Zijun Gao

Ph.D. Student in Statistics, admitted Autumn 2017
Zijun Gao
Zijun Gao is a Ph.D. candidate in the Statistics Department at Stanford University advised by Professor Trevor Hastie. Prior to attending Stanford, she obtained a Bachelor of Science in Mathematics from Tsinghua University, China.

Her major research interest is causal inference with heterogeneity. Her works focus on developing efficient methodologies of estimating and validating heterogeneous causal effects with applications of large-scale healthcare databases. She also works on real-world data motivated topics such as conditional density estimation and batched bandit problem.
Graduation Year
Dissertation Title
Applications of Machine Learning to Some Statistical Inference Problems
Advisor Name
Committee Names
Tibshirani, Wager