Lap‐Pui Chau

Nanyang Technological University, Hong Kong Polytechnic University

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About

Lap‐Pui Chau is a leading researcher at the forefront of embodied AI and 3D computer vision, with a particular focus on advancing robotic perception and manipulation. His work bridges the critical gap between deep learning and real-world deployment, tackling challenges in depth estimation and object-centric robotic control. Chau’s major contributions include pioneering robust stereo matching algorithms for autonomous systems, such as the "Soft Warping Based Unsupervised Domain Adaptation for Stereo Matching" (10 citations), which enhances depth perception across varying environments. He also introduced the "RSAN: A Retinex based Self Adaptive Stereo Matching Network" to handle low-light conditions like night and rain, addressing a key bottleneck in field robotics. More recently, his comprehensive "Survey of Embodied Learning for Object-centric Robotic Manipulation" (8 citations) has become a foundational resource for researchers exploring how robots can learn to interact with objects in unstructured settings. With a career dedicated to making machines see and act intelligently, Chau’s work is shaping the next generation of autonomous systems, from self-driving cars to service robots.