My research interests are diverse but linked through the common thread of computation-heavy statistical techniques, particularly Bayesian/semi-Bayesian techniques. My long-term research goals involve developing inferential statistical methods for modern-day problems involving complex big and high-dimensional data, e.g., those arising in cancer genomics, computational biology, and medicine. Alongside methodology development, I also work on developing theoretical foundations and software implementations of novel statistical techniques. A few of my current research directions are as follows: (a) inferential statistical modeling in genomics and computational biology, (b) statistical methods for medical product safety assesment and pharmacovigilance, (d) theoretical analysis of Markov chain Monte Carlo and other Bayesian computation algorithms, (d) Bayesian methods for dimension reduction in multivariate analysis, and (e) statistical analyses in collaborative scientific studies.

Please see Publications for a detailed list of publications. Feel free to send me an email if you’re interested in any of these directions, and would like to discuss research and collaboration opportunities.