends:

• Studying the market average salary for the position that you want

• Be aware of their self-perceived value and the prevalent industry norms

Finally, when inquired about her networking strategies, Avila suggests:

• Create a list of probably attendees and conduct research regarding their research and background

• Strike up a conversation with them regarding the interests, which will ultimately forging meaningful, mutually beneficial relationships

Out of a total of 40 submissions, four were designated as finalists. The winner will be chosen at the October 15-18, 2023 INFORMS Annual Meeting taking place in Phoenix Arizona, during which the finalists will showcase their work in a dedicated session. All finalists receive a commemorative plaque, and the winning entrant(s) receives a $500 honorarium. In addition, the winning paper, if not published or under review elsewhere, will be invited for a fast-track review at Transportation Science.

Dipayan Banerjee
Fleet Sizing and Service Region Partitioning for Same-Day Delivery Systems

Many existing Same-Day Delivery (SDD) studies focus primarily on operational dispatch problems and do not consider system design questions. Furthermore, prior work on SDD system design does not consider the fleet sizing decision when a service region may be partitioned into zones dedicated to individual vehicles (such designs have been shown to improve system efficiency in related vehicle routing settings). Banerjee's research utilizes a novel approach to addressing two key tactical design challenges when planning an SDD system: figuring out how many delivery vehicles you need and dividing the delivery area into manageable zones.

Using continuous approximations to capture average-case operational behavior, the problem of independently maximizing the area of a single-vehicle delivery zone is considered first. The approach then characterizes area-maximizing dispatching policies and leverages the results to develop a procedure for calculating optimal areas as a function of a zone's distance from the depot, given a maximum number of daily dispatches per vehicle. Using minimal computation, the approach specifies fleet sizes and builds vehicle delivery zones that meet operational requirements, verified by simulation results.

Sushil Varma
Electric Vehicle Fleet and Charging Infrastructure Planning

Varma's research focuses on finding the best way to dispatch electric vehicles to pick up customers while making sure they charge periodically. As customer requests arrive, system operators must determine the minimum number of vehicles and chargers for a given service level, along with a matching and charging policy that maximizes that service level. Varma's approach provides a sharp characterization of the fleet size and the charging infrastructure requirements as demand grows. The research highlights the fundamental differences between planning for an electric vehicle system and a gas-powered system. To understand the difference, note that serving a customer comprises two steps -  pickup and trip, each contributing to the fleet size requirement of the system. As EVs require charging time, they need more vehicles to compensate for the trip part of the service. In turn, the optimal dispatching policy can reduce the EV requirement induced by the pick up part of the service by lowering the pickup times, owing to the extra EVs due to the trip phase. The reduction in the EV requirement depends on the number of charging stations and the size of the EV battery packs. 

The research proposes the "Power-of-d" dispatching policy, which achieves this performance by selecting the d closest vehicles to a trip request and choosing the one with the highest battery level. Varma also conducted detailed simulations that verified the scaling results. The paper discusses how the results extend to accommodate demand that increases/decreases repetitively or cyclically over time.

About Dipayan

Dipayan Banerjee is a fifth-year ISyE Ph.D. candidate advised by Professors Alan Erera and Alejandro Toriello. He is broadly interested in optimization for logistics and supply chain management with a focus on modern e-commerce systems. His doctoral research, supported by the NSF Graduate Research Fellowship and the Eisenhower Transportation Research Fellowship, studies demand management and delivery optimization for e-retail fulfillment. Dipayan was jointly awarded ISyE's Atlanta Air Cargo Association Fellowship for Ph.D. Research Excellence in Supply Chain Engineering in 2022. In addition to being named a finalist for the 2023 INFORMS TSL Society Best Student Paper Award, he also was a finalist for the 2019 INFORMS Undergraduate Operations Research Prize.

About Sushil

Sushil Varma, also a 5th-year ISyE Ph.D. student, is advised by Professor Siva Theja Maguluri. His research interests include queueing theory, game theory, and revenue management with applications in electric vehicles, online marketplaces like ride-hailing, load balancing, and stochastic processing/matching networks. Sushil was awarded the Stephen. S. Lavenberg Best Student Paper Award in IFIP Performance 2021 and the Alice and John Jarvis Best Student Paper Award in 2022.

