His research interests lie at the intersection of perception, control and learning. Specific interests include probabilistic programming, probabilistic modeling (particularly with structured Bayesian nonparametrics), reinforcement learning, dynamical systems modeling, information theory, manifold learning, kernel methods, massively parallel processing, visual perception, optimal control, deep neural networks and robotics.