Hedyeh Rafii-Tari
Papers
12
Total Citations
726
H-Index
10
About
Hedyeh Rafii-Tari is a pioneering researcher at the intersection of medical robotics, endovascular intervention, and machine learning-assisted surgical systems. Her work has fundamentally advanced the field of robot-assisted catheterization, with her landmark 2013 review on emerging endovascular catheterization technologies accumulating over 280 citations and becoming an essential reference for clinicians and engineers alike. Rafii-Tari's research uniquely bridges the gap between experienced interventionalist expertise and robotic capability, developing intelligent systems that learn and replicate expert navigation strategies within complex vascular anatomies. Her contributions to force-sensing technologies and haptic feedback systems have improved both patient safety and procedural precision, while her learning-based frameworks — drawing on techniques such as Hidden Markov Models and non-rigid registration — have enabled robots to collaboratively assist clinicians during demanding endovascular procedures. Beyond catheterization, she has extended her expertise to laparoscopic surgery training through force-sensing simulation environments and cooperative control frameworks informed by Learning from Demonstration. With a cumulative citation record exceeding 700 across her most influential works, Rafii-Tari represents a significant voice in next-generation surgical robotics, consistently driving toward safer, smarter, and more collaborative minimally invasive interventions.
Research Focus
Key Achievements
Top Papers
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- 2A force feedback system for endovascular catheterisation102 citations · 2012
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