Papers
17
Total Citations
122
H-Index
7
About
Won Hyong Lee is a robotics researcher whose work sits at the intersection of human-robot interaction (HRI), affective computing, and social robotics. Over more than a decade of scholarship, Lee has made sustained contributions to one of the field's most challenging problems: enabling robots to generate, represent, and express emotions in ways that feel natural and believable to human users. Among his most influential contributions is his application of Laban Movement Analysis (LMA) to emotional motion representation, using RGB-D cameras such as the Microsoft Kinect to capture and interpret whole-body joint trajectories — work that has accumulated nearly 30 citations across related publications. His earlier research introduced novel emotion generation models grounded in concepts of energy, entropy, and homeostasis, as well as stochastic interpretations of the OCC cognitive model to account for uncertainty in emotional responses. Lee also developed practical tools for synchronized multimodal expression and automated gesture generation tied to speech patterns, bridging theoretical frameworks with deployable robotic systems. More recently, his 2020 review of robotic applications in pediatric care — his most cited work with 29 citations — signals a broadening focus toward real-world, human-centered deployment. Taken together, Lee's research offers a rigorous and creative foundation for robots capable of emotionally resonant social interaction.
Research Focus
Key Achievements
Top Papers
- 1Robotic Uses in Pediatric Care: A Comprehensive Review29 citations · 2020
- 2LMA based emotional motion representation using RGB-D camera18 citations · 2013
- 3LMA based emotional motion representation using RGB-D camera10 citations · 2013
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- 5How to completely use the PAD space for socially interactive robots8 citations · 2011
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