Collaborative Specialization in Artificial Intelligence
About my research
My research spans a number of topics in deep machine learning. I am interested in methodologies such as generative modelling, graph representation learning and sequential decision making. I also pursue applied projects that leverage computer vision to mitigate biodiversity loss.
How my research improves life
Despite widespread investment in machine learning (ML) technology, there remains a significant gap between human- and machine-level performance on most tasks. My long-term research goal is to close this gap and make ML systems more systematic, accurate, and affordable.
Why choose U of G?
My Canada CIFAR AI Chair enables me to consistently attract and support top students with diverse backgrounds to the Machine Learning Research Group. Through the chair, the Vector Institute provides top-up funding to trainees, an in-person and virtual network through events and Slack, as well as internships. Trainees also have access to the top GPU computing research cluster in Canada. Vector issues welcome letters to new recruits, outlining benefits of Vector Institute affiliation. My trainees are also given priority to attend events such as the CIFAR Deep Learning / Reinforcement Learning Summer School, which provide world-class training and professional development opportunities.