Jiahao Wang

Papers

Total Citations

H-Index

About

Jiahao Wang is a researcher working at the intersection of computer vision, robotics, and human motion synthesis, with a focus on enabling machines to understand and replicate complex physical interactions. His most prominent contribution, **SAGA: Stochastic Whole-Body Grasping with Contact** (2022), has garnered 54 citations and represents a significant advance in the synthesis of realistic human grasping behaviors. Unlike prior methods that modeled only the hand in isolation, Wang's work tackles the far more challenging problem of whole-body human-object interaction, generating plausible full-body poses alongside contact-aware grasping — with direct applications in AR/VR, video games, and robotics. Beyond human motion synthesis, Wang has also made strides in active robotic perception, proposing uncertainty-guided policies that allow mobile robots to intelligently select optimal viewpoints for efficient 3D object reconstruction using Neural Radiance Fields — a notably sample-efficient approach compared to existing solutions. Across his research portfolio, Wang demonstrates a consistent drive to bridge the gap between realistic human-like interaction modeling and practical robotic deployment, making his work relevant to both the graphics and embodied AI communities.