We extend our wishes for success to both of these remarkable students. Their dedication, hard work, and commitment to their research have already set them on a remarkable path. Regardless of the outcome, their recognition is a testament to academic excellence.

The annual event is scheduled to be held from the 18th to the 21st of May in Montreal, Canada.  

Widely considered the largest industrial and systems Engineering event of the year, it attracts the participation of leading industry professionals.  

With various paper presentations from reputable teaching institutions worldwide, the IISE Conference is popular among students and faculty eager to present their research work. 

In conjunction with his role as the chair professor, Dr. Montreuil holds pivotal positions as the Director of the Physical Internet Center and Co-director of the Supply Chain and Logistics Institute at ISyE. 

Dr. Montreuil’s 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. 

Throughout his 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.  

Having 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. 

Yao Xie

Sequential Predictive Conformal Inference for Time Series | Chen Xu, Yao Xie

We present a new distribution-free conformal prediction algorithm for sequential data (e.g., time series), called the \textit{sequential predictive conformal inference} (\texttt{SPCI}). We specifically account for the nature that time series data are non-exchangeable, and thus many existing conformal prediction algorithms are not applicable. The main idea is to adaptively re-estimate the conditional quantile of non-conformity scores (e.g., prediction residuals), upon exploiting the temporal dependence among them. More precisely, we cast the problem of conformal prediction interval as predicting the quantile of a future residual, given a user-specified point prediction algorithm. Theoretically, we establish asymptotic valid conditional coverage upon extending consistency analyses in quantile regression. Using simulation and real-data experiments, we demonstrate a significant reduction in interval width of \texttt{SPCI} compared to other existing methods under the desired empirical coverage.

Xiaoming Huo

Conformalization of Sparse Generalized Linear Models | Etash Guha, Eugene Ndiaye, Xiaoming Huo

Given a sequence of observable variables $(x_1, y_1), \ldots, (x_n, y_n)$, the conformal prediction method estimates a confidence set for $y_{n+1}$ given $x_{n+1}$ that is valid for any finite sample size by merely assuming that the distribution is permutation invariant. Although attractive, computing such a set is infeasible in most regression problems. Indeed, in these cases, the unknown variable $y_{n+1}$ can take an infinite number of possible values, and generating conformal sets requires retraining a predictive model for each of them. In this paper, we focus on a sparse model with only a subset of variables for prediction, and we leverage numerical continuation techniques to efficiently approximate the solution path. The key property we exploit is that the set of selected variables is invariant under a small perturbation of the input data. Therefore, it is sufficient to enumerate and refit the model only at the change points of the set of active features and smoothly interpolate the rest of the solution via a predictor-corrector mechanism. We show how our path-following algorithm accurately approximates conformal prediction sets and illustrate its performance using synthetic and real data examples.

Tuo Zhao

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories | Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

Existing theories on deep nonparametric regression have shown that when the input data lie on a low-dimensional manifold, deep neural networks can adapt to the intrinsic data structures. In real world applications, such an assumption of data lying exactly on a low dimensional manifold is stringent. This paper introduces a relaxed assumption that the input data are concentrated around a subset of $\RR^d$ denoted by $\cS$, and the intrinsic dimension of $\cS$ can be characterized by a new complexity notation — effective Minkowski dimension. We prove that, the sample complexity of deep nonparametric regression only depends on the effective Minkowski dimension of $\cS$ denoted by $p$. We further illustrate our theoretical findings by considering nonparametric regression with an anisotropic Gaussian random design $N(0,\Sigma)$, where $\Sigma$ is full rank. When the eigenvalues of $\Sigma$ have an exponential or polynomial decay, the effective Minkowski dimension of such an Gaussian random design is $p=\cO(\sqrt{\log n})$ or $p=\cO(n^\gamma)$, respectively, where $n$ is the sample size and $\gamma\in(0,1)$ is a small constant depending on the polynomial decay rate. Our theory shows that, when the manifold assumption does not hold, deep neural networks can still adapt to the effective Minkowski dimension of the data, and circumvent the curse of the ambient dimensionality for moderate sample sizes.

