Feng Liang

Feng Liang is a Professor of Statistics at the University of Illinois Urbana-Champaign (UIUC), serving as Interim Director of the Program in Actuarial Science and Risk Management within the College of Liberal Arts and Sciences. He is affiliated with the Information Trust Institute and the Biomedical and Translational Sciences department. Liang holds a Ph.D. in Statistics from Yale University (2002) and a B.A. in Mathematics from Peking University (1997).

His research focuses on Bayesian methods, decision theory, information theory, and data mining, with applications to machine learning and statistical modeling. Notable contributions include work on predictive density estimation, model calibration, uncertainty quantification, and high-dimensional data analysis. His recent publications address topics like regression recalibration, minimax optimality in diffusion models, and Bayesian variable selection techniques.

Liang has held editorial roles, including Associate Editor for Bayesian Analysis (2009–2015) and Editor for the ISBA Bulletin (2013–2015). His research spans theoretical advancements in statistical methodology and practical applications in fields like hydrology and biomedical sciences. He collaborates internationally and has contributed to interdisciplinary projects, including machine learning for environmental modeling and neural architecture search.

His work emphasizes bridging statistical theory with real-world challenges, particularly in uncertainty estimation, graphical models, and computational efficiency in Bayesian frameworks.