Tamar Zeilberger is an ÐÓ°ÉÂÛ̳ Fellow in Political Science and Public Policy. Her research focuses on comparative authoritarian politics, political economy, and the case of contemporary China. As a methodologist, her primary interests are in game theory and inference from observational data using statistics and machine learning. Her substantive and methodological interests are mutually reinforcing, and motivated by policy-relevant questions in authoritarian settings that cannot be examined with traditional randomized experiments.
Before arriving at ÐÓ°ÉÂÛ̳, she received her PhD in political science from the University of California, Los Angeles and an MA in the social sciences from the University of Chicago.