Less is More: Task-aware Layer-wise Distillation for Language Model Compression | Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao

Layer-wise distillation is a powerful tool to compress large models (i.e. teacher models) into small ones (i.e., student models). The student distills knowledge from the teacher by mimicking the hidden representations of the teacher at every intermediate layer. However, layer-wise distillation is difficult. Since the student has a smaller model capacity than the teacher, it is often under-fitted. Furthermore, the hidden representations of the teacher contain redundant information that the student does not necessarily need for the target task’s learning. To address these challenges, we propose a novel Task-aware layEr-wise Distillation (TED). TED designs task-aware filters to align the hidden representations of the student and the teacher at each layer. The filters select the knowledge that is useful for the target task from the hidden representations. As such, TED reduces the knowledge gap between the two models and helps the student to fit better on the target task. We evaluate TED in two scenarios: continual pre-training and fine-tuning. TED demonstrates significant and consistent improvements over existing distillation methods in both scenarios.

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation | Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao

Transformer models have achieved remarkable results in various natural language tasks, but they are often prohibitively large, requiring massive memories and computational resources. To re- duce the size and complexity of these models, we propose LoSparse (Low-Rank and Sparse ap- proximation), a novel model compression tech- nique that approximates a weight matrix by the sum of a low-rank matrix and a sparse matrix. Our method combines the advantages of both low- rank approximations and pruning, while avoid- ing their limitations. Low-rank approximation compresses the coherent and expressive parts in neurons, while pruning removes the incoherent and non-expressive parts in neurons. Pruning enhances the diversity of low-rank approxima- tions, and low-rank approximation prevents prun- ing from losing too many expressive neurons. We evaluate our method on natural language under- standing, question answering, and natural lan- guage generation tasks. We show that it signif- icantly outperforms existing compression meth- ods. Our code is publicly available at https: //github.com/yxli2123/LoSparse

Machine Learning Force Fields with Data Cost-Aware Training | Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

Machine learning force fields (MLFF) have been proposed to accelerate molecular dynamics (MD) simulation, which finds widespread applications in chemistry and biomedical research. Even for the most data-efficient MLFFs, reaching chemical accuracy can require hundreds of frames of force and energy labels generated by expensive quantum mechanical algorithms, which may scale as $O(n^3)$ to $O(n^7)$, with $n$ proportional to the number of basis functions.To address this issue, we propose a multi-stage computational framework — ASTEROID, which lowers the data cost of MLFFs by leveraging a combination of cheap inaccurate data and expensive accurate data. The motivation behind ASTEROID is that inaccurate data, though incurring large bias, can help capture the sophisticated structures of the underlying force field. Therefore, we first train a MLFF model on a large amount of inaccurate training data, employing a bias-aware loss function to prevent the model from overfitting the potential bias of this data. We then fine-tune the obtained model using a small amount of accurate training data, which preserves the knowledge learned from the inaccurate training data while significantly improving the model’s accuracy. Moreover, we propose a variant of ASTEROID based on score matching for the setting where the inaccurate training data are unlabeled. Extensive experiments on MD datasets and downstream tasks validate the efficacy of ASTEROID.Our code and data are available at \url{https://github.com/abukharin3/asteroid}.

Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data | Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang

Diffusion models achieve state-of-the-art performance in various generation tasks. However, their theoretical foundations fall far behind. This paper studies score approximation, estimation, and distribution recovery of diffusion models, when data are supported on an unknown low-dimensional linear subspace. Our result provides sample complexity bounds for distribution estimation using diffusion models. We show that with a properly chosen neural network architecture, the score function can be both accurately approximated and efficiently estimated. Further, the generated distribution based on the estimated score function captures the data geometric structures and converges to a close vicinity of the data distribution. The convergence rate depends on subspace dimension, implying that diffusion models can circumvent the curse of data ambient dimensionality.

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process | Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha

Transformer Hawkes process models have shown to be successful in modeling event sequence data. However, most of the existing training methods rely on maximizing the likelihood of event sequences, which involves calculating some intractable integral. Moreover, the existing methods fail to provide uncertainty quantification for model predictions, e.g., confidence interval for the predicted event’s arrival time. To address these issues, we propose SMURF-THP, a score-based method for learning Transformer Hawkes process and quantifying prediction uncertainty. Specifically, SMURF-THP learns the score function of the event’s arrival time based on a score-matching objective that avoids the intractable computation. With such a learnt score function, we can sample the arrival time of events from the predictive distribution. This naturally allows for the quantification of uncertainty by computing confidence intervals over the generated samples. We conduct extensive experiments in both event type prediction and uncertainty quantification on time of arrival. In all the experiments, SMURF-THP outperforms existing likelihood-based methods in confidence calibration while exhibiting comparable prediction accuracy.

