Daniel Roy focuses on theoretical questions, especially ones that combine computer science, statistics, and probability. He received a PhD in computer science in 2011 from the Massachusetts Institute of Technology, winning a George M. Sprowls Award for an outstanding PhD thesis from MIT’s electrical engineering and computer science department. Subsequently, Roy held a Newton International Fellowship (Royal Society) and a Research Fellowship at Emmanuel College (University of Cambridge). In 2014, he joined the University of Toronto as assistant professor of statistics. He has co-authored more than thirty articles, and has helped introduce probabilistic programming as a sub-discipline of the machine-learning field.