Tengyuan Liang

I am a Professor of Econometrics and Statistics at the University of Chicago, Booth School of Business.

I use insights and principles from learning theory and statistical theory to understand models and data. On the applied side, I study causal machine learning in business and economic contexts.

Currently, I think about the following topics:

– Generative models: mathematical theory and inference methods;

– Causal inference: individualization and optimized experimentation;

– Overparametrization and regularization: insights and algorithms.