Juba Ziani

Sequential Strategic Screening | Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

We initiate the study of strategic behavior in screening processes with multiple classifiers. We focus on two contrasting settings: a “conjunctive” setting in which an individual must satisfy all classifiers simultaneously, and a sequential setting in which an individual to succeed must satisfy classifiers one at a time. In other words, we introduce the combination of strategic classification}with screening processes. We show that sequential screening pipelines exhibit new and surprising behavior where individuals can exploit the sequential ordering of the tests to “zig-zag” between classifiers without having to simultaneously satisfy all of them. We demonstrate an individual can obtain a positive outcome using a limited manipulation budget even when far from the intersection of the positive regions of every classifier. Finally, we consider a learner whose goal is to design a sequential screening process that is robust to such manipulations and provide a construction for the learner that optimizes a natural objective.

Santanu Dey | Anderson-Interface Professor 

As the accomplished A. Russell Chandler III Professor and Associate Chair of Graduate Studies, Dr. Santanu Dey was appointed to the endowed professorship position as ISyE’s next Anderson-Interface Professor. Dey brings an extensive amount of knowledge in the area of non-convex optimization, and in particular mixed integer linear and nonlinear programming. 

Xiaoming Huo | A. Russell Chandler III Professor 

Dr. Xiaoming Huo is an admired professor in the H. Milton Stewart School of Industrial and Systems Engineering and also serves as the Associate Director for Research in the Institute for Data Science and Engineering (IDEaS). Huo has recently been appointed the professorship and will continue his research work spanning statistical theory, statistical computing, and data analytics, with significant contributions in areas like sparse representation, wavelets, and statistical problems in detectability. 

Mohit Singh | Coca-Cola Foundation Professor 

As an Associate Professor and Director of the Algorithms and Randomness Center (ARC), Dr. Mohit Singh was appointed to the professorship as a Coca-Cola Foundation Professor. He brings expertise in discrete optimization, approximation algorithms, and convex optimization. His research focuses on optimizing cloud computing, logistics, network design, and machine learning. 

Kamran Paynabar | Fouts Family Professor 

Dr. Kamran Paynabar has become the Fouts Family Professor and Associate Professor at the H. Milton Stewart School of Industrial and Systems Engineering. His research interests lie in the integration of applied and theoretical aspects of data mining and statistical modeling. Prior to this appointment, Paynabar was the Fouts Family Early Career Professor from 2018 to 2023.  

Joel Sokol | Harold E. Smalley Professor 

Professor Joel Sokol is renowned for his work in sports analytics and applied operations research, as the next Harold E. Smalley Professor. Additionally, he serves as the Director of Georgia Tech's interdisciplinary Master of Science in Analytics degree program (MSA). His LRMC method for predictive modeling in the NCAA basketball tournament is widely recognized, and his non-sports research has received prestigious accolades. 

We extend our warmest congratulations to these exceptional individuals on their well-deserved appointments and look forward to their continued contributions to the field of Industrial and Systems Engineering at Georgia Tech. 

Karan Agrawal, Chris Carter, Jing Li, Kaibo Liu, Kendall Tyson, and Tuba Yilmaz Gozbasi were all recognized for their great achievements. This annual program showcases how Georgia Tech alumni impact every field worldwide and work to improve the way we live through their diligence and expertise from an early age.
 

Karan Agrawal, IE 19
Senior Manager, Supply Chain | Peloton Interactive

An award-winning supply chain practitioner and thought leader with four years of experience across the U.S., U.K., and Canada in Fortune 500 companies and tech startups, Karan Agrawal currently serves as senior manager, supply chain at Peloton. He has led multiple strategic supply chain initiatives, focused primarily on manufacturing and sourcing with multimillion-dollar scale and impact. Prior to Peloton, he worked at Dell, where he played a critical role in its supply chain digital transformation journey and strengthened the corporate brand through numerous external academic and industry partnerships. Passionate about building diverse communities from the ground up, Agrawal initiated the American Production and Inventory Control Society, or APICS, at Georgia Tech, launched an innovative TED-like storytelling platform at Dell called “Talks @ Dell,” and recently founded Toronto’s first supply chain community.

