Daniel Roy

Daniel Roy is the Research Director and a Founding Faculty member at the Vector Institute, as well as a CIFAR Canada AI Chair.3 He is also a Full Professor of Statistics at the University of Toronto, with a cross-appointment in the Department of Computer Science.3 Roy was appointed as a Canada CIFAR AI Chair in 2017 and renewed in 2023.2

Roy's research focuses on the foundational principles of prediction, inference, and decision-making under uncertainty, spanning machine learning, statistics, mathematical logic, applied probability, and computer science.3 He is particularly interested in probabilistic programming, computational perspectives on fundamental ideas in probability theory and statistics, and the complexity of probabilistic and statistical inference.2

Education and Career

• Roy received his S.B., M.Eng., and Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology between 1999 and 2011.3
• He was named Vector Research Co-Director in October 2023, focusing on internal initiatives.1
• Roy is an associate professor in the Department of Statistical Sciences at the University of Toronto and the Department of Computer and Mathematical Sciences at the University of Toronto Scarborough.1

Achievements

• Founding member of the Vector Institute in 20172
• Ontario Early Researcher Award in 20172
• Google Faculty Research Award in 20172
• Organizer of the 1st, 2nd, and 3rd NIPS Workshops on Probabilistic Programming (2008, 2012, 2014)2
• Best Poster at the Conference on Bayesian Nonparametrics in 20152

Roy's work at the Vector Institute contributes to advancing strategic research priorities in areas such as AI trust and safety, foundation models, and AI for science.1