Max Robotics — Global Service Robot Directory + US Certification

About

Tommaso Da Col is a leading researcher at the intersection of robotic surgery, autonomous navigation, and surgical skill assessment. His primary contributions lie in developing intelligent systems that reduce surgeon workload by automating endoscope control during robot-assisted minimally invasive procedures. Da Col’s most influential work, the SCAN system (35 citations), introduces autonomous camera navigation to enhance surgical efficiency, while his subsequent studies (26 and 21 citations) experimentally validate these methods for training and complex tasks like ex vivo neobladder reconstruction. He has also pioneered multi-modal feedback platforms, such as GEYEDANCE (6 citations), which integrates Optical Coherence Tomography (OCT) for safer robot-assisted ophthalmic surgery. Addressing safety in machine learning, Da Col’s work on unsupervised out-of-distribution detection (5 citations) ensures robust performance in retinal microsurgery. His research demonstrates a clear trajectory from foundational automation to advanced, safety-critical applications, with cumulative citations exceeding 100. Da Col’s achievements include advancing surgical skill evaluation through objective, data-driven metrics, reducing reliance on subjective expert observation. His work is pivotal for trainees and experienced surgeons alike, promising shorter operation times, improved precision, and safer robotic interventions.