Reinforcement Learning
Algorithm & Application
Virtual Seminar

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Welcome

This is an online seminar that presents the latest advances in reinforcement learning applications and theory. Our goal is to bring you a virtual seminar (approximately) featuring the latest work in applying reinforcement learning methods in many exciting areas (e.g., health sciences, or two-sided markets).

Topics

Speakers

Slide Susan Murphy Susan Murphy is Professor of Statistic at Harvard University, Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University, and Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences. Her lab works on clinical trial … Slide Bo An Bo An is a President’s Council Chair Associate Professor in Computer Science and Engineering, Nanyang Technological University, Singapore. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst. His current research … Slide Michael R. Kosorok Michael R. Kosorok, Ph.D., the W.R. Kenan, Jr. Distinguished Professor of Biostatistics and Professor of Statistics and Operations Research at the University of North Carolina at Chapel Hill, received his PhD in Biostatistics from the University of Washington in 1991. He is an internationally known biostatistician… Slide Tony Qin Tony Qin is Principal Research Scientist and Director of the reinforcement learning group at DiDi AI Labs, working on core problems in ridesharing marketplace optimization. Prior to DiDi, he was a research scientist in supply chain and inventory optimization at Walmart Global E-commerce... Slide Yansheng Wang Yansheng Wang is currently a first year Ph.D. candidate in School of Computer Science and Engineering at Beihang University. He is working on crowd intelligence, spatial crowdsourcing and reinforcement learning. He has published several papers in highly refereed conferences ... Slide Fanyou Wu  Fanyou Wu is now a Ph.D. candidate in Forestry and Natural Resources Department, Purdue University. His research focuses on the application of machine learning in forestry and transportation, and has published several paper in those fields. He has also won many championships and runners-up ... Slide Eric Laber Eric Laber is the Goodnight Distinguished Professor and Faculty Scholar in the department of Statistics at NC State University. He joined NC State after completing his PhD at the University of Michigan in 2011. His research focuses on methods development for data-driven decision making ...
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Recent Events

November 19th, 2020

10:00am – 11:00pm EST

Nathan Kallus, Cornell University

Statistically Efficient Offline Reinforcement Learning

Discussion Leader: Chengchun Shi

November 5th, 2020

10:00am – 11:00am EST

Eric Laber, NC State University

Partially observable Markov Decision Processes as a Model for Chronic Illness


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