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Rachel Heaton uses computational experimental methods to study the impact of cognitive psychology on design. Her research goal is to understand how people mentally represent and reason about objects as they see the world. Her interests include examining the ways perception and cognition influence human responses to designed artifacts, as well as the psychological processes that underlie design creativity. Her work encompasses computational models of object recognition, perceptual grouping, visual attention, eye movements, reasoning by visual analogy, and perception of visual affordances. She also studies the generative capabilities of artificial intelligence and general issues related to neural computation. Prior to her academic career, she worked in the semiconductor industry where she designed digital logic for CPUs and network processor architectures.
GRE is optional for admission to all graduate programs in Statistics. Full status admission requires higher language scores than limited status.