My PhD work is in Statistical Machine Learning. I study generalizations to Structured Prediction methods — Probabilistic Graphical Models (PGMs), Markov Random Fields (MRFs), Structured Support Vector Machines (Structured SVMs) — that leverage multiple outputs for increased expressivity and performance. My research emphasizes models and inference/learning algorithms for generating multiple diverse predictions.
I have graduated and am taking a temporary leave from full-time research during fall 2014 to work on a VC funded startup.
During my PhD, I was advised by Rob Rutenbar and I collaborated closely with Dhruv Batra and Pushmeet Kohli.
I spent summer 2013 at Microsoft Research Cambridge. Before my PhD, I worked as a Hardware Engineer at National Instruments.