• Statistician and Economist, with research work focusing on causal inference with high-dimensional data, applications of machine learning methods, counterfactual and policy analysis, distribution and quantile methods, shape restrictions, partial identification, and extreme value theory.

• The International Ford Professor at the Department of Economics and Center for Statistics and Data Science at the MIT, and an International Fellow at CEMMAP, University College London.

• Joined MIT in 2000, after completing Ph.D. in Economics at Stanford University in 2000 and M.S. in Statistics from the UIUC in 1997. 

• Also worked as a Senior Principal Scientist for the Core Artificial Intelligence group at Amazon.com for several years, while on academic leave.

• Co-Editor of the Econometrics Journal and an Action Editor of the Journal of Machine Learning Research.

• Elected Fellow of the American Academy of Arts and Sciences, Econometric Society, and Institute of Mathematical Statistics.

• Inaugural Moderator for the Economics section of ArXiv.org launched in 2017. 

• Co-author of the new Interdisciplinary Ph.D. program in Statistics  at MIT — by the MIT’s Institute for Data, Systems, and Society. Co-author of the new B.S. degree 6-14 in Computer Science, Economics, and Data Science at MIT

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