Max Robotics — Global Service Robot Directory + US Certification

About

Mohammad Farid Azampour is a leading researcher at the intersection of robotics, medical imaging, and artificial intelligence, with a primary focus on advancing ultrasound (US)-guided robotic systems. His work centers on developing intelligent, autonomous navigation methods for minimally invasive procedures, particularly in neurosurgery and abdominal interventions. Azampour pioneered the first reinforcement learning (RL)-based robotic navigation using ultrasound images, achieving 50 citations for his foundational work that combines deep Q-networks with real-time US feedback. He has also made significant contributions to surgical simulation, creating a Position-Based Dynamics (PBD) simulator for brain deformations during keyhole neurosurgery, cited 19 times. His innovative use of implicit neural representations includes Ultra-NeRF, a physics-enhanced model for novel view US synthesis (16 citations), and breathing-compensated volume reconstruction for robotic US (11 citations). Notably, his CACTUSS framework (9 citations) addresses abdominal aortic aneurysm diagnosis by mapping common anatomical spaces between CT and US. Azampour’s work on shape completion and real-time visualization for robotic spine acquisitions further demonstrates his commitment to overcoming US imaging limitations, such as shadowing artifacts. With a growing citation impact, his research is shaping the future of autonomous, image-guided robotic surgery.