Papers
10
Total Citations
359
H-Index
6
About
Youngwoo Yoon is a robotics and human-computer interaction researcher whose work centers on enabling natural, expressive communication between humans and intelligent agents. He is best known for his pioneering contributions to co-speech gesture generation — the challenge of teaching robots and virtual avatars to produce lifelike gestures synchronized with speech. His landmark 2020 paper, "Speech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity," has accumulated over 300 citations and stands as a foundational reference in the field, introducing a deep learning framework that leverages text, audio, and speaker identity simultaneously to produce remarkably human-like motion. His earlier 2019 work demonstrated that humanoid robots could learn social gesturing end-to-end, moving beyond rigid, hand-crafted rule systems. Beyond gesture synthesis, Yoon has made meaningful contributions to person-following robots using RGB-D sensing, developing robust visual tracking methods that enabled mobile robots to navigate and follow individuals in real-world environments. More recently, his research has expanded into evaluating human-care robot services for elderly populations and validating objective motion evaluation metrics. Together, his body of work reflects a consistent commitment to making robots more socially intelligent, perceptive, and genuinely useful companions for humans.
Research Focus
Key Achievements
Top Papers
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- 3Co-Speech Gesture Synthesis using Discrete Gesture Token Learning10 citations · 2023
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- 5Depth assisted person following robots8 citations · 2013
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- 8Person following with a RGB-D camera for mobile robots3 citations · 2012
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