Papers
6
Total Citations
145
H-Index
6
About
Jiahao Chen is a multidisciplinary researcher whose work sits at the dynamic intersection of human-robot interaction, neuroscience, and intelligent robotic systems. His research is particularly distinguished by its application of neural measurement techniques — including EEG, event-related potentials, and spectral perturbations — to objectively evaluate how humans perceive and emotionally respond to robots, moving beyond traditional self-report methods to uncover the underlying cerebral mechanisms of human preference formation. Chen's most influential contribution examines how robot gaze and vocal human-likeness shape users' subjective perceptions and brain activity during voice conversations, accumulating 55 citations and establishing him as a notable voice in social robotics research. His complementary studies on humanoid robot appearance and voice preference further reveal how design choices in robotics can be empirically grounded in neural evidence. Beyond social robotics, Chen has demonstrated impressive breadth through his work on emotional expression in non-humanoid urban robots and drone task allocation using digital twin frameworks. His more recent exploration of bio-inspired learning models integrating basal ganglia and cerebellar functions reflects an expanding interest in biomimetic robotics. With nearly 150 citations across his published work, Chen is an emerging researcher making meaningful contributions to human-centered robot design and intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Emotional expressions of non-humanoid urban robots22 citations · 2020
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