Nicolas Padoy

About

Nicolas Padoy is a pioneering researcher at the intersection of computer vision, artificial intelligence, and surgery, whose work has fundamentally shaped how intelligent systems can understand and augment the operating room. His research spans surgical workflow recognition, skill assessment, tool segmentation, and human-machine collaboration, addressing some of the most pressing challenges in next-generation surgical care. Padoy's contributions have demonstrated remarkable breadth and depth. His work on surgical phase and step recognition — including multi-task temporal convolutional networks — has laid critical groundwork for context-aware robotic assistance. His explorations of self-supervised and fully unsupervised approaches to surgical instrument segmentation have pushed the boundaries of what is achievable with limited labeled data, a perennial challenge in medical imaging. His 2022 review on computer vision in surgery (189 citations) has become an essential reference for the field, while his HeiChole benchmark study (96 citations) established standardized evaluation frameworks for surgical AI systems globally. Beyond algorithms, Padoy envisions surgery as an ecosystem of intelligent collaboration, evidenced by his early human-machine collaborative surgery framework and the OR Black Box initiative. With over 700 cumulative citations across his most influential works, his impact on making surgery safer, more objective, and more data-driven is both substantial and growing.

Research Focus

Key Achievements

Top Papers

1. 1
   Computer vision in surgery: from potential to clinical value

   189 citations · 2022
2. 2
   Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

   96 citations · 2023
3. 3
   Human-Machine Collaborative surgery using learned models

   95 citations · 2011
4. 4
   Multi-Task Temporal Convolutional Networks for Joint Recognition of Surgical Phases and Steps in Gastric Bypass Procedures

   85 citations · 2021
5. 5
   Technical skill assessment in minimally invasive surgery using artificial intelligence: a systematic review

   62 citations · 2023
6. 6
   OR black box and surgical control tower: Recording and streaming data and analytics to improve surgical care

   52 citations · 2021
7. 7
   Seeing is believing: increasing intraoperative awareness to scattered radiation in interventional procedures by combining augmented reality, Monte Carlo simulations and wireless dosimeters

   46 citations · 2015
8. 8
   Self-Supervised Surgical Tool Segmentation using Kinematic Information

   44 citations · 2019
9. 9
   FUN-SIS: A Fully UNsupervised approach for Surgical Instrument Segmentation

   40 citations · 2023
10. 10
    Articulated clinician detection using 3D pictorial structures on RGB-D data

    31 citations · 2016

Key Collaborators

Contact & Links