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Dale Schuurmans, PhD



Computing Science

About Me


  • B.Sc., Mathematics, University of Alberta, 1985
  • B.Sc., Computing Science, University of Alberta, 1986
  • M.Sc., Computing Science, University of Alberta, 1988
  • Ph.D., Computer Science, University of Toronto, 1996


  • PDF, Cognitive Science, University of Pennsylvania/NEC Research, 1996-1998
  • Asst. Prof., Computer Science, University of Waterloo, 1998-2002
  • Assoc. Prof., Computer Science, University of Waterloo, 2002-2003



Artificial Intelligence
Machine Learning
Reinforcement Learning


Machine Learning, Probability Modeling, Optimization, Search.


My long term goal is to develop systems that learn predictive models from massive data sources when the requisite models are complex (e.g., as in perception, language interpretation, information extraction, bio-informatics, robot learning). Some of the key challenges are knowledge representation for learning -- how to usefully express and debug prior domain assumptions -- and navigating complex model spaces -- how to find good models while avoiding over/under-fitting. Some ongoing projects include: statistical natural language modeling, reinforcement learning, and learning search control. I've also developed some new methods for probabilistic inference, optimization, and constraint satisfaction.