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Causal Inference

Ambarish Chattopadhyay

I am a Postdoctoral Fellow at Stanford Data Science, where I work with Professor Guido Imbens. My research interests lie in developing statistical theory and methods for causal inference in randomized experiments and observational studies, with applications to problems in social and medical sciences.  As part of my doctoral research, I worked on creating balanced, efficient, and robust experimental designs to randomly assign individuals to multiple treatment groups, which has been used in designing clinical trials on internet-based cognitive behavioral therapy. I also worked on developing methodology to generalize causal inferences from a study to an arbitrary target population of interest. My research as a Stanford Data Science fellow broadly explores statistical methods to learn about causal effects from observational data, focusing on settings with interference between units.

I obtained my Ph.D. from the Department of Statistics, Harvard University in 2022, under the supervision of Dr. Jose Zubizarreta. During my Ph.D., I also worked with Prof. Carl Morris and Prof. Kosuke Imai. Previously, I received a Bachelor’s degree (B.Sc.) in Statistics from St. Xavier’s College, Kolkata (under University of Calcutta) in 2015 and a Master’s degree in Statistics (M.Stat) from Indian Statistical Institute in 2017.  I grew up in a town called Diamond Harbour in West Bengal, India.