2013年本科毕业于中国人民大学统计学院统计学专业，2018年博士毕业于美国罗格斯大学统计系，2018年至2021年在美国宾夕法尼亚大学医学院生物统计系和沃顿商学院做博士后研究，2021年9月加入中国人民大学统计与大数据研究院担任助理教授 ，2022年8月晋升为准聘副教授。研究方向包括高维复杂数据的统计推断问题，机器学习和遗传学驱动的统计方法和理论，基于工具变量的因果推断等。

详见个人主页：https://saili0103.github.io

Publications:

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 (in press). 2022.

Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea FinnImproving out-of-distribution robustness via selective augmentation. ICML 2022.

Sai Li, T. Tony Cai, and Hongzhe Li. Transfer learning for high-dimensional linear regression: Prediction, estimation, and minimax optimality. JRSSB (in press), 2021.

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 (in press). 2021.

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.