A common thread in my research is the harnessing of theoretical techniques from varied disciplines to solve practical problems. I love learning, implementing complicated statistical inference, data-parallel programming, and algorithms in a simple way. Currently I am interested in nonparametric Bayesian methods, scalable machine learning, fast sampling techniques, random graph generative models and applications of machine learning to VLSI CAD.