Jiajia Ge

Siemens (China)

Papers

1

Total Citations

14

H-Index

1

About

Dr. Jiajia Ge is a leading researcher at the intersection of robotic surgery, machine learning, and medical simulation, with a primary focus on advancing autonomous systems for endovascular interventions. Her most impactful work tackles the critical challenge of bridging the simulation-to-reality gap in robotic-assisted procedures. In her highly cited 2025 paper, "Sim2Real Learning With Domain Randomization for Autonomous Guidewire Navigation in Robotic-Assisted Endovascular Procedures" (14 citations), Dr. Ge introduces a domain randomization framework that enables surgical robots to learn robust navigation policies in simulated environments and transfer them effectively to real-world clinical tasks. This contribution directly addresses a major bottleneck in the clinical adoption of endovascular robots—the lack of intelligent, autonomous assistive capabilities that physicians have long requested. By demonstrating that simulated training can produce reliable real-world performance, her research paves the way for safer, more efficient robotic systems in complex vascular procedures. Dr. Ge’s work is not only technically innovative but also clinically grounded, offering a practical pathway toward reducing physician cognitive load and improving patient outcomes in minimally invasive surgery.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Sim2Real Learning With Domain Randomization for Autonomous Guidewire Navigation in Robotic-Assisted Endovascular Procedures
14 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Siemens (China)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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