My current research interests include Bayesian approaches to machine learning, artificial intelligence, statistics, information retrieval, bioinformatics, and computational motor control. Statistics provides the mathematical foundations for handling uncertainty, making decisions, and designing learning systems. I have recently worked on Gaussian processes, non-parametric Bayesian methods, clustering, approximate inference algorithms, graphical models, Monte Carlo methods, and semi-supervised learning. I have also worked on Computational Neuroscience and Sensorimotor Control. I am interested in how computational theories of learning relate to cognition.