SIMON STORK

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About

Simon Stork is a rising researcher in the rapidly evolving field of robot-assisted interventional radiology, with a primary focus on improving the precision and accessibility of minimally invasive procedures. His work centers on the intersection of surgical robotics, medical image guidance, and human-machine interaction, particularly for soft tissue needle placement. In his most-cited study, "Learning Needle Placement in Soft Tissue With Robot-assisted Navigation" (2023), Stork conducted a pioneering phantom study evaluating the learning curves of novices using a novel cone-beam CT-guided robotic assistance system. This work demonstrated that even inexperienced operators could achieve high accuracy with minimal training, highlighting the potential of such systems to democratize complex interventions. While his citation count is still growing—a hallmark of an early-career investigator—his contributions are already shaping the conversation around skill transfer and workflow integration in robotic surgery. Stork’s research is particularly notable for its practical, translational approach, bridging the gap between engineering prototypes and clinical reality. As robotic navigation becomes standard in interventional suites, Stork’s findings on learning efficiency and system usability will be foundational for training the next generation of clinicians.