Department of Statistics
Department of Electrical Engineering and Computer Science (by courtesy)
University of Michigan, Ann Arbor
In Every City, There's a George Floyd
My research group is engaged in fundamental research in the following areas:
I like to work in multi-disciplinary teams and am currently interested in
machine learning problems arising in several scientific areas, especially behavioral sciences, brain sciences,
chemistry, learning sciences, life sciences, and medicine.
My work has been supported by an NSF CAREER grant (2015), a Sloan Research Fellowship (2017), and an Adobe Data Science Research Award (2020).
Statistical learning theory: We are developing theory and algorithms for
predictions problems (e.g., learning to rank and multilabel learning) with complex label
spaces and where the available human supervision is often weak. Another focus
is on dependent and/or non-stationary data (such as in time series
Sequential prediction in a game theoretic framework: We are trying to
understand the power and limitations of sequential prediction algorithms
when no probabilistic assumptions are placed on the data generating mechanism.
High dimensional and network data analysis: We are developing scalable algorithms with
provable performance guarantees for learning from high dimensional and network
Optimization algorithms: We are creating incremental, distributed and parallel
algorithms for machine learning problems arising in today's data rich world.
Reinforcement learning: We are synthesizing and further developing concepts and techniques from
artificial intelligence, control theory and operations research for pushing
frontier in sequential decision making with a focus on delivering personalized
health interventions via mobile devices. Here is a short video from a talk I gave at NYAS
and an article from ISR Sampler. A related seminar series that I ran during 2013-2018 is archived here.
My alma maters are IIT Kanpur (B.Tech., 2002) and UC Berkeley
(M.A., 2005 and Ph.D., 2007. Advisor: Peter Bartlett).
I was a research assistant professor at TTIC from 2008 to 2010.
From 2010 to 2012, I was a post-doctoral fellow at UT Austin where I worked with Inderjit Dhillon and
My younger brother Anuj Tewari is a Research Manager at Facebook.
I am one of the organizers of a semester long program on the Theory of Reinforcement Learning that will run during Fall 2020 at the Simons Institute for the Theory of Computing.
Activities at U-M I'm involved with:
Students and Postdocs
270 West Hall
1085 South University
Ann Arbor, MI 48109-1107