Devavrat Shah

Devavrat Shah received his BTech degree from IIT Bombay and his PhD degree from Stanford University, both in Computer Science. He is Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT where he has been teaching since 2005.
His research focuses on statistical inference and stochastic networks. His contributions span a variety of areas including resource allocation in communications networks, inference and learning on graphical models, algorithms for social data processing including ranking, recommendations and crowdsourcing and more recently causal inference. His work spans a range of areas across electrical engineering, computer science and operations research. He has been an associate editor for IEEE Transaction on Information Theory, Journal of Operations Research and Queuing Systems as well as lead guest editor for IEEE Journal on Selected Areas in Information Theory on Estimation and Inference. He is a Kavli Fellow of National Academy of Science invited as a distinguished young scientist as part of 2014 Indonesian-American Symposium. He has received paper awards from INFORMS Applied Probability Society, INFORMS Management Science and Operations Management, NeurIPS, ACM Sigmetrics and IEEE Infocom. He has received the Erlang Prize from INFORMS Applied Probability Society and Rising Star Award from ACM Sigmetrics. He has received multiple Test of Time paper awards from ACM Sigmetrics. He is a distinguished alumni of his alma mater IIT Bombay. In 2013, he co-founded the machine learning start-up Celect (part of Nike since August 2019) which helps retailers optimize inventory using accurate demand forecasting. In 2019, he co-founded Ikigai Labs with the mission of building self-driving organization by empowering data business operators to make data-driven decisions with ease of spreadsheets.