LI Bo

Bo Li is a professor at the School of Data Science, Fudan University, and holds a position at the School of Economics, Fudan University. He is also affiliated with the Institute of Statistics and Data Science, Fudan University. His research focuses on statistical learning, causal inference, and data science, with applications in economics, healthcare, and industry. He has made significant contributions to the fields of high-dimensional statistics, causal inference, and machine learning, particularly in the areas of treatment effect estimation, counterfactual prediction, and robust learning under distributional shifts. His work has been published in top-tier journals and conferences, including the Journal of the American Statistical Association, Journal of the Royal Statistical Society, and NeurIPS, ICML, and KDD. Bo Li has also been recognized for his research and teaching excellence, and he is actively involved in mentoring students and early-career researchers.

Bo Li is a scholar in the fields of Statistics, Economics, Management Science, and Marketing. His research focuses on statistical methods for high-dimensional data, including particle filters, regularization, and shrinkage tuning parameter selection. He also explores economic disparities, such as gender pay gaps and employment trends in China. His work addresses challenges in causal inference, treatment effect estimation, and model misspecification. Li's research includes methods for stable prediction, heterogeneous risk minimization, and counterfactual prediction. He has published on topics such as the glass ceiling effect, data-driven variable decomposition, and penalized likelihood estimation for covariance matrix monitoring. His contributions span both theoretical and applied aspects of statistical and economic modeling.