My research lies at the intersection of Bayesian statistics and machine learning. I am interested in developing statistical theory and methods, hierarchical models, and efficient Bayesian inference for big data. I am currently focused on the development of nonparametric Bayesian hierarchical models for count data analysis, categorical data analysis, mixture modeling (clustering, mixed-membership modeling, topic modeling), dictionary learning (feature learning, factor analysis), network modeling, and deep learning.