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About

Fan Xue is a leading researcher at the intersection of computer vision, construction engineering, and digital twin technology. His primary research areas include automated construction waste management, 3D point cloud registration, and the development of low-cost digital twin buildings. Xue’s most impactful contribution is the application of semantic segmentation—a computer vision technique—to automatically recognize and classify mixed construction waste from images, a breakthrough that has garnered 134 citations and promises to revolutionize recycling and sorting processes on demolition sites. He also pioneered the RegARD method, a symmetry-based coarse registration technique that aligns smartphone-captured colorful point clouds with CAD drawings, enabling affordable, accurate digital twin models for the built environment. This work, cited 40 times, bridges the gap between low-cost sensing and high-fidelity modeling. Additionally, Xue has organized and contributed to the proceedings of the 38th International Symposium on Automation and Robotics in Construction (ISARC 2021), and his recent benchmarking of computer vision models for waste sorting (20 citations) continues to set standards for the field. His research is instrumental in making construction sites smarter, safer, and more sustainable.