Kwanmin Lee
Papers
2
Total Citations
54
H-Index
2
About
Kwanmin Lee is a researcher at the intersection of human-robot interaction and user acceptance, exploring how subtle social cues shape our relationship with technology. His most cited work investigates the dual influence of familiarity and robot gesture on user acceptance of information, demonstrating that repeated exposure and non-verbal communication—such as a robot’s gestures—significantly enhance how people perceive and trust robotic agents. Through a carefully designed three-week experiment, Lee’s studies (each garnering 22 and 32 citations respectively) provide empirical evidence that social dynamics like familiarity can bridge the gap between human and machine, making robots more approachable and effective communicators. His contributions are particularly notable for bridging cognitive psychology and robotics, offering practical insights for designing socially intelligent machines in education, healthcare, and service settings. Lee’s work underscores a key insight: that the success of human-robot interaction depends not only on functionality but on the nuanced, familiar gestures that make technology feel more human.
Research Focus
Key Achievements
Top Papers
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