I am interested in quantifying model uncertainty in dynamical systems. This is useful for generating reliable predictions and building robust control systems. By sampling a variety of scenarios from our model - not just those contained in the data - we can expose our controller to a wider variety of settings, leading to better performance in new ones.
I am also interested in the problem of inference from noisy or incomplete data and in variational inference methods.

Variational Inference; Gaussian Processes; Dynamical Systems; Reinforcement Learning