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Xiangdong Gao is a leading figure in intelligent welding manufacturing, whose research bridges machine vision, infrared sensing, and neural network control to revolutionize automated welding processes. His work primarily focuses on real-time seam tracking and quality monitoring, addressing critical challenges in both traditional arc welding and advanced laser welding. Gao’s most influential contribution is his comprehensive 2021 review on machine vision-based welding monitoring (94 citations), which synthesizes decades of progress and sets a roadmap for future smart manufacturing systems. His pioneering 2011 study on infrared image recognition for fiber laser welding (67 citations) demonstrated how thermal imaging can enable precise seam tracking under harsh conditions, a technique now widely adopted in high-precision industries. Earlier, his foundational 2000 work on neural network control for arc-welding robots laid the groundwork for adaptive automation in robotic welding. More recently, his 2021 investigation into current stability’s effect on additive deposition (2 citations) extends his expertise into 3D printing of metal components. With over 160 cumulative citations, Gao’s research has profoundly influenced both academic understanding and industrial practice, making him a key authority in the evolution of intelligent, sensor-driven welding technologies.