University of Guelph

Vector Institute

Ontario, Canada

I’m interested in machine learning theory, so that models can be deployed with confidence in practice. This has led me to take an inter-disciplinary approach, bridging information theory, statistical physics, and elements of electrical and computer engineering.

My current research interests are motivated by the “adversarial examples” problem, which limits opportunities for the responsible deployment of deep learning models in performance critical settings, e.g., commercial autopilots, or health care. More generally, I am interested in representation learning, and causal modeling.

Personal interests include electronics, traveling, cycling, and sailing.