Department of Computer Science, University of Toronto
Fields of Study
Areas of Interest
Approximate Bayesian Inference
David Duvenaud is an assistant professor in computer science and statistics at the University of Toronto. He holds a Canada Research Chair in generative models. His postdoctoral research was done at Harvard University, where he worked on hyperparameter optimization, variational inference, and chemical design. He did his Ph.D. at the University of Cambridge, studying Bayesian nonparametrics with Zoubin Ghahramani and Carl Rasmussen. David spent two summers in the machine vision team at Google Research, and also co-founded Invenia, an energy forecasting and trading company.