LeSean Brown
Papers
1
Total Citations
20
H-Index
1
About
LeSean Brown is a leading researcher in human-robot interaction, with a particular focus on the psychological and perceptual dynamics that shape how people respond to anthropomorphic machines. His most cited work, "A Comprehensive Approach to Validating the Uncanny Valley using the Anthropomorphic RoBOT (ABOT) Database" (2020, 20 citations), provides a rigorous empirical framework for testing the uncanny valley hypothesis—the idea that robots that look almost, but not perfectly, human elicit feelings of eeriness and discomfort. Brown’s contributions include developing standardized methods for quantifying robot anthropomorphism and systematically validating emotional responses across a wide range of robotic designs. His research has helped clarify the conditions under which the uncanny valley emerges, offering critical insights for designers aiming to create more socially acceptable robots. Beyond this landmark paper, Brown has advanced the use of large-scale databases like ABOT to enable reproducible, data-driven studies in human-robot interaction. His work is widely cited by engineers, psychologists, and roboticists, and he is recognized for bridging theoretical models with practical design guidelines. Brown’s research continues to inform how robots are built and perceived, making him a key figure in understanding the delicate balance between human likeness and user comfort.
Research Focus
Key Achievements
Top Papers
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