PhD Students: please attend a special meeting with Prof. Sanmay Das, of Washington University, who is a faculty candidate for GMU's Department of Computer Science.


The meeting is TOMORROW (Wednesday) in Research Hall 163 at NOON.  It is only 30 minutes long.


Prof. Das specializes in the connections between artificial intelligence, machine learning, and algorithms applied to the social sciences.


Here is Prof. Das's bio.


Sanmay Das is an associate professor in Computer Science and Engineering and the chair of the steering committee of the newly formed Division of Computational and Data Sciences at Washington University in St. Louis. He has broad interests across AI, machine learning, and computational social science. His research interests are in designing effective algorithms for agents in complex, uncertain environments, and in understanding the social or collective outcomes of individual behavior. His recent work focuses on algorithmic allocation of scarce societal resources, with an eye towards the distributive justice implications of different policies and mechanisms. Dr. Das is chair of the ACM Special Interest Group on Artificial Intelligence, a member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems, and serves as an associate editor of the ACM Transactions on Economics and Computation and of the Journal of Artificial Intelligence Research. Dr. Das has served as program co-chair of the AAMAS and AMMA conferences and area chair for AAAI, in addition to regularly serving as a senior program committee member of major conferences including IJCAI, AAAI, EC, and AAMAS. He has been recognized with awards for research and teaching, including an NSF CAREER Award and the Department Chair Award for Outstanding Teaching at Washington University. He has worked with the US Treasury department on machine learning approaches to credit risk analysis, and occasionally consults in the areas of technology and finance. He holds a Ph.D. from MIT, and a Bachelor's degree from Harvard.