Dong Won Lee

Papers

Total Citations

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About

Dong Won Lee is a researcher at the intersection of human-robot interaction (HRI) and embodied AI, with a focus on making social robots more expressive, scalable, and accessible. His work bridges gesture generation and community-driven robotics platforms. In his most cited paper, "Style Transfer for Co-speech Gesture Animation: A Multi-speaker Conditional-Mixture Approach" (2020, 4 citations), Lee pioneered a method to generate personalized, speaker-specific gestures for virtual agents, enabling more natural and diverse non-verbal communication—a key contribution to embodied conversational AI. He is also a leading voice in democratizing HRI research through his work on the "Jibo Community Social Robot Research Platform @Scale" (2024, 2 citations), which tackles the critical lack of shared, replicable platforms in the field. By introducing a standardized, scalable social robot ecosystem, Lee addresses a long-standing barrier to cross-community collaboration and reproducible studies. His work is particularly notable for its practical impact: the Jibo platform aims to lower the entry barrier for HRI researchers worldwide, while his gesture style transfer work has implications for animation, gaming, and assistive technologies. Lee’s research is shaping a future where social robots are both more human-like and more widely available for scientific inquiry.