Ray Bai

Ray Bai is an Assistant Professor in the Department of Statistics at the University of South Carolina (USC), part of the McCausland College of Arts and Sciences. Effective August 2025, he will join the George Mason University (GMU) Department of Statistics as a faculty member. His research focuses on Bayesian statistics, deep learning, and causal inference, with applications to biomedical and public health challenges such as genomic studies, drug repositioning, and electronic health records analysis. Bai holds a PhD in Statistics from the University of Florida (2018), an MS in Applied Mathematics from the University of Massachusetts Amherst, and a BA from Cornell University. His work has been supported by the National Science Foundation (NSF).

Education:

• PhD in Statistics, University of Florida (2018)
• MS in Applied Mathematics, University of Massachusetts Amherst
• BA, Cornell University

Research interests include scalable algorithms for high-dimensional data, nonconvex optimization, and distributed inference methodologies. His work bridges statistical theory with practical applications in healthcare, emphasizing robustness and computational efficiency. Recent contributions address challenges in single-index models for skewed data, generative quantile regression, and Bayesian varying-coefficient models.

Advising includes supervising PhD students Zile Zhao and Shijie Wang, who have contributed to survival analysis and deep learning frameworks. Future openings for students at GMU focus on Bayesian methodology and machine learning.

Labs/Teams: Collaborates on projects involving interdisciplinary teams in biostatistics and computational biology.