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About

Chenxi Xiao is a robotics and computer vision researcher whose work spans 3D perception, tactile sensing, and autonomous exploration. Best known for developing Triangle-Net, a robust point cloud classification framework designed to improve 3D object recognition for real-world applications such as autonomous vehicles and service robots, Xiao has demonstrated a consistent focus on making robotic systems more capable in unstructured and challenging environments. This work alone has accumulated nearly 40 citations, reflecting its impact on the field. Beyond 3D vision, Xiao has made notable contributions to tactile and multimodal sensing. Their research on tactile whisker-based active exploration enables robots to navigate and recognize objects without visual input—a critical capability in occluded or hazardous settings. Further work on chemical and haptic sensing for explosive ordnance disposal robots highlights a commitment to high-stakes, real-world deployments. More recent contributions extend into dexterous manipulation, including bimanual grasp synthesis and novel visuotactile fingertip sensors like HumanFT and PP-Tac, pushing boundaries in human-like robotic dexterity. With a growing citation record exceeding 110 citations across diverse topics, Xiao represents an emerging voice bridging perception, sensing, and intelligent manipulation in modern robotics research.