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Poster session
Abbas Zaidi · Christoph Kurz · David Heckerman · YiJyun Lin · Stefan Riezler · Ilya Shpitser · Songbai Yan · Olivier Goudet · Yash Deshpande · Judea Pearl · Jovana Mitrovic · Brian Vegetabile · Tae Hwy Lee · Karen Sachs · Karthika Mohan · Reagan Rose · Julius Ramakers · Negar Hassanpour · Pierre Baldi · Razieh Nabi · Noah Hammarlund · Eli Sherman · Carolin Lawrence · Fattaneh Jabbari · Vira Semenova · Maria Dimakopoulou · Pratik Gajane · Russell Greiner · Ilias Zadik · Alexander Blocker · Hao Xu · Tal EL HAY · Tony Jebara · Benoit Rostykus

Author Information

Abbas Zaidi (Duke University)
Christoph Kurz (Helmholtz Zentrum München)
David Heckerman (Amazon)
YiJyun Lin (UNR)

My research interests revolve around the application of machine learning and natural language processing to misinformation and crisis management. My dissertation applies machine learning methods to improve identification of heterogeneous effects of climate change on violent conflict.

Stefan Riezler (Heidelberg University)
Ilya Shpitser (Johns Hopkins University)
Songbai Yan (University of California, San Diego)
Olivier Goudet (INRIA)
Yash Deshpande (MIT)
Judea Pearl (UCLA)

Judea Pearl is a professor of computer science and statistics at UCLA. He is a graduate of the Technion, Israel, and has joined the faculty of UCLA in 1970, where he conducts research in artificial intelligence, causal inference and philosophy of science. Pearl has authored three books: Heuristics (1984), Probabilistic Reasoning (1988), and Causality (2000;2009), the latter won the Lakatos Prize from the London School of Economics. He is a member of the National Academy of Engineering, the American Academy of Arts and Sciences, and a Fellow of the IEEE, AAAI and the Cognitive Science Society. Pearl received the 2008 Benjamin Franklin Medal from the Franklin Institute and the 2011 Rumelhart Prize from the Cognitive Science Society. In 2012, he received the Technion's Harvey Prize and the ACM Alan M. Turing Award.

Jovana Mitrovic (University of Oxford)
Brian Vegetabile (RAND Corporation)
Tae Hwy Lee (University of California, Riverside)

Tae-Hwy Lee is Professor of Economics at University of California Riverside. He received a Ph.D. in economics in 1990 from University of California San Diego under the supervision of Sir Clive W.J. Granger, a Nobel Laureate in Economic Science. He received his undergraduate degree in economics in 1985 from Seoul National University. His primary research and teaching areas are econometrics, statistics, and machine learning, with interests of applications in financial econometrics, time series forecasting, panel data models, maximum score regression, high dimensional modeling in conditional mean and covariance, and causal inference. He has published or has written more than 60 papers in the topics of nonstationary time series, nonlinear time series models, aggregation issues, specification testing, forecasting, inference in predictive regression, causality, volatility models, quantile models, factor models, nonparametric methods, shrinkage methods, model selection, model averaging, causal inference, machine learning methods, high dimensional models, panel data models, and etc. Professor Lee has received several awards including the NSF/ASA/BLS Senior Research Fellowship and the Econometric Theory Tjalling C. Koopmans Prize.

Karen Sachs (Stanford)
Karthika Mohan (UC Berkeley)
Reagan Rose (Harvard University)
Julius Ramakers (University of Duesseldorf)
Negar Hassanpour (University of Alberta)
Pierre Baldi (UC Irvine)
Razieh Nabi (Johns Hopkins University)
Noah Hammarlund (Indiana University)
Eli Sherman (Johns Hopkins University)
Carolin Lawrence (Heidelberg University)
Fattaneh Jabbari (University of Pittburgh)
Vira Semenova (MIT)
Maria Dimakopoulou (Stanford University)
Pratik Gajane (Université Lille 3)
Russell Greiner (University of Alberta)
Ilias Zadik (MIT)

I am a CDS Moore-Sloan (postdoctoral) fellow at the Center for Data Science of NYU and a member of it's Math and Data (MaD) group. I received my PhD on September 2019 from MIT , where I was advised by David Gamarnik. My research lies broadly in the interface of high dimensional statistics, the theory of machine learning and applied probability.

Alexander Blocker (Foresite Capital)
Hao Xu (University of California, Riverside)
Tal EL HAY (IBM Research)
Tony Jebara (Netflix)
Benoit Rostykus (Netflix)

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