Robert A. Jacobs
University of Massachusetts, 1990
Short Bio: For my undergraduate studies, I attended the University of Pennsylvania where I majored in Psychology. I spent the next two years working as a Research Assistant in a biomedical research laboratory at Rockefeller University. For graduate school, I attended the University of Massachusetts at Amherst where I earned a Ph.D. degree in Computer and Information Science (graduate advisor: Andrew Barto). I then served in two postdoc positions, one in the Department of Brain & Cognitive Sciences at the Massachusetts Institute of Technology (postdoc advisor: Michael Jordan), and the other in the Department of Psychology at Harvard University (postdoc advisor: Stephen Kosslyn). I'm currently a faculty member at the University of Rochester where my title is Professor of Brain & Cognitive Sciences, of Computer Science, and of the Center for Visual Science. I am also a member of the Center for Computation and the Brain.
The Computational Cognition and Perception Lab uses experimental and computational methodologies to study human learning, memory, and decision making in cognitive and perceptual domains. How is new information—such as a visual feature distinguishing the appearances of identical twins or a combination of features allowing a person to identify or categorize novel objects—acquired and how does this information become established in memory? How are perceptual learning and memory similar or different from cognitive learning and memory? How is low-level perceptual information abstracted to form the basis of high-level conceptual knowledge? To what extent are people's behaviors consistent with the optimal behaviors of computational models based on Bayesian statistics? Our research lab addresses these and other questions.
Current Postdoctoral Fellows & Graduate Students
We are currently seeking new graduate students and postdoctoral fellows to join our lab. If you're interested, please contact .
Goker uses experimental and computational studies to characterize the nature of abstract, conceptual representations of objects. For example, are these representations "part-based", meaning that objects are characterized in terms of their parts and the spatial relations among these parts?
Matt is interested in how high-level conceptual representations can be acquired from low-level perceptual experiences. Computational models are used to implement a theory of concept acquisition.