Sanmay Das has been elected chair of the Association for Computing Machinery's Special Interest Group on Artificial Intelligence (SIGAI) for a three-year term that began July 1.
The group's focus is the study of intelligence and its realization in computer systems, and its mission is to promote and support AI-related conferences. The group publishes a quarterly newsletter, AI Matters, with ideas and announcements of interest to the AI community.
Das, associate professor of computer science & engineering, also is chair of the steering committee of the university's newly formed Division of Computational & Data Sciences, a doctoral program designed to train students interested in disciplines that apply data and computing to some of today's most important societal problems. He is a member of the department's innovative machine learning and artificial intelligence faculty who design novel algorithms and study their theoretical properties and real-world applicability. In addition to their interdisciplinary collaborations with WashU researchers, the faculty members also are frequently called on by industry and media for their expertise.
In addition to serving with the Association for Computing Machinery (ACM), he is a member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems (IFAAMS) and serves as an associate editor of the ACM Transactions on Economics and Computation and of the Journal of Artificial Intelligence Research. He has served as program co-chair of the Autonomous Agents and Multi-Agent Systems (AAMAS) conference and area chair for the Association for the Advancement of Artificial Intelligence (AAAI), in addition to regularly serving as a senior program committee member of major conferences including International Joint Conference on Artificial Intelligence, AAAI, Economics and Computation, and AAMAS.
Das has received awards for research and teaching, including an NSF CAREER Award and the Department Chair Award for Outstanding Teaching at WashU. He has worked with the U.S. Treasury department on machine learning approaches to credit risk analysis, and occasionally consults in the areas of technology and finance.
Das earned doctoral and master's degrees from Massachusetts Institute of Technology in 2006 and 2003, respectively, and a bachelor's degree from Harvard College in 2001.