npadoy

Short Bio

Photo Nicolas Padoy is Professor of Computer Science at the University of Strasbourg and Director of Computer Science and AI Research at IHU Strasbourg. He joined the University of Strasbourg as an Assistant Professor on a Chair of Excellence in September 2012, where he created and is currently leading the research group CAMMA on Computational Analysis and Modeling of Medical Activities. CAMMA focuses on computer vision, medical image analysis, activity recognition, artificial intelligence and the applications thereof to surgical workflow analysis and human-machine cooperation during surgery. Nicolas Padoy graduated with a Maîtrise in Computer Science from the Ecole Normale Supérieure de Lyon in 2003 and with a Diploma in Computer Science from the Technische Universität München (TUM), Munich, in 2005. He completed his PhD jointly between the Chair for Computer Aided Medical Procedures at TUM and the INRIA group MAGRIT in Nancy. Subsequently, he was a postdoctoral researcher and later an Assistant Research Professor in the Laboratory for Computational Interactions and Robotics at the Johns Hopkins University, USA. In 2015, Nicolas Padoy was awarded the Guy Ourisson Prize by the Cercle Gutenberg, which recognizes promising young researchers in Alsace. In 2020, he was awarded one of 43 national AI Chairs by the Agence Nationale de la Recherche (ANR) for his project AI4ORSafety. In 2023, he was awarded a European ERC Consolidator Grant for his project CompSURG.

Selected Professional Activities

  • General Chair, IPCAI 2023-2025
  • Associate Editor, Elsevier journal on Medical Image Analysis (IF 13.8)
  • Program Chair, MICCAI 2021
  • General Chair, CLINICCAI 2021, 2022, 2023
  • Program Chair, IPCAI 2017
  • Area Chair, IPCAI 2016, 2018, 2019, 2021
  • Area Chair, MICCAI 2013, 2015, 2016
  • Workshop Chair, MICCAI 2015
  • Organizer, CVPR Medical Computer Vision Workshop, 2018, 2019, 2020, 2021, 2022, 2023
  • Organizer, M2CAI Workshop and Challenges, MICCAI 2016

Selected Teaching Activities

  • Computer vision
  • Deep learning
  • Programming and algorithms

Selected Publications

  • A. Murali, D. Alapatt, P. Mascagni, A. Vardazaryan, A. Garcia, N. Okamoto, D. Mutter, N. Padoy, Latent Graph Representations for Critical View of Safety Assessment, IEEE Transactions on Medical Imaging (TMI), arXiv preprint, code, dataset, 2023
  • L. Sestini, B. Rosa, E. De Momi, G. Ferrigno, N. Padoy, FUN-SIS: a Fully UNsupervised approach for Surgical Instrument Segmentation, Elsevier Medical Image Analysis, arXiv preprint, 2023
  • T. Yu, P. Mascagni, J. Verde, J. Marescaux, D. Mutter, N. Padoy, Live Laparoscopic Video Retrieval with Compressed Uncertainty, Elsevier Medical Image Analysis, arXiv preprint, 2023
  • S. Ramesh, V. Srivastav, D. Alapatt, T. Yu, A. Murali, L. Sestini, C.I. Nwoye, I. Hamoud, A. Fleurentin, G. Exarchakis, A. Karargyris, N. Padoy, Dissecting Self-Supervised Learning Methods for Surgical Computer Vision, Elsevier Medical Image Analysis, arXiv preprint, code, 2023
  • C.I. Nwoye, T. Yu, C. Gonzalez, B. Seeliger, P. Mascagni, D. Mutter, J. Marescaux, N. Padoy, Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos, Elsevier Medical Image Analysis, arXiv preprint, doi:10.1016/j.media.2022.102433, code1, code2, 2022
  • V. Srivastav, A. Gangi, N. Padoy, Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the OR, Elsevier Medical Image Analysis, arXiv preprint, code, 2022
  • H. Kassem, D. Alapatt, P. Mascagni, Consortium AI4SafeChole, A. Karargyris, N. Padoy, Federated Cycling (FedCy): Semi-supervised Federated Learning of Surgical Phases, IEEE Transactions on Medical Imaging (TMI), arXiv preprint, 2022
  • C.I. Nwoye, D. Alapatt, T. Yu, A. Vardazaryan, […], C. Gonzalez, N. Padoy, CholecTriplet2021: A benchmark challenge for surgical action triplet recognition, Elsevier Medical Image Analysis, arXiv preprint, code, 2022
  • P. Mascagni, D. Alapatt, T. Urade, A. Vardazaryan, D. Mutter, J. Marescaux, G. Costamagna, B. Dallemagne, N. Padoy, A Computer Vision Platform to Automatically Locate Critical Events in Surgical Videos: Documenting Safety in Laparoscopic Cholecystectomy, Annals of Surgery, 2021
  • P. Mascagni, A. Vardazaryan, D. Alapatt, T. Urade, T. Emre, C. Fiorillo, P. Pessaux, D. Mutter, J. Marescaux, G. Costamagna, B. Dallemagne, N. Padoy, Artificial Intelligence for Surgical Safety: Automatic