Ruisheng Wang

University of Calgary, Shenzhen University

Papers

Total Citations

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About

Dr. Ruisheng Wang is a leading researcher at the intersection of computer vision, robotics, and geospatial engineering, with a core focus on intelligent 3D scene understanding and autonomous infrastructure inspection. His work is distinguished by pioneering the application of graph matching techniques for semantic scene parsing of street-view data, a foundational contribution that has garnered 13 citations. More recently, Dr. Wang has advanced the frontier of robotic perception in extreme environments, developing legged robot-aided 3D tunnel mapping systems that leverage residual compensation and anomaly detection—a highly cited 2024 paper with 12 citations. His latest innovation, TUC-Net, introduces a neighborhood feature perception aggregation network for point cloud segmentation, specifically designed to address the challenging terrains of tunnels under construction (5 citations in 2025). By enabling unmanned data collection and robust semantic segmentation in hazardous subterranean settings, Dr. Wang’s work directly supports the critical goal of intelligent, safer tunnel construction. His research portfolio demonstrates a clear trajectory from urban scene analysis to high-impact, real-world applications in infrastructure monitoring and robotic autonomy.