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About

Mohammad Jolaei is a leading researcher at the intersection of soft robotics and medical intervention, whose work is fundamentally reshaping autonomous cardiac ablation. His primary research focuses on developing intelligent control systems for tendon-driven catheters, aiming to reduce surgeon fatigue and improve procedural precision. Jolaei’s most impactful contribution is his pioneering framework for achieving Level-2 task autonomy in robotic cardiac ablation, detailed in his highly cited 2020 paper (65 citations). This work introduced a novel kinematic model for flexible catheters, enabling autonomous navigation and control. He further advanced the field by developing sensor-free force control methods (24 citations), allowing clinicians to estimate and control tip-tissue contact forces without additional hardware. His innovative use of learning-from-simulation for real-time tip force estimation (11 citations) has been validated with ex-vivo tissue, bridging the gap between simulation and clinical reality. Beyond medical robotics, Jolaei has also contributed to tactile-based grasp stability prediction for robotic manipulators. His research is characterized by a unique blend of rigorous modeling, data-driven learning, and practical validation, making him a rising authority in autonomous surgical systems.