My research focuses primarily on adding Bayesian filtering and optimal control concepts to probabilistic machine learning paradigms...
In short, classical filtering and optimal control methods are typically slow and difficult to tune for systems which are both high-dimensional and nonlinear (such as human-robot interaction) while machine learning methods do not provide guarantees for stability and robustness in learned controllers. By merging ideas from both I am working to create intelligent robot control methods which are an order of magnitude faster than conventional optimal controllers.