Campus
- Downtown Toronto (St. George)
- Scarborough (UTSC)
Cross-Appointments
Fields of Study
- Data Science
- Theoretical Statistics
Areas of Interest
- Machine learning
- Statistical learning theory
- Foundations of statistics; nonstandard analysis
- Online learning; bandits; and other models of adversarial learning
- Statistical analysis of data with complex structures (graphs, arrays, etc.); probabilistic symmetries
- Probabilistic programming
- Bayesian nonparametric statistics
Biography
Daniel Roy is Canada CIFAR AI Chair at the Vector Institute and associate professor in the Departments of Statistical Sciences, Computer Science, Electrical and Computer Engineering, and Computer and Mathematical Sciences. Roy's research spans machine learning, mathematical statistics, and theoretical computer science. Roy is a recent recipient of a NSERC Discovery Accelerator Supplement, an Ontario Early Research Award, and a Google Faculty Research Award. Prior to joining Toronto, Roy was a Research Fellow of Emmanuel College and Newton International Fellow of the Royal Society and Royal Academy of Engineering, hosted by the University of Cambridge. Roy completed his doctorate in Computer Science at the Massachusetts Institute of Technology, where his dissertation was awarded the MIT EECS Sprowls Award, given to the top theses in computer science in that year.
Education
Awards
- NSERC Discovery Accelerator Supplement (DAS) Natural Sciences and Engineering Research Council
- Early Researcher Award Ontario Ministry of Research, Innovation and Science (MRIS)
- Faculty Research Award Google
- Newton International Fellowship the British Academy, Academy of Medical Sciences, and the Royal Society