ABOUT THIS KIND OF RESEARCH

Artificial intelligence at Brown University is concerned with theoretical and empirical studies involving problems ranging from natural language interpretation and machine perception to mobile robotics and disembodied agents, such as those employed in searching the World Wide Web. The research emphasizes algorithmic issues as they arise in using sophisticated models (many of them probabilistic) to represent and solve such problems. The applications include machine and human vision, auctions and other economic transactions on the World Wide Web, data mining, extraction of semantic content from text, face and gesture recognition, and planning and control for mobile robots. The basic techniques borrow from information and game theory, statistics, probability theory, operations research, Bayesian decision theory, and the design and analysis of algorithms. Faculty and students (both graduate and undergraduate) are involved in multidisciplinary research projects collaborating with such departments as Applied Mathematics, Brain Science, Cognitive Science, Engineering, and the School of Medicine.

FACULTY INVOLVED

• James Anderson
  Research: Applications of neural networks for learning and memory and mathematical models for cognition.
  
  Graduate programs: Cognitive & Linguistic Sciences; Neuroscience
   
• Michael Black
  Research: Computer Vision. Motion estimation and analysis using probabilistic and statistical methods.
  
  Graduate programs: Computer Science.
   
• Eugene Charniak
  Research: Statistical natural language processing.
  
  Graduate programs: Computer Science; Cognitive & Linguistic Sciences
   
• David Cooper
  Research: Machine recognition and learning from images and video.
  
  Graduate programs: Computer Vision, Pattern Recognition and Stochastic Processes within the Division of Engineering
   
• Thomas Dean
  Research: Adaptive planning and control in complex environments.
  
  Graduate program: Computer Science; Cognitive & Linguistic Sciences
   
• Stuart Geman
  Research: Probability and stochastic processes, and machine and natural vision.
  
  Graduate programs: Computer Science; Applied Mathematics
   
• Amy Greenwald
  Research: Multi-agent learning in game-theoretic environments.
  
  Graduate program: Computer Science
   
• Thomas Hofmann
  Research: Machine learning, pattern recognition, neural networks, computer vision.
  
  Graduate program: Computer Science
  
  
• Mark Johnson
  Research: Structured stochastic models of human language comprehension and
  production.
  
  Graduate program: Cognitive & Linguistic Sciences
     
• Benjamin Kimia
  Research: The computational and perceptual aspects of recovery and representing of shape of objects for such tasks as object recognition and construction of brain atlases.
  
  Graduate program: Engineering
  
  
• Predrag (Pedja) Neskovic
  Research: Neural networks, pattern recognition and computer vision.
   
• Harvey Silverman
  Research: Speech recognition and microphone arrays.
  
  Graduate program: Engineering