I am an assistant professor in the Department of Statistics at Indiana University. I am broadly interested in developing likelihood-based and Bayesian methods for various statistical problems with strong theoretical support. Specifically, I have been focusing on likelihood-based inference for network data, theory and methods for high-dimensional data, Bayesian nonparametrics, and Bayesian methods for computer experiments and uncertainty quantification. On the application side, I am also interested in designing new Bayesian methods for computational biology.
I received my Ph.D. from the Department of Applied Mathematics and Statistics at Johns Hopkins University under the supervision of Dr. Yanxun Xu.
Ph.D. in Applied Mathematics and Statistics, 2020
Johns Hopkins University, Baltimore, MD, U.S.
M.A. in Applied Mathematics and Statistics, 2016
Johns Hopkins University, Baltimore, MD, U.S.
B.Sc in Mathematics and Applied Mathematics, 2014
South China University of Technology