Dr. Daniel Roy

Biography

Daniel M. Roy is a Professor in the Department of Statistical Sciences at the University of Toronto, where he holds a cross-appointment in the Department of Computer Science. He is the Research Director of CIFAR Canada AI Chair and a Founding Faculty member of the Vector Institute. Roy's research lies at the intersection of statistical learning, machine learning, and computer science, focusing on the foundational principles underlying prediction, inference, and decision-making under uncertainty. His work has made substantial contributions to learning theory, statistical network analysis, decision theory, and probabilistic programming. He also has interests in Bayesian nonparametric statistics and non-standard analytical foundations related to decision theory. Daniel received his Ph.D. from the Massachusetts Institute of Technology and has held fellowships including a Newton International Fellowship and a Royal Society Research Fellowship. His collaborative work spans various applications in artificial intelligence, data science, and advanced mathematical theories. He is actively involved in mentoring graduate students and postdoctoral researchers, and he seeks individuals with strong quantitative backgrounds to join his research group.

Research Interests

Experience