Favorite Tech Memory: Emceeing the largest cultural show on campus in front of 1,200 attendees at the Ferst Center for the Arts.

Chris Carter, IE 07
Chief Engineer, Executive GM | Toyota Motor North America (HQ)

Chris Carter has 15 years of experience in portfolio management, leadership, instruction, team building, and people development worldwide. Through Georgia Tech Professional Education, he became a Project Management Professional (PMP) & Agile Certified Practitioner (ACP). As chief engineer for Toyota Motor North America, Connected Technologies division, Carter is responsible for portfolio management for all Toyota and Lexus new model infotainment systems, including various technology life cycle management activities. He facilitates a team, leading tech strategy, market research, and global tech life cycle planning. During his tenure, he also worked abroad in Japan for Lexus International, leading midsize segments model years for RX, NX, and ES. Carter is also the academic program director over Project Management and Professor of the Practice candidate at Georgia Tech.

Favorite Tech Memory: Junior’s Grill. I used to have the French Toast Special and chicken finger basket every week.

Jing Li, IE 10
Product Management Sr. Principal | Accenture

With a non-traditional journey from Peace Corps Ukraine to product innovation, Jing Li blends her unique skills and experiences to lay the foundation for the next generation of leaders through education, technology, sustainability, and diversity. She founded the nonprofit Project Ollie to provide Ukrainian educators and learners with humanitarian support and tools to thrive. She helped reduce food waste through IoT sensors, and she advocates for inclusion and diversity in the workplace as well as in the open water swimming community. She was a four-year letterwinner in swimming at Georgia Tech and the former president of the NorCal GT Alumni network.

Favorite Tech Memory: Standing on the 50-yard line as a finalist for Ms. Georgia Tech in fall 2009.

Kaibo Liu, MS Stat 11, PhD IE 13
Professor | University of Wisconsin–Madison

Kaibo Liu is a professor at UW–Madison’s ISyE department and associate director of UW-Madison IoT systems research center. He received a bachelor’s in industrial engineering from the Hong Kong University of Science and Technology (HKUST) and a master’s in statistics and PhD in industrial engineering from Georgia Tech. His research focuses on system informatics and industrial big data analytics for quality improvement in complex engineering systems. He has won prestigious career awards, including the Innovations in Education Award and the Award for Technical Innovation in Industrial Engineering from the Institute of Industrial and Systems Engineering.

Favorite Tech Memory: I cherish having earned two degrees in four years and having my first child during my Georgia Tech PhD program.

Kendall Tyson, IE 11
SVP, Finance and Business Intelligence | Seattle Kraken

Kendall Tyson is the senior vice president of finance and business intelligence for the Seattle Kraken, the city’s professional ice hockey team. She oversees the strategic planning, data management, and financial affairs of the Kraken and its affiliates. Before joining the Kraken, Tyson led corporate development at Topgolf, where she evaluated mobile apps, entertainment venues, and golf technology. Earlier in her career, she advised state government agencies on business transformations as a management consultant at Accenture. In addition to her degree from Georgia Tech, Kendall holds a bachelor’s from Emory University and an MBA from the Yale School of Management. She currently resides in Seattle, Washington, with her husband and two children.

Favorite Tech Memory: Walking on the Great Wall of China while studying abroad in Beijing and Singapore.

Tuba Yilmaz Gozbasi, MS OR 11, PhD IE 13
COO & Cofounder | Optiyol

Tuba Yilmaz Gozbasi worked as an operations research consultant at Solvoyo and an assistant professor of operations management at Özyeğin University Faculty of Business. She is currently cofounder and COO of Optiyol, a delivery management SaaS, offering a route optimization engine and a mobile driver app with live tracking capabilities to increase delivery efficiency and improve customer service.

Favorite Tech Memory: I started dating my husband (and partner at Optiyol) while studying for a comprehensive exam in the grad lab.

