Yuehao Wang
Papers
5
Total Citations
303
H-Index
4
About
Yuehao Wang is a pioneering researcher at the intersection of medical robotics, computer vision, and neural rendering, with a particular focus on advancing surgical intelligence through cutting-edge computational methods. His work addresses one of medicine's most pressing challenges: enabling robots and AI systems to perceive, reconstruct, and navigate the complex, dynamic environments of the human body during surgery. Wang's most influential contribution, "Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery" (2022, 148 citations), demonstrated how neural rendering techniques could accurately model soft tissue deformation — a critical capability for safe robotic intervention. Building on this foundation, his "Neural LerPlane Representations for Fast 4D Reconstruction of Deformable Tissues" (2023, 51 citations) pushed the boundaries of real-time spatial understanding, while "EndoGSLAM" (2024, 35 citations) brought Gaussian splatting techniques into endoscopic settings for live dense reconstruction and tracking. Complementing his perception research, Wang has championed human-in-the-loop frameworks for surgical robot learning (67 citations), creating interactive simulation environments that accelerate policy training. Collectively, his work is shaping the future of autonomous and semi-autonomous surgical systems.
Research Focus
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Top Papers
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