Anish’s research interests are in causal inference, econometrics, and high-dimensional statistics. He is particularly interested in data-driven decision-making in engineering and social systems using tools from econometrics and machine learning.
Before joining Columbia, he was a postdoctoral scientist at Amazon, Core AI and also at the Simons Institute, UC Berkeley. He received his PhD in EECS from MIT, where he was fortunate to be advised by Alberto Abadie, Munther Dahleh, and Devavrat Shah. He has served as a technical consultant to TauRx Therapeutics and Uber Technologies on questions related to experiment design and causal inference. He was also a management consultant at Boston Consulting Group.
For his dissertation, he received the INFORMS George B. Dantzig best thesis award (2nd place), and the ACM SIGMETRICS outstanding thesis award (2nd place). He has also received best paper awards from Unisex NSDI’23 and the American Statistical Association.