I am currently a Research Assistant Professor at the Toyota Technological Institute at Chicago.
Prior to this I was a Simons-Berkeley fellow at the Simons Institute for the Theory of Computing. Before that I was at the School of Technology and Computer Science at the Tata Institute of Fundamental Research, Mumbai for my Ph.D. under the guidance of Prof. Prahladh Harsha. I was partly supported by the Google PhD Fellowship (Algorithms).
Earlier, I obtained an M.Sc. degree in Computer Science from CMI. A long time ago, in a galaxy far, far away... I obtained a B.Tech. degree in Mechanical Engineering from IIT, Kharagpur.
My research interests lie broadly in the field of randomized computation. I have dabbled in classical and zero-error information theory, coding theory, and sampling algorithms. Recently, I have been thinking about questions in causal inference and treatment effect estimation, specifically estimating quantile treatment effects and estimating treatment effects in the presence of multiple subpopulations.
The essence of mathematics is proving theorems — and so, that is what mathematicians do: They prove theorems. But to tell the truth, what they really want to prove, once in their lifetime, is a Lemma, like the one by Fatou in analysis, the Lemma of Gauss in number theory, or the Burnside–Frobenius Lemma in combinatorics.
Now what makes a mathematical statement a true Lemma? First, it should be applicable to a wide variety of instances, even seemingly unrelated problems. Secondly, the statement should, once you have seen it, be completely obvious. The reaction of the reader might well be one of faint envy: Why haven’t I noticed this before? And thirdly, on an esthetic level, the Lemma — including its proof — should be beautiful!
-- Proofs from THE BOOK