Papers

8

Total Citations

171

H-Index

6

About

Xin Lei is an emerging researcher whose work sits at the intersection of human-robot interaction (HRI), social cognition, and educational technology. Lei's scholarship centers on how humans perceive, evaluate, and emotionally respond to robots in collaborative and social settings, with particular expertise in responsibility attribution, robot personality, and the psychological dynamics of human-robot teams. Among Lei's most influential contributions is a body of work examining how people assign blame and credit in human-robot groups, exploring how factors such as relative status, power distance orientation, and task structure shape responsibility judgments — work that has collectively garnered nearly 100 citations. Lei has also made notable strides in educational HRI, investigating how robot tutors' feedback styles influence learner outcomes and how emotional responses during robot-mediated cooperation and competition manifest neurologically. A distinctive methodological strength in Lei's research is the use of functional near-infrared spectroscopy (fNIRS) to uncover neural correlates of robot personality perception and error responses, bridging behavioral and neuroscientific approaches. More recently, Lei has expanded into service robotics, examining how robot personality traits like extroversion facilitate user self-disclosure and intimacy. This growing portfolio marks Lei as a rigorous and innovative voice in the rapidly evolving field of human-robot social dynamics.

Research Focus

Key Achievements

6
H-Index
8
Papers
171
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Effect of relative status on responsibility attributions in human–robot collaboration: Mediating role of sense of responsibility and moderating role of power distance orientation
49 citations · 2021
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Tsinghua University, Zhejiang University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago