Research Interests: Probabilistic machine learning approaches to solve problems in robotics and computer vision

Research Description: My research interests are in the development of probabilistic machine learning and computer vision tools to solve problems in robotics. Specifically, I am interested in building robot perception capabilities for shared autonomy through automatic and lightly supervised machine learning that aims to infer human needs with as little burden on the user as possible, by making use of Bayesian probabilistic sampling and approximation strategies and leveraging advances in representation learning. A particular focus of my work lies in building interpretable machine learning algorithms for robotics, along with explanatory mechanisms, so as to boost trust in and advance the deployment of complex robotic systems.