Professor Hyman's interest in image processing dates back to his post-doctoral year at the National Institutes of Health. Based on Pavlovian conditioning experiments with animals, the NIH and its contractors were creating crude models of the mechanisms of learning. My physics background, especially statistical mechanics, was adaptable to the project. There are parallels between systems of neurons leading to high-level cognitive functions and systems of particles leading to macroscopic phenomenon like weather. Professor Hyman uses computer technology judiciously throughout the curriculum, exposing his students to a wide variety of research tools.
Theorists can still get away with using pencils and paper.
But then they turn around and ask us to prove their theoretical models. Instead of learning science secondhand, they discover it for themselves. Website created by Rachel Souder-Arguedas '01 and maintained by the Office of Public Relations.