Joseph Jay Williams

Assistant Professor

Fields of Study

Areas of Interest

  • Technology-based field experiments
  • Learning, memory & education
  • Physical health behaviour change
  • Stress, wellness & mental health
  • Mobile health interventions
  • Explanation, reflection & self-explanation
  • Concepts & categories
  • High-level cognition
  • Psychologically informed "WISE" interventions for motivation
  • Human-computer interaction
  • Optimal experimental design
  • Statistical methodology
  • Bayesian statistics
  • Computational cognitive science
  • Machine learning
  • Reinforcement learning


Joseph Jay Williams is an Assistant Professor in Computer Science at the University of Toronto (with a Graduate Appointment in Psychology), leading the Intelligent Adaptive Interventions research group. He was previously an Assistant Professor at the National University of Singapore's School of Computing in the department of Information Systems & Analytics, a Research Fellow at Harvard's Office of the Vice Provost for Advances in Learning, and a member of the Intelligent Interactive Systems Group in Computer Science. He completed a postdoc at Stanford University in Summer 2014, working with the Office of the Vice Provost for Online Learning and the Open Learning Initiative. He received his PhD from UC Berkeley in Computational Cognitive Science, where he applied Bayesian statistics and machine learning to model how people learn and reason. He received his B.Sc. from University of Toronto in Cognitive Science, Artificial Intelligence and Mathematics, and is originally from Trinidad and Tobago.