Michael Biehler (advisor: Professor Jianjun Shi)

• Mary G. and Joseph Natrella Scholarship, American Statistical Association (ASA) (2023)
• Best Student Paper Award (Winner) Quality Control and Reliability Engineering (QCRE) Division, IISE (2023)
  • For the paper: M. Biehler, D. Lin , J. Shi (2023): “DETONATE: Nonlinear Dynamic Evolution Modeling of Time-dependent 3-dimensional Point Cloud Profiles” IISE Transactions
• Best Student Paper Award (Finalist) Data Analytics and Information Systems (DAIS) Division, IISE (2023)
  • For the paper: M. Biehler, A. Kulkarni, J. Li, J. Shi (2023+): “MULTI-MODAL: MULTI-fidelity, multi-modality 3D shape modeler:” submitted to IEEE Transactions on Automation Science and Engineering
• Phillip J. and Delores A. Scott Graduate Student Health and Wellness Award, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech (2023)
• IHE-LeaD Fellow, Burroughs Wellcome Fund, Interdisciplinary and Health and Environment Leadership Development (2022-2023)

Alina Gorbunova (advisors: Professor Jianjun Shi and Professor Kamran Paynabar)

• NSF Graduate Research Fellowship (2023)

 Shancong Mou (advisor: Professor Jianjun Shi)

• Best Track Paper Award (Winner), Quality Control and Reliability Engineering (QCRE) Division, IISE (2023) 
  • For the paper: Mou, S., Gu, X., Cao, M., Bai, H., Huang, P., Shan, J., Shi, J.*, 2023 “RGI: Robust GAN-Inversion for Generic Pixel-wise Anomaly Detection and Mask-free Image Inpainting”, The International Conference on Learning Representations (ICLR 2023).
• John S.W. Fargher Jr. Scholarship, IISE (2023)
• Angela P. and Reed J. Baker Research Excellence Award, School of ISyE, Georgia Institute of Technology (2023)

 Zihan Zhang (advisors: Professor Jianjun Shi and Professor Kamran Paynabar)

• Aerospace and Test Measurement Division Scholarship, ISA (2023)
• ISA Scholarship, ISA (2023)
• Gilbreth Memorial Scholarship, IISE (2023)
• NCORE Student Scholar, National Conference on Race and Ethnicity in Higher Education (2023)

Sustainability Research + Innovation Congress 2023 is the world's largest gathering for the global sustainability community, and for the first time, the event took place in the Latin American and Caribbean Region. SRI unites more than 2000 global sustainability research leaders, government and civil society experts, funders and innovators to inspire action and promote a sustainability transformation. The global and annual event elevates diverse knowledge on sustainability, provides an inspiring platform to share innovative ideas, and creates an inclusive space for collaboration and action. SRI is a joint initiative of Future Earth and the Belmont Forum.

As part of the Fri Jun 30 panel session "Reducing Emissions from Logistics", Thomas discussed "Life-cycle Approaches to Assessing Emissions from Logistics." To help provide the academic perspective, she was joined by Marilyn Brown, Regents' and Brook Byers Professor of Sustainable Systems in the School of Public Policy,  who spoke on "Three trends challenging U.S. and global emissions reductions from logistics." The private sector perspective was provided by Alex Rodriguez, Regional Head of Energy Transition Execution - LAM with A.P. Moller - Maersk. Rodriquez provided a broad and interesting discussion of air-water-land logistics, its impact on the environment, and possible future solutions. The session was organized by Jorge Barnett Lawton, Managing Director of the Georgia Tech Panama Logistics Innovation & Research Center, who also moderated the session from Panama City.

To learn more about the annual event and view available recordings, please visit https://sricongress.org/.

Mei was chosen for his path-breaking research in sequential analysis and change-point detection, seminal contribution to streaming data analysis in machine learning and data science, and outstanding service to the profession.

The ASA will honor him at an awards ceremony on August 8, 2023, during the Joint Statistical Meetings (JSM) in Toronto. Professor Mei's nomination was put forth by Roshan Joseph, the A. Russell Chandler III Chair and a professor in ISyE.

Mei received his Ph.D. in Mathematics with a minor in Electrical Engineering from the California Institute of Technology (Caltech) in 2003 and a B.S. in Mathematics from Peking University, China in 1996. He has also worked as a Post Doc in Biostatistics for two years in the renowned Fred Hutchinson Cancer Research Center in Seattle before joining ISyE in January 2006.

His research endeavors primarily revolve around the development of practical (bio)statistical, machine learning, and data science theories and algorithms, for efficient real-time or online data-driven decision-making with applications to engineering, operation research, and biomedical and health sciences.

Mei’s honors include:

• 2021 Star Research Achievement Award in the Virtual Critical Care Congress
• 2020 Best Paper Competition Award in the Quality, Statistics & Reliability (QSR) of INFORMS
• 2010 CAREER Award from National Science Foundation
• 2009 Abraham Wald Prize in Sequential Analysis
• 2008 Best Paper Award of the 11th International Conference on Information Fusion.

He is an Associate Editor of Technometrics, Statistica Sinica, Journal of Applied Statistics, and Sequential Analysis. He was the past president of the ASA Georgia Chapter.

Engineers who are performing exceptional research and technical work in a variety of disciplines will come together for the two-and-a-half-day event. The participants — from the industry, academia, and government — were nominated by fellow engineers or organizations.  

Ayer also serves as the research director for healthcare analytics and business intelligence in the Center for Health & Humanitarian Systems at Georgia Tech and holds a courtesy appointment at Emory Medical School. 

Ayer's contributions to the field have also led to his role as a senior advisor to the Centers for Disease Control and Prevention (CDC), as well as his position as an associate editor for Operations Research, Management Science, and MSOM. Additionally, he has served as the past president of the INFORMS Health Application Society. 

His research focuses on healthcare analytics and socially responsible business analytics with a particular emphasis on practice-focused research. His research papers have been published in top tier management, engineering, and medical journals; along with being covered by popular media outlets, including the Wall Street Journal, Washington Post, U.S. News, and NPR. 

The symposium will be hosted by the University of Colorado, Boulder, September 10-13, 2023, and will explore four themes: 

•     Engineered Quantum Systems 

•     Mining and Mineral Resource Production 

•     Resilience and Security in the Information Ecosystem 

•     Complex Systems in the Context of Health Care 

Since the program’s inception in 1995, more than 5,000 early-career engineers have participated in previous symposia, many of whom have gone on to become national leaders in the engineering community. Georgia Tech is proud to partner with organizations like The Grainger Foundation to promote a vibrant engineering profession and public appreciation of engineering. 

Read the article in its entirety within the Scientific American website.

Gathering together in New Orleans for their exciting achievements, four of our H. Milton Stewart School of Industrial and Engineering (ISyE) members united to celebrate their papers and research studies.

This included two current faculty members: Chuck Zhang, Harold E. Smalley Professor, and Lauren Steimle, Assistant Professor. Joining these esteemed faculty members were two remarkable ISyE Ph.D. alumni who have carved out their own paths of excellence. Reem Khir, currently an Assistant Professor at Purdue University, and Dan Li, now an Assistant Professor at Clemson University.

The conference had two paper sessions: Best Application Paper and Best Paper. Both sessions featured representation from members within the Georgia Tech ISyE community, covering various studies ranging from Markov decision processes to cell manufacturing.

Best Application Paper Session:

IISE Transactions Focus Issue on Supply Chain and Logistics
Reem Khir, Alan Erera, and Alejandro Toriello, "Two-stage sort planning for express parcel delivery"

IISE Transactions Focus Issue on Design and Manufacturing
Jialei Chen, Zhaonan Liu, Kan Wang, Chen Jiang, Chuck Zhang, and Ben Wang, "A Calibration-free Method for Biosensing in Cell Manufacturing"

IISE Transactions Focus Issue on Data Science, Quality, and Reliability
Dan Li, Kamran Paynabar, and Nagi Gebraeel, "A degradation-based detection framework against covert cyberattacks on SCADA systems"

Best Paper Session:

IISE Transactions Focus Issue on Operation Engineering and Analytics
Lauren N. Steimle, Vinayak S. Ahluwalia, Charmee Kamdar, and Brian T. Denton, "Decomposition methods for solving Markov decision processes with multiple models of the parameters"

*bolded: GT ISyE members

Through the Georgia Tech Research Institute (GTRI), H. Milton Stewart School of Industrial and Systems Engineering, and Supply Chain and Logistics Institute, Georgia Tech has been providing research and training support to personnel at the base, which supports the USMC mission worldwide. Activities under the new contract will be managed through the Albany installation, which has approximately 3,000 civilian staff and slightly more than 400 military personnel, making it one of the largest employers in Southwest Georgia.

The new Information Analysis Center Multiple Award Contract (IAC MAC) was competitively awarded through the Department of Defense Information Analysis Center. In all, the task order contract specifies 22 areas where GTRI, Georgia Tech, and partner organizations can support the USMC, and is the largest contract ever awarded to GTRI from the USMC.

“This award will continue the applied research efforts that support the analysis, assessment, and integration of technologies and methods to enhance the operations of the Marine Corps logistics, storage, and maintenance capabilities, while also providing potential support to the broader Marine Corps and DoD requirements,” said Larry Kimm, manager of GTRI’s Quantico Field Office and project director for the new contract. “This contract builds upon a nearly five-year partnership between Georgia Tech and the U.S. Marine Corps to provide ‘white-hat’ research and analysis support.”

Research projects conducted under earlier contracts have included the development and demonstration of robotic platform prototypes for improved ground vehicle autonomous inventory operations, and the development of a software tool that rapidly collates disparate inventory information to simplify tracking procedures. Additionally, ongoing workflow optimization modeling and simulation, and analytical studies of MARCORLOGCOM parts, repair, paint, and back-shop maintenance operations are supporting enhanced efficiency and mission readiness requirements. 

Georgia Tech’s Supply Chain and Logistics Institute provides research and education in the application of scientific principles to optimize the design and integration of supply chain strategy, infrastructure, processes, and technology. It has taught courses to hundreds of civilian employees and military personnel at Marine Corps Logistics Base Albany, providing advanced training and certification in logistics operations and industrial engineering principles. 

“The Supply Chain and Logistics Institute is pleased to continue engaging with GTRI on Marine Corps Logistics Command’s innovation and improvement needs,” said Timothy Brown, managing director of the Institute. “We look to continue delivering professional education programs, applied research by our Industrial and Systems Engineering faculty and graduate students, and operations improvement efforts by our affiliate researchers.”

Graduate and undergraduate programs at Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE) have been ranked first in the nation by U.S. News & World Report for more than a quarter century. The school is the largest of its kind in the United States.

In addition to its Georgia Tech collaborators, GTRI has also worked with multiple subcontractors to collaboratively conduct detailed business case analyses and change management support activities to optimize reorganization decisions and processes for MARCORLOGCOM. Georgia Tech has also involved interns from Albany Technical College and Albany State University in serving the organization’s needs.

In addition to supporting MARCORLOGCOM in Albany, the task order contract will allow GTRI and Georgia Tech to serve the broader needs of the USMC in such areas as automation, airborne networks, command-and-control systems, communications, cybersecurity, data exchange standards, electronic combat, human systems integration, manufacturing optimization, modeling and simulation, secure information systems, software assurance, systems engineering, technology insertion, and technology analysis.

GTRI’s connection to Georgia Tech academic colleges and research institutes makes it attractive to organizations interested in promoting innovation and changing organizational approaches. “Agencies gain access to the world-class expertise we have at Georgia Tech, both within GTRI and on the academic side,” Kimm said.

Located on Marine Corps Logistics Base Albany, MARCORLOGCOM provides worldwide, integrated logistics, supply chain, and distribution management; depot-level maintenance management; and strategic pre-positioning capability in support of the operating forces and other supported USMC units to maximize their readiness and sustainability and to support enterprise and program-level total life cycle management.

The DoD IAC collects, analyzes, synthesizes, produces, and disseminates scientific and technical information (STI) to DoD and federal government users. IACs support The Office of the Under Secretary of Defense for Research and Engineering (R&E) in carrying out the R&E community's three strategic guiding imperatives: 1) mitigating new and emerging adversary threats that could degrade U.S. (and allied) capabilities; 2) enabling affordable new or extended capabilities in existing military systems; and 3) developing technology surprise through science and engineering applications to military problems. 

Additionally, Becky plans and coordinates economic and business development activities with a variety of state and local organizations. From 2008 to 2012, Becky directed the market research program to understand customer’s preferences and needs, which led to expanded product and service offerings and increased non-aeronautical revenue by 40 percent.

We are very excited to have Becky join our board, lend us her expertise, and continue ATL's participation and support of SCL programs.