Papers

28

Total Citations

1,239

H-Index

19

About

Gaoyang Pang is a prominent researcher whose work sits at the dynamic intersection of human-robot interaction, wearable sensing technologies, and intelligent robotics. His research spans three core domains: smart wearable systems for healthcare and rehabilitation, flexible tactile sensing for collaborative robots, and machine learning-driven human-machine interfaces. Among his most significant contributions is his pioneering development of IoT-enabled rehabilitation systems, including a smart wearable armband paired with machine learning and 3D-printed robotic hands to aid stroke recovery (187 citations). His groundbreaking work on robot skin — particularly CoboSkin, a variable-stiffness collaborative robot skin — has advanced the safety of human-robot collaboration by giving robots a tangible sense of touch (99 citations). His comprehensive review of robot skin technologies (94 citations) has become a key reference for researchers navigating this rapidly evolving field. Pang has also made notable strides in machine learning-enabled tactile sensor design (147 citations), super-resolution tactile arrays powered by deep learning (52 citations), and facial expression recognition using conditional GANs for intuitive human-robot interaction (111 citations). With a career stretching from early hexapod locomotion research (2002) to cutting-edge flexible sensor systems, Pang's cumulative impact reflects his sustained influence in shaping the future of intelligent, human-centered robotics.

Research Focus

Key Achievements

19
H-Index
28
Papers
1,239
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
An IoT-Enabled Stroke Rehabilitation System Based on Smart Wearable Armband and Machine Learning
187 citations · 2018
📈 Most Prolific Year: 2025 (5 Papers)
🤝 Key Collaborators: 68
🏛 Institutions: Power Systems Engineering Research Center, The University of Sydney, Zhejiang University, University of Hong Kong

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago