I am currently working on statistical methodologies and models involving large data sets from remote sensing, data networks (internet and sensor networks), neuroscience, finance, and bioinformatics. Together with my students and collaborators, I have been working on different areas of statistical machine learning, theoretical and computational.  These areas include boosting, Lasso, support vector machines (SVM), and semi-supervised learning.  On the computational side, we have developed algorithms such as BLasso and iCAP for sparse modeling.

My past research areas have also included empirical processes, markov chain monte carlo, signal processing, the minimum description length principle (MDL), and  information theory.