{"656970":{"#nid":"656970","#data":{"type":"event","title":"ML PhD Defense of Dissertation | Shixiang (Woody) Zhu: Statistical Learning and Decision Making for Spatio-Temporal Data","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EStatistical Learning and Decision Making for Spatio-Temporal Data\u003Cbr \/\u003E\r\n\u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003EApril 8\u003Csup\u003Eth\u003C\/sup\u003E, 2022\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cstrong\u003ETime:\u0026nbsp;\u003C\/strong\u003E12:00 pm \u0026ndash; 1:30 pm EDT\u003Cbr \/\u003E\r\n\u003Cstrong\u003ELocation\u003C\/strong\u003E:\u0026nbsp;\u003Ca href=\u0022https:\/\/bluejeans.com\/5007129655\u0022 title=\u0022https:\/\/bluejeans.com\/5007129655\u0022\u003Ehttps:\/\/bluejeans.com\/5007129655\u003C\/a\u003E\u0026nbsp;(BlueJeans meeting link) \/ Main 126\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EStudent Name\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EShixiang (Woody) Zhu\u003Cbr \/\u003E\r\nMachine Learning PhD Student\u003Cbr \/\u003E\r\nH. Milton Stewart School of Industrial and Systems Engineering\u003Cbr \/\u003E\r\nGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1 Yao Xie (Advisor)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2 Dr. He Wang (H. Milton Stewart School of Industrial \u0026amp; Systems Engineering, Georgia Institute of Technology)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E3 Dr. Pascal Van Hentenryck (H. Milton Stewart School of Industrial \u0026amp; Systems Engineering, Georgia Institute of Technology)\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E4 Dr. George Nemhauser (H. Milton Stewart School of Industrial \u0026amp; Systems Engineering, Georgia Institute of Technology)\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E5 Dr. Feng Qiu (Argonne National Laboratory)\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\u003ESpatio-temporal data modeling and sequential decision analytics are a growing area of research with an enormous amount of modern spatio-temporal data being consistently collected from the real world. These applications include power grids, public safety systems, healthcare systems, financial markets, social media, IoT networks, and even our personal mobile devices. Understanding the intricate spatio-temporal dynamics behind these data requires the next generation of mathematical and statistical algorithms based on quantitative models of human and physical dynamics. In this thesis, we first present the recent developments in this area with both methodological advances and various real-world applications. Then we develop new theoretical and algorithmic techniques for capturing the dynamics of real-world spatio-temporal data by combining cutting-edge machine learning and classical statistical models. We also formulate the sequential decision making process as an optimization problem in a data driven manner, which could suggest better decisions by taking advantage of the historical knowledge. Lastly, we study a wide array of real-world spatio-temporal datasets using our proposed methods. The results demonstrate the value of spatio-temporal analytics in understanding computational, physical, and social systems.\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESpatio-temporal data modeling and sequential decision analytics are a growing area of research with an enormous amount of modern spatio-temporal data being consistently collected from the real world.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Spatio-temporal data modeling and sequential decision analytics are a growing area of research with an enormous amount of modern spatio-temporal data being consistently collected from the real world. "}],"uid":"27592","created_gmt":"2022-04-04 16:14:18","changed_gmt":"2022-04-04 16:14:18","author":"Joshua Preston","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-08T13:00:00-04:00","event_time_end":"2022-04-08T14:30:00-04:00","event_time_end_last":"2022-04-08T14:30:00-04:00","gmt_time_start":"2022-04-08 17:00:00","gmt_time_end":"2022-04-08 18:30:00","gmt_time_end_last":"2022-04-08 18:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"576481","name":"ML@GT"}],"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\u003E\u003Ca href=\u0022mailto:Niebuhr, Stephanie E \u0026lt;stephanie.niebuhr@cc.gatech.edu\u0026gt;\u0022\u003E\u003Cstrong\u003EStephanie Niebuhr\u003C\/strong\u003E\u003C\/a\u003E\u003Cbr \/\u003E\r\nAcademic Advisor, ML PhD program\u003Cbr \/\u003E\r\nCollege of Computing\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}