Andrew Feng
Papers
1
Total Citations
10
H-Index
1
About
Andrew Feng is a leading researcher in computer graphics and embodied AI, whose work focuses on synthesizing realistic, communicative human motions for virtual agents and humanoid robots. His primary research areas include co-speech gesture generation, character animation, and human-robot interaction. Feng’s most notable contribution is his pioneering work on "Co-Speech Gesture Synthesis using Discrete Gesture Token Learning" (2023), which has already garnered 10 citations for its novel approach to creating believable, synchronized gestures that accompany speech. This work is critical for enabling robots and avatars to interact naturally with humans, enhancing user trust and engagement in applications ranging from education to telepresence. By treating gesture generation as a discrete token learning problem, Feng has opened new pathways for data-driven animation, making virtual characters more expressive and lifelike. His research bridges the gap between computational animation and real-world robotics, promising to transform how we design communicative machines.
Research Focus
Key Achievements
Top Papers
- 1Co-Speech Gesture Synthesis using Discrete Gesture Token Learning10 citations · 2023