Max Robotics — Global Service Robot Directory + US Certification

About

Xiaokang Yang is a pioneering researcher at the intersection of computer vision, medical imaging, and brain-inspired computing. His most impactful work centers on real-time 4D reconstruction and tracking in surgical environments, where he developed **Neural LerPlane Representations** for fast deformable tissue reconstruction (51 citations) and **EndoGSLAM**, a Gaussian splatting framework enabling real-time dense reconstruction and tracking during endoscopic surgeries (35 citations). These contributions are transforming minimally invasive surgery by providing surgeons with unprecedented real-time 3D visualization of dynamic anatomical structures. Yang also advances foundational AI through **L3E-HD**, a framework leveraging hyperdimensional computing for efficient learning in high-dimensional spaces (12 citations), and explores continual predictive learning from video streams (5 citations). His work on hierarchical clustering for obstacle detection using RGB-D cameras (2 citations) further demonstrates his versatility in robotics perception. With a growing citation footprint and innovations that bridge theoretical computing paradigms with life-saving clinical applications, Yang is establishing himself as a leading voice in next-generation surgical robotics and efficient AI systems.