Devavrat Shah

Devavrat Shah is the Andrew (1956) and Erna Viterbi Professor in MIT’s Department of Electrical Engineering and Computer Science (EECS) and director of the Statistics and Data Science Center within MIT’s Institute for Data, Systems and Society (IDSS). Shah is the faculty director of the MIT Deshpande Center for Technological Innovations. He is also a visiting adjunct professor at the Tata Institute of Fundamental Research. His research focuses on statistical inference and stochastic networks, and his contributions span a variety of areas including resource allocation in communications networks, inference and learning on graphical models, and algorithms for social data processing, including ranking, recommendations and crowdsourcing. Within networks, his work spans a range of areas across electrical engineering, computer science and operations research. He earned a BS in computer science and engineering from the Indian Institute of Technology, and a PhD in computer science from Stanford University.

Publications

• Malani, A., Soman, S., Asher, S., Imbert, C., Tandel, V., Agarwal, A., Alomar, A., Sarker, A., Shah, D., Shen,D., Gruber, J., Sachdeva, S., Kaiser, D., Bettencourt, L. M. A. (2020). Adaptive control of COVID-19 outbreaks in India: Local, gradual, and trigger-based exit paths from lockdown. National Bureau of Economic Research Working Paper Series.
• Shah, D., Song, D., Xu, Z., Yang, Y. (2020). Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation.
• Agarwal, A., Alomar, A., Sarker, A., Shah, D., Shen,D., Yang, C. (2020). Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?

Media

• August 19, 2020: EdExLive, Great Learning launches online bootcamp in Data Science in collaboration with MIT faculty.
• May 15, 2020: MIT News, A data-driven response to a pandemic.
• December 9, 2019: MIT News, Model beats Wall Street analysts in forecasting business financials.