I'm an assistant professor at the University of Toronto. My research focuses on constructing deep probabilistic models to help predict, explain and design things. For example:

Neural ODEs, a kind of continuous-depth neural network,
Automatic chemical design using generative models,
Gradient-based hyperparameter tuning,
Structured latent-variable models for modeling video,
and Convolutional networks on graphs.
Previously, I was a postdoc in the Harvard Intelligent Probabilistic Systems group with Ryan Adams. I did my Ph.D. at the University of Cambridge, where my advisors were Carl Rasmussen and Zoubin Ghahramani. My M.Sc. advisor was Kevin Murphy at the University of British Columbia. I spent a summer working on probabilistic numerics at the Max Planck Institute for Intelligent Systems, and the two summers before that at Google Research, doing machine vision. I co-founded Invenia, an energy forecasting and trading firm where I still consult. I'm also a founding member of the Vector Institute.