Shih-Yang Su

Shih-Yang Su is a recent PhD graduate in Computer Science from the University of British Columbia, specializing in Human Motion Learning, 3D Vision, and Character Animation. His research bridges computer vision and graphics, with significant contributions to neural rendering and articulated human modeling.

His primary research interests include:

• Human Motion Learning and Character Animation using neural representations
• Neural Radiance Fields (NeRF) for articulated objects and human bodies
• 3D Vision techniques for novel view synthesis and depth inpainting
• Reinforcement Learning applications in embodied environments

His publication record shows a clear progression from reinforcement learning (2017-2018) toward neural rendering and human modeling (2020-2024), with increasing focus on articulated neural representations. Key publications include work on Neural Point Characters (ICCV 2023) and DANBO (ECCV 2022), which address fundamental challenges in representing articulated human bodies.

Collaborations span multiple institutions including Meta Reality Labs (with Dr. Michael Zollhöfer and Dr. Timur Bagautdinov), University of Maryland (with Prof. Jia-Bin Huang), Borealis AI (with Dr. Hossein Hajimirsadeghi), and Academia Sinica (with Dr. Yi-Hsuang Yang and Dr. Li Su).