School of Medicine
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TAMER CETIN
Affiliate, Medicine - Primary Care and Population Health
BioTamer Çetin is a research scientist at Stanford working in applied econometrics, causal inference, and machine learning, with a focus on developing robust methods for statistically reliable empirical analysis. His research spans econometric theory and applications involving weak identification, instrumental variables, debiased machine learning, and high-dimensional causal estimation.
At Stanford, his work connects modern statistical learning tools with classical questions in identification, inference, and policy evaluation. His research aims to improve the reliability of empirical conclusions when researchers and scientists face complex data, multiple identification strategies, or imperfect instruments.
Before joining Stanford, Dr. Çetin held research and teaching roles across academia, consulting, and industry. He has taught courses in economics, econometrics, and data science. His broader interests include causal inference, health and labor economics, machine learning for empirical research, market regulation, and antitrust.
