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Sendhil Mullainathan is a Distinguished Fellow at the University of Chicago Booth School of Business. His current research uses machine learning to understand complex problems in human behavior and social policy, particularly in the field of medicine. He explores computational techniques that can uncover biomedical insights from large-scale health data. His past work has combined insights from economics and behavioral science with causal inference tools—utilizing lab, field, and natural experiments—to address social issues such as discrimination and poverty. Significant papers include his studies on the impact of poverty on mental bandwidth, algorithms for improving judicial decision-making, and the effects of higher cigarette taxes on smokers' happiness. Mullainathan is a co-author of the book 'Scarcity: Why Having Too Little Means So Much' and regularly contributes to The New York Times. His research has been published in numerous prestigious journals including The Quarterly Journal of Economics, Science, and The American Economic Review. He co-founded the nonprofit ideas42 and the Abdul Latif Jameel Poverty Action Lab, promoting the use of randomized control trials in development. He has received notable accolades such as the MacArthur “Genius Grant” and was designated a “Young Global Leader” by the World Economic Forum. His previous academic positions include the Robert C. Waggoner Professorship at Harvard University, where he taught courses on machine learning and big data. Mullainathan's interests include basketball and classic espresso machines.
The doctoral program at Booth is organized into 'dissertation areas' which include Accounting, Behavioral Science, Econometrics and Statistics, Finance, Marketing, and Operations Management.