I am a Professor of Statistics in the Department of Mathematics at the University of Maryland. Some of my recent interests are in understanding theoretical foundations of deep neural network models and AI from the lens of statistical theory. My other research expertise lie in (1) developing Bayesian model and theory for dimensional and infinite-dimensional models, and variational Bayes theory, (2) statistics on manifolds or broadly geometry & statistics, (3) statistical network analysis and (4) statistical foundations of deep neural network models such as deep generative models.
My applied interests lie in leveraging topological and geometric approaches for data analysis, particularly through the use of topological data analysis (TDA) tools to study data spanning continuous and discrete structures, including TDA sequences and networks.