Daniel Roy focuses on theoretical questions, especially ones that combine computer science, statistics, and probability. He received his PhD in computer science from the Massachusetts Institute of Technology in 2011, 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.