I am an Assistant Professor of Statistics at the University of South Carolina. I joined the Department of Statistics at U of SC in 2020 after spending two years as a postdoc at the University of Pennsylvania under the supervision of Yong Chen and Mary Boland. I obtained my PhD in Statistics from the University of Florida in 2018 under the supervision of Malay Ghosh.

My methodological and theoretical research focuses on high-dimensional modeling and scalable machine learning algorithms for large and complex data sets. My recent work has been on developing flexible (mostly Bayesian) methods that relax assumptions such as linearity, Gaussianity, and/or independence. Some of the statistical tools I use include nonconvex optimization, sparsity-inducing priors, and decision tree ensembles. My applied research focuses on meta-analysis, spatiotemporal modeling, and analysis of electronic health records.

Graduate students: Interested in working with me? I have projects on: high-dimensional modeling, scalable Bayesian computing, and spatiotemporal statistics. Please feel free to reach out.

Curriculum vitae: CV_Bai (last updated February 2021)
Google Scholar: Ray Bai
Twitter: @raybai07