I work on probabilistic programming, which means using techniques from the field of programming languages to make Bayesian modelling easier to use and more accessible. I have also worked on kernel mean embeddings and their applications to probabilistic programming. I am currently based in Cambridge as a part of the Cambridge-Tuebingen PhD programme.
Advances in Neural Information Processing Systems 29, pages: 1732-1740, (Editors: D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett), Curran Associates, Inc., 30th Annual Conference on Neural Information Processing Systems (NIPS), 2016 (conference)
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems