Yishu Ji
Papers
1
Total Citations
6
H-Index
1
About
Yishu Ji is an emerging researcher in human-robot interaction (HRI) and cognitive neuroscience, with a focus on understanding how humans perceive and respond to errors during collaborative tasks. Their most-cited work, "Responses to Human and Robot Errors in Human‒Robot Collaboration: An fNIRS Study" (2024), employs functional near-infrared spectroscopy to investigate neural correlates of error processing in joint human-robot activities. This study, with 6 citations, provides foundational insights into how trust, cognitive load, and affective responses differ when errors originate from human versus robotic partners—a critical consideration for designing adaptive, socially aware robots. Ji’s contributions bridge experimental psychology and engineering, offering empirical evidence to improve robot transparency and error recovery strategies. While early in their career, this work has already been recognized for its methodological rigor, using neuroimaging to quantify implicit reactions that self-reports may miss. Ji’s research holds promise for advancing collaborative robotics in manufacturing, healthcare, and service domains, where seamless human-robot teamwork is essential. Their findings underscore the importance of designing robots that can both detect and appropriately respond to human errors, fostering more intuitive and resilient partnerships.
Research Focus
Key Achievements
Top Papers
- 1