Shueng-Han Gary Chan

Shueng-Han Gary Chan is a faculty member in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), within the College of Engineering. He is actively engaged in research and mentoring, with a strong publication record in mobile computing, indoor localization, and AI for pervasive systems.

His research focuses on indoor localization using Wi-Fi, geomagnetic, and inertial signals, sensor fusion, crowd counting with deep learning, domain adaptation, and efficient mobile AI systems. His work bridges theoretical innovation with real-world deployment, as seen in systems for missing person search and indoor navigation.

Recent publications (2023–2025) show a consistent trend toward self-supervised and domain-agnostic learning, efficient model design for mobile devices, and robust signal fusion in noisy environments. His team leverages transformer architectures, graph neural networks, and novel optimization techniques to solve real-world challenges in urban and indoor spaces.

He has advised numerous graduate students, including Jierun Chen, Zhuoxuan Peng, and Tianlang He, who have contributed as first authors to joint publications. His collaborations span institutions and include work on large-scale system deployments and mobile AI.

He leads a research group focused on mobile and pervasive computing, with projects involving IoT-based contact tracing, indoor navigation (e.g., DeepNavi, SiFu), and real-time localization systems. The team emphasizes practical deployment and system robustness.