I’m an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. I’m a member of the Waterloo Institute for Artifical Intelligence (waterloo.ai), the Waterloo Institute for Complexity and Innovation (WICI) and Secretary of the Canadian Artificial Intelligence Association (CAIAC) which coordinates the yearly organization of the Canadian Conference on AI. I received his Ph.D. and M.Sc. in Computer Science from the University of British Columbia working in the Laboratory for Computational Intelligence with David Poole. Before coming to Waterloo he completed a postdoc at Oregon State University working with Tom Dietterich’s machine learning group on robust decision making under uncertainty in simulated Forest Fire domains.
In my research I seek out dependable and transparent ways to augment human decision making in complex domains. That complexity is what Artificial Intelligence/Machine Learning (AI/ML) makes research so difficult as well as exciting.
The complexity could come from the presence of spatial structure, large scale streaming data, uncertainty, or unknown causal structure, or interaction of multiple decision makers.
My focus is on developing new algorithms, methodologies, simulations, and datasets within the fields of Reinforcement Learning (RL), Deep Learning, Manifold Learning and Ensemble Methods. I often work in collaboration with academic researchers, industry researchers and engineers or policy-makers in diverse fields such as sustainable forest management, physics and chemistry, autonomous development and medical imaging.
I’m always happy to talk to people about my research, or the impact of AI/ML/RL on our world and its role in our society in the future. I do not take on many incoming students, so if you are hoping to join my lab as a graduate student for research please read this note.