Qingyun Huang

City University of Hong Kong, Shanghai Jiao Tong University

Papers

Total Citations

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About

Qingyun Huang’s research bridges ancient medical wisdom with cutting-edge robotics and sensor technology. Her primary contributions lie in three intersecting domains: bio-inspired tactile sensing for medical diagnostics, multi-sensor fusion for robotic localization, and the computational analysis of traditional Chinese medicine (TCM) techniques. In her highly cited 2022 work on sphygmopalpation, Huang engineered tactile robotic fingers capable of replicating the millennia-old TCM practice of pulse diagnosis, successfully identifying fundamental arterial pulse patterns—a feat that earned 11 citations and demonstrated how robotic haptics can decode complex physiological signals. More recently, her 2025 paper introduced a low-cost, multi-sensor fusion framework achieving centimeter-level 3D indoor localization for wheeled robots navigating multi-floor environments, a breakthrough for autonomous systems in hospitals and warehouses. By integrating inertial, visual, and LiDAR data, her approach overcomes the accuracy-cost tradeoff that has long hindered practical deployment. Huang’s work is notable for its cross-cultural innovation: she does not merely apply robotics to modern problems but systematically validates ancient diagnostic frameworks through modern engineering, offering a template for preserving and enhancing traditional knowledge. Her research has profound implications for telemedicine, autonomous navigation, and human-robot interaction.