Yihong Gu

I'm a Postdoctoral Research Fellow at the Department of Biomedical Informatics, Harvard Medical School, advised by Prof. Tianxi Cai. Previously, I obtained my Ph.D. from the Department of Operations Research and Financial Engineering at Princeton University, where I was fortunate to be advised by Prof. Jianqing Fan. Prior to Princeton, I received my bachelor's degree from the Department of Computer Science and Technology at Tsinghua University.

My research spans algorithmic statistical learning, nonparametric statistics, deep learning, causal inference, variable selection, factor models, robust statistics, and their applications in health studies. Here are some topics I am working on:

Learning causality using data from multiple environments
Deep learning for statistical estimation
Statistical analysis of deep learning
Fundamental limits in statistical estimation

News

[2025/06] I joined the Department of Biomedical Informatics at Harvard Medical School as a Postdoctoral Research Fellow.

[2025/05] Our paper ''Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning" has been accepted to the Annals of Statistics.

[2025/05] I successfully defended my Ph.D.! My dissertation covers two works on statistical estimation using neural networks and three works on invariance learning.

[2025/01] New paper "Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization": we show learning invariance is fundamentally hard in computation, and also bridge invariance learning and distribution robust optimization in the method.