Rachel Heaton

Nearly half of the human brain is devoted to vision, and yet there is still much we don’t understand about how that half works: How does the human visual system deliver representations that allow us to understand and reason about the visual world? How does it make contact with our daily experiences, such as the quality of the user experience of a coffee maker, what we deem fashionable, the metaphors we see in artwork, and even how we know whether we can sit on something we recognize as a chair? This question also manifests in emergent and risky technologies that we hope will emulate our own behaviors, such as self-driving cars, unmanned drones (UAV’s), and missile and landing guidance systems.

I develop computational models of the human visual system that simulate the way we generate mental representations of the objects we see in our environment, and how we compare our prior knowledge to those representations in order to make inferences about those objects. Starting from 2-dimensional images, the models I work with simulate the activity of large numbers of individual neurons in the brain that fire together to represent contours, surfaces, objects, scenes, and ultimately bind both objects and scenes into abstract representations that can be used for reasoning. The goal of my work is to provide information about psychological theories to vision scientists, new computational methods to artificial intelligence researchers, and give all of us more insight into our own nature and experiences.