Yisi Liu

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About

Yisi Liu is a pioneering researcher at the intersection of neuroscience, human-robot interaction, and affective computing. Their work focuses on understanding how humans perceive and emotionally respond to robotic designs, particularly humanoid robots, using advanced neurophysiological tools. Liu’s most cited study, "Detection of Humanoid Robot Design Preferences Using EEG and Eye Tracker" (2019, 19 citations), represents a significant contribution to human-robot interaction by employing Electroencephalogram (EEG) and eye-tracking technology to objectively measure users’ cognitive and emotional reactions to robot aesthetics. This research directly addresses the critical challenge of low user appeal in modern humanoid robots, providing data-driven design recommendations that bridge engineering and psychology. By demonstrating how neural and ocular signals can reveal implicit preferences, Liu has established a methodological framework for creating more engaging, socially acceptable robotic companions. Their work has implications for robotics design, user experience research, and assistive technology development, positioning Liu as a key figure in the emerging field of neuroergonomic design for human-robot collaboration.