{"252601":{"#nid":"252601","#data":{"type":"event","title":"Big Data Chalk \u0026 Talk\/Brown Bag: Haesun Park","body":[{"value":"\u003Cp\u003EFour Georgia Tech research hubs have launched a new \u201cchalk \u0026amp; talk\u201d brown bag lunch series on Big Data. The weekly series, sponsored jointly by the\u0026nbsp;Institute for Data \u0026amp; High Performance Computing (IDH),\u0026nbsp;\u003Ca href=\u0022http:\/\/www.materials.gatech.edu\/\u0022\u003EInstitute for Materials (IMaT)\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022http:\/\/cda.gatech.edu\/\u0022\u003ECenter for Data Analytics (CDA)\u003C\/a\u003E\u0026nbsp;and\u0026nbsp;\u003Ca href=\u0022http:\/\/www.cc.gatech.edu\/~bader\/index.html\u0022 target=\u0022_blank\u0022\u003ECenter for High Performance Computing (HPC)\u003C\/a\u003E\u0026nbsp;will be held on most Thursdays during the Fall and Spring Semesters and feature a mix of topics, including those related to big data for materials and manufacturing, as well as other topics critical to the broader area of big data.\u003C\/p\u003E\u003Ch6\u003EAll meetings are held on Thursdays during lunchtime.\u0026nbsp;\u003C\/h6\u003E\u003Cp\u003E\u003Cstrong\u003EDate:\u003C\/strong\u003E January 23\u003Cbr \/\u003E\u003Cstrong\u003ETopic:\u003C\/strong\u003E\u0026nbsp;\u0022Interactive Visual Analytics for Text Data Analysis\u0022\u003Cbr \/\u003E\u003Cstrong\u003EPresenter:\u003C\/strong\u003E\u0026nbsp;\u003Ca href=\u0022http:\/\/www.cc.gatech.edu\/~hpark\/\u0022 target=\u0022_blank\u0022\u003EHaesun Park\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMany modern data sets can be represented in high dimensional vector spaces and have benefited from computational methods that utilize advanced techniques from numerical linear algebra and optimization. Visual analytics approaches have contributed greatly to data understanding and analysis due to utilization of both automated algorithms and human\u2019s quick visual perception and interaction. However, visual analytics targeting high dimensional large-scale data such as a document collection has been challenging due to low dimensional screen space with limited pixels to represent data.\u003C\/p\u003E\u003Cp\u003EWe present some of the key foundational methods for supervised dimension reduction such as linear discriminant analysis (LDA), dimension reduction and clustering\/topic discovery by nonnegative matrix factorization (NMF), and visual spatial alignment for effective fusion and comparisons by orthogonal Procrustes. We demonstrate how these methods can effectively support interactive visual analytic tasks that involve large-scale document data sets in two of the visual analytics systems, UTOPIAN for interactive topic discovery and VisIRR for visual document retrieval and recommendation.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPrior to joining the College of Computing\u0027s School of Computational Science and Engineering faculty in 2005, Haesun Park was on the faculty at the University of Minnesota, Twin Cities, from 1987 to 2005, and from 2003 to 2005, she also served as a program director for the Computing and Communication Foundations Division at the National Science Foundation in Arlington, Va. She\u0026nbsp;is the director of the NSF\/DHS Foundations of Data and Visual Analytics (FODAVA-Lead) initiative and executive director of the Center for Data Analytics (CDA) at Georgia Tech.\u003C\/p\u003E\u003Cp\u003EPark\u0027s current research interests include numerical algorithms, pattern recognition, bioinformatics, information retrieval, and data mining. She has published more than 100 research papers in these areas and has served on numerous conference committees and journal editorial boards.\u0026nbsp;Currently, she is on the editorial board of \u003Cem\u003EBIT Numerical Mathematics\u003C\/em\u003E, \u003Cem\u003ESIAM Journal on Matrix Analysis and Applications\u003C\/em\u003E, and the \u003Cem\u003EInternational Journal of Bioinformatics Research and Applications\u003C\/em\u003E. In 2008 and 2009, Park served as a conference co-chair for the SIAM International Conference on Data Mining, and in 2013, she was elected as a SIAM Fellow.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EFour Georgia Tech research hubs have launched a new \u201cchalk \u0026amp; talk\u201d brown bag lunch series on Big Data. The weekly series, sponsored jointly by the\u0026nbsp;Institute for Data \u0026amp; High Performance Computing (IDH),\u0026nbsp;\u003Ca href=\u0022http:\/\/www.materials.gatech.edu\/\u0022\u003EInstitute for Materials (IMaT)\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022http:\/\/cda.gatech.edu\/\u0022\u003ECenter for Data Analytics (CDA)\u003C\/a\u003E\u0026nbsp;and\u0026nbsp;\u003Ca href=\u0022http:\/\/www.cc.gatech.edu\/~bader\/index.html\u0022 target=\u0022_blank\u0022\u003ECenter for High Performance Computing (HPC)\u003C\/a\u003E\u0026nbsp;will be held on most Thursdays during the Fall and Spring Semesters and feature a mix of topics, including those related to big data for materials and manufacturing, as well as other topics critical to the broader area of big data.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Four Georgia Tech research hubs have launched a new \u0022chalk \u0026 talk\u0022 brown bag lunch series on Big Data."}],"uid":"27255","created_gmt":"2013-11-08 16:51:33","changed_gmt":"2017-04-13 21:23:53","author":"Josie Giles","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-01-23T11:30:00-05:00","event_time_end":"2014-01-23T13:00:00-05:00","event_time_end_last":"2014-01-23T13:00:00-05:00","gmt_time_start":"2014-01-23 16:30:00","gmt_time_end":"2014-01-23 18:00:00","gmt_time_end_last":"2014-01-23 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"174121":{"id":"174121","type":"image","title":"XDATA - Haesun Park","body":null,"created":"1449179012","gmt_created":"2015-12-03 21:43:32","changed":"1475894816","gmt_changed":"2016-10-08 02:46:56","alt":"XDATA - Haesun Park","file":{"fid":"195808","name":"park1.jpg","image_path":"\/sites\/default\/files\/images\/park1_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/park1_0.jpg","mime":"image\/jpeg","size":1418626,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/park1_0.jpg?itok=zkubNqFA"}}},"media_ids":["174121"],"related_links":[{"url":"http:\/\/www.cc.gatech.edu\/~hpark\/","title":"Haesun Park"}],"groups":[{"id":"1304","name":"High Performance Computing (HPC)"},{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"78621","name":"Big Data; materials; HPC"},{"id":"79311","name":"FLAMEL Traineeship Program"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EHolly Rush\u003Cbr \/\u003E\u003Ca href=\u0022mailto:holly@cc.gatech.edu\u0022\u003Eholly@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}