While there has been significant progress at the interface of statistics and computer science in recent years, many fundamental challenges remain. Some are mathematical and algorithmic in nature, such as the challenges associated with optimization and sampling in high-dimensional spaces. Some are statistical, including the challenges associated with multiple decision-making. Others are economic in nature, including the need to cope with scarcity and provide incentives in learning-based two-way markets. I will present recent progress on each of these fronts.
Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research interests bridge the computational, statistical, cognitive and biological sciences. Professor Jordan is a member of the National Academy of Sciences and a member of the National Academy of Engineering. He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He received the IJCAI Research Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and the ACM/AAAI Allen Newell Award in 2009.