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About

Javad Fotouhi’s research sits at the intersection of medical robotics, image-guided interventions, and extended reality, where he develops systems that enhance precision and safety in surgical procedures. His most influential work, “Dual-robot ultrasound-guided needle placement: closing the planning-imaging-action loop” (64 citations), pioneers a closed-loop framework that integrates planning, real-time imaging, and robotic action, significantly improving needle placement accuracy. He further advances the field by enabling machine learning in X-ray-based procedures through realistic simulation of image formation (61 citations), a contribution that reduces reliance on costly clinical data for training AI models. Fotouhi also explores the educational potential of virtual reality, demonstrating its effectiveness for training surgical robot setup (8 citations), and develops radiation-free methods for navigated screw placement in pediatric hip surgery (4 citations). His innovative “Reflective-AR Display” introduces a novel interaction methodology for virtual-to-real alignment in medical robotics (3 citations). With a portfolio spanning augmented reality, artificial intelligence, and robot-assisted interventions, Fotouhi’s work has garnered over 140 citations, reflecting its growing impact on safer, more accessible surgical technologies.