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Aaron Schein is an Assistant Professor in the Department of Statistics and the College at the University of Chicago, where he is also affiliated with the Data Science Institute. His research focuses on developing methodology in Bayesian statistics, causal inference, and machine learning, particularly as applied to problems in political science, economics, and genetics. Before joining the University of Chicago, he was a postdoctoral fellow at the Data Science Institute at Columbia University. Aaron earned his PhD in Computer Science from the University of Massachusetts Amherst and holds a BA in Political Science. His academic interests span Bayesian statistics, machine learning, applied causal inference, econometrics, and computational social science.
Data Science Institute, Columbia University • New York, NY
Conducted research in data science methodologies.
Department of Philosophy