About

Tianyu Xiang is a leading researcher at the intersection of medical robotics, tactile sensing, and reinforcement learning, with a focus on advancing autonomous systems for vascular intervention. His major contributions lie in developing intelligent frameworks for surgical skill assessment and autonomous guidewire delivery in percutaneous coronary intervention (PCI). Xiang pioneered the use of dynamic warping manipulations for objective PCI skill evaluation, enabling quantitative differentiation between expert and novice performance. He also introduced a novel Halbach-cylinder-based magnetic skin for robotic tactile sensing, addressing the long-standing challenge of weakly interpretable information mapping in tactile sensors. His work on discrete soft actor-critic with auto-encoders and model-based offline reinforcement learning has achieved over 10 citations each, demonstrating significant impact in autonomous instrument delivery. Notably, Xiang’s research combines offline and online reinforcement learning to effectively learn complex, soft-body manipulation skills, reducing the need for extensive human training. With over 60 total citations across his top papers, Tianyu Xiang is shaping the future of intelligent, autonomous vascular robotic systems.

Research Focus

Key Achievements

4
H-Index
5
Papers
61
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Surgical Skill Assessment Based on Dynamic Warping Manipulations
21 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Beijing Academy of Artificial Intelligence, Chinese Academy of Sciences, University of Chinese Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago