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Thomas Dean
Professor of Computer ScienceContact Information
Box 1910Brown University
Providence, RI 02912
Email: tld at cs.brown.edu
Personal home page: http://www.cs.brown.edu/~tld/
Research Areas
| Artificial Intelligence |
| Computational Neuroscience |
| Machine Learning |
| Robotics |
Research Themes
| Statistical Approaches |
| Brain Science |
Research Topics or Projects
| Computational Models of the Neocortex |
| Planning Under Uncertainty |
| Stochastic Models for Web Agents and the Web Environment |
Courses Taught
| CSCI1480 | Building Intelligent Robots | |
| CSCI1410 | Introduction to Artificial Intelligence | |
| CSCI0090-C | Talking with Computers |
Research Interests
Thomas Dean’s general research interests include automated temporal and spatial reasoning, planning, robotics, learning, and probabilistic inference. He is particularly interested in problems in which the notions of uncertainty and risk are complicated by the imposition of a limited time for deliberation and action. When the problems faced by an agent in a dynamic environment are complex, one typically must trade time for precision in making decisions: How long should you spend deciding what to pack when rushing to catch a plane? A similar tradeoff arises in deciding how much time and effort to expend in learning about a new or evolving environment: When visiting a new city, how much effort should you put into learning the streets and landmarks?
A more recent project involves building a probabilistic model of the neocortex. The basic tools for his research are derived from probability, statistics, Bayesian decision theory, and the design and analysis of algorithms. The applications involve mobile robots that perform such tasks as search and rescue, as well as and disembodied “knowbots” that operate on the World Wide Web.
Selected Publications
Dean, T. Scalable Inference in Hierarchical Generative Models. In Proceedings of the Ninth International Symposium on Artificial Intelligence and Mathematics (2006). [ pdf ]
Dean, T. A Computational Model of the Cerebral Cortex. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05) (Cambridge, Massachusetts, 2005), AAAI, MIT Press, pp. 938-943. [ pdf ]
Dean, T. Hierarchical Expectation Refinement for Learning Generative Perception Models. Tech. rep., Brown University, Providence, Rhode Island, Aug 2005. [ pdf ]
Dean, T. Scalable Inference in Hierarchical Generative Models. In Proceedings of the Ninth International Symposium on Artificial Intelligence and Mathematics (2005), Annals of Artificial Intelligence and Mathematics. [ pdf ]
Dean, T. Talking With Computers. Cambridge University Press, New York, 2005.
Dean, T., Ed. Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99, Stockholm, Sweden, July 31 - August 6, 1999, 2 Volumes. Morgan Kaufmann Publishers, San Francisco, California, 1999.
All publications by Thomas Dean
| Page Owner: Thomas Dean | Last Modified: Mon Aug 20 14:30:39 2007 |