ABOUT THIS KIND OF RESEARCH

Research on Theory and Computation at Brown covers many departments, many faculty members and many approaches. A central theme is the study of learning on various levels. The major focus in the Institute for Neural Systems has been the "B-C-M" model for synaptic plasticity, which is the subject of ongoing theoretical studies and experiments on both the molecular and system level. Learning models based on neural nets are studied by several groups and language learning specifically is studied in the Cognitive and Linguistic Sciences (CLS) Department. Models of the compositional structure of thinking are pursued in Applied Mathematics, as well as the CLS and Neuroscience Departments. Much of the research is concentrated on the three major areas of vision, motor skills and language. In all of these areas, computational theories are compared with both biological and psychophysical/psycholinguistic experiments. There is a strong focus on theoretical studies based on stochastic modeling of visual and language abilities in Applied Mathematics, CLS and Computer Science. Another focus is the study of shape: this is an essential component both of object recognition algorithms in computer vision and of object models in computer graphics and is studied in Engineering and Computer Science.

FACULTY INVOLVED

• James Anderson
  Research: Applications of neural networks for learning and memory and mathematical models for cognition.
  
  Graduate programs: Cognitive & Linguistic Sciences; Neuroscience
   
• Elie Bienenstock
  Research: Compositional mechanisms in natural and artificial vision.
  
  Graduate program: Applied Math; 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
   
• Russell Church
  Research: Quantitative models of time perception and timed performance.
  
  Graduate program: Psychology
   
• 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
   
• Leon Cooper
  Research: Learning and memory, computational neuroscience.
  
  Graduate programs: Neuroscience; Physics
   
• Jerry Daniels
  Research: Problems of optimization and neural networks. Time series prediction. Genetic algorithms for jigsaw puzzle solving.
  
  Graduate program: Engineering
   
• Katherine Demuth
  Research: Normal and impaired language learning / development.
  
  Graduate programs: Cognitive & Linguistic Sciences
   
• Fulvio Domini
  Research: 3D shape perception, motion, depth perception, computational vision.
  
  Graduate program: Cognitive & Linguistic Sciences
   
• John Donoghue
  Research: Motor skill learning.
  
  Graduate program: Neuroscience
   
• 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
   
• John Hughes
  Research: Computer graphics, especially graphics influenced by computer vision. Mathematical foundations for modeling. Vision-based modeling.
  
  Graduate program: Computer Science
   
• Mark Johnson
  Research: Structured stochastic models of human language comprehension and production.
  
  Graduate programs: 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
  
   
• David Laidlaw
  Research: Biological imaging, visualization, modeling and computation.
  
  Graduate program: Computer Science
  
  
• Mayank Mehta
  Research: Mechanisms of learning in neuronal networks. We use simultaneous recording of a large number of neurons, and computational modeling.
  
  
• Predrag (Pedja) Neskovic
  Research: Neural networks, pattern recognition and computer vision.
   
• David Mumford
  Research: The construction of stochastic models for the study of vision and especially the modeling of image statistic and of shape.
  
  Graduate programs: Applied Mathematics; Physics
   
• Michael Paradiso
  Research: The neural basis of visual perception.
  
  Graduate program: none
   
• Julie Sedivy
  Research: Human Language comprehension, psycholinguistics, semantic and pragmatic theory.
  
  Graduate program: Cognitive & Linguistic Sciences
   
• David Sheinberg
  Research: Neural mechanisms of natural vision.
  
  Graduate program: Neuroscience
   
• Harel Shouval
  Research: Theoretical and experimental aspects of synaptic plasticity.
  
  Graduate program: none
   
• James Simmons
  Research:
  
  Graduate program: Cognitive & Linguistic Sciences
   
• Michael Tarr
  Research: Behavioral, computational and neuroscientific study of object recognition.
  
  Graduate programs: Cognitive & Linguistic Sciences; Neuroscience; Psychology
   
• William Warren
  Research: Human perception and action; visual control of locomotion and navigation.
  
  Graduate program: Cognitive & Linguistic Sciences