Jing Li

I am a postdoctoral researcher in the CAUSALab at the Harvard T.H. Chan School of Public Health, advised by Prof. Miguel Hernán.

My research lies at the intersection of causal inference and computer science, with a focus on advancing classical causal inference methods by integrating modern machine learning techniques. To bridge the gap between causal inference methodology and practical application, I also develop scientific computing tools that enable scalable and reproducible implementation of causal inference methods. In particular, I have been involved in open-source software development, leading and contributing to packages including pygformula, gformula, and gformulaICE, which support causal inference analyses for longitudinal observational data.

Previously, I received my Ph.D. in Computer Science from the School of Computer Science at Peking University, where I was advised by Prof. Yizhou Wang. Prior to my Ph.D., I obtained my bachelor's degree in Statistics from the School of Mathematics and Statistics at Wuhan University.