Rui Xiang

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About

Rui Xiang is a researcher whose work spans advanced manufacturing and computer vision, with a particular focus on bridging practical engineering challenges and cutting-edge deep learning solutions. In the domain of welding technology, Xiang has contributed a comprehensive review of double-electrode gas metal arc welding (GMAW), cataloging its approaches, developments, and variants—a foundational resource that has already garnered 15 citations since its 2024 publication. This work underscores Xiang’s ability to synthesize complex industrial processes for broader research communities. Equally impactful is Xiang’s pioneering work in autonomous systems. As the lead author of “3dDepthNet: Point Cloud Guided Depth Completion Network for Sparse Depth and Single Color Image” (2020, 8 citations), Xiang proposed an end-to-end deep learning architecture that fuses sparse LiDAR data with a single color image to produce accurate dense depth maps. By leveraging the dimensional nature of depth images, this innovation directly addresses critical perception challenges in robotics and autonomous driving, offering a novel approach to sensor fusion. Xiang’s dual expertise in manufacturing process optimization and AI-driven perception highlights a versatile research portfolio, making notable contributions to both industrial efficiency and intelligent system reliability.