He earned a master's degree and a PhD respectively from the universities of Waterloo and Toronto and was a postdoc at Columbia, Princeton and McGill universities. He develops machine learning models, including deep learning models, to analyze large collections of data and to help in decision-making. His main contributions are in the field of recommender systems. The Toronto paper matching system (TPMS), a system to recommend and match papers to reviewers that he co-developed, was adopted by dozens of major conferences over the last five years (it has recommended papers for over six thousand reviewers). He has published 20 papers in international conferences and won a second-best paper award at the 2008 Uncertainty in Artificial Intelligence (UAI) conference.