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Sai Li Associate Professor

Research Areas: High-dimensional statistics, statistical foundations for machine learning and AI, causal inference.

Office: Room 811, Lyu Dalong Building, Tsinghua University


Email: saili@mail.tsinghua.edu.cn


Go to Sai Li Personal Homepage
职称 Associate Professor 地址 Room 811, Lyu Dalong Building, Tsinghua University
电话 邮箱 saili@mail.tsinghua.edu.cn
个人主页 https://saili0103.github.io

Previous appointments

Associate professor at Department of Statistics and Data Science, Tsinghua University, December 2025 till now.

Associate professor at Institute of Statistics and Big Data, Renmin University of China, September 2022 to November 2025.

Assistant professor at Institute of Statistics and Big Data, Renmin University of China, September 2021 to August 2022.

Postdoctoral researcher at Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, July 2018 to June 2021.


Education

Ph.D., Department of Statistics and Biostatistics, Rutgers Univeristy, 2018.

Bachelor of Economics, School of Statistics, Renmin University of China, 2013.


Publications

Sai Li and Linjun Zhang. Multi-dimensional domain generalization with low-rank structures. Journal of the American Statistical Association(accepted). 2025.

Sai Li and Ting Ye. A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Data. Journal of the Royal Statistical Society: Series B. 87(2), 529-548. 2025.

Jianqiao Wang, Sai Li, and Hongzhe Li. A unified approach to robust inference for genetic covariance. Journal of the American Statistical Association. 119(548): 2585-2597, 2024.

Sai Li, Yisha Yao, and Cun-Hui Zhang. Comment: A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models. Journal of the American Statistical Association. 118(543), 1586–1589, 2023.

Sai Li, Linjun Zhang, T. Tony Cai, and Hongzhe Li. Estimation and inference in high-dimensional GLMs with transfer learning. Journal of the American Statistical Association. 119(546), 1274–1285, 2023.

Sai Li, Tianxi Cai, and Rui Duan. Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach. Annals of Applied Statistics. 17(4): 2970-2992, 2023.

Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, and Chelsea Finn. Improving out-of-distribution robustness via selective augmentation. International Conference of Machine Learning. PMLR 162:25407-25437, 2022.

Sai Li, T. Tony Cai, and Hongzhe Li. Transfer learning in large-scale graphical models with false discovery rate control. Journal of the American Statistical Association. 118(543), 2171–2183, 2022.

Sai Li, T. Tony Cai, and Hongzhe Li. Transfer learning for high-dimensional linear regression: Prediction, estimation, and minimax optimality. Journal of the Royal Statistical Society: Series B.84: 149–173, 2022.

Sai Li, T. Tony Cai, and Hongzhe Li. Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach. Journal of the American Statistical Association. 117(540): 1835-1846, 2022.

Sai Li. Debiasing the debiased Lasso with bootstrap. Electronic Journal of Statistics, 14(1): 2298-2337, 2020.

Sai Li, Ritwik Mitra, and Cun-Hui Zhang. Comment: An adaptive resampling test for detecting the presence of significant predictors. Journal of the American Statistical Association. 110(512): 1455-1456, 2016.