About

Mingcong Chen is a leading researcher at the intersection of robotics, medical imaging, and surgical automation. Their work focuses on developing intelligent robotic systems for minimally invasive surgery, autonomous ultrasound imaging, and tactile sensing. Chen’s major contributions include pioneering fully autonomous 3D ultrasound acquisition for artery imaging, eliminating the need for contrast agents and radiation, and creating DaFoEs, a deep-learning framework for force estimation in robotic surgery by fusing cross-modality datasets. They also designed MicroNeuro, a dual-segment flexible robotic endoscope for intraventricular biopsy, and developed an ultra-fast intrinsic contact sensing method for arbitrary-shaped medical instruments. With over 55 citations across their top papers, Chen’s research has significantly advanced patient safety and surgical precision. Notable achievements include the OMsense omni-tactile sensor inspired by compound eyes and the USPilot system, which integrates large language models for robotic ultrasound assistance. Chen’s work is widely recognized for its innovation in combining robotics, AI, and clinical applications, offering transformative solutions for modern healthcare.

Research Focus

Key Achievements

5
H-Index
12
Papers
59
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Fully Robotized 3D Ultrasound Image Acquisition for Artery
17 citations · 2023
📈 Most Prolific Year: 2024 (6 Papers)
🤝 Key Collaborators: 41
🏛 Institutions: Chinese Academy of Sciences, King's College London, City University of Hong Kong, Chinese University of Hong Kong, Shenzhen, Hong Kong Baptist University, Institute of Automation

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago