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Dale Schuurmans, PhD

Professor

Science

Computing Science

About Me

Education

  • 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

Positions

  • 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

Research

Areas

Artificial Intelligence
Machine Learning
Reinforcement Learning

Interests

Machine Learning, Probability Modeling, Optimization, Search.

Summary

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.