Max Robotics — Global Service Robot Directory + US Certification

About

Andres Diaz-Pinto is a leading researcher at the intersection of medical image analysis, surgical robotics, and artificial intelligence. His work focuses on making AI more practical and reliable for real-world clinical applications, particularly in segmentation and surgical automation. Diaz-Pinto is widely recognized for his contributions to extending foundation models for medical imaging, most notably through his highly cited work on "Segment Any Medical Model Extended" (2024, 11 citations), which addresses the limitations of the Segment Anything Model (SAM) on medical images. He has also made significant strides in surgical outcomes research, demonstrating how 3D models can reduce complications during robotic-assisted radical prostatectomy (2024, 7 citations). His most recent work, "SuFIA-BC" (2025), tackles the challenge of generating high-quality demonstration data for visuomotor policy learning in surgical subtasks, pushing the boundaries of surgical robot learning. With a portfolio that bridges computer vision, clinical translation, and robotics, Diaz-Pinto’s research is shaping the future of AI-assisted surgery and medical imaging.