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About

Chengdong Yang’s research bridges the gap between advanced manufacturing and next-generation neuromorphic hardware, with a primary focus on intelligent welding systems and artificial sensory devices. His early work revolutionized thick-plate welding automation, developing multi-pass path planning algorithms that adapt to groove size variations and assembly gaps using vision sensors, eliminating the need for back chipping—a breakthrough that significantly improved welding quality and efficiency. His 2014 paper on this topic has accumulated 25 citations, while related studies on weld pool surface reconstruction and multi-agent robot control further cemented his contributions to manufacturing robotics. More recently, Yang has ventured into neuromorphic computing, engineering a tunnel silicon nitride-based reconfigurable bi-mode nociceptor analog that mimics biological pain perception for robotic sensory systems. This 2024 work, already garnering 6 citations, demonstrates his ability to pivot from industrial automation to cutting-edge bio-inspired electronics. With a career spanning foundational welding research and emerging neuromorphic technologies, Yang’s work exemplifies how traditional manufacturing expertise can inform the development of intelligent, adaptive systems for next-generation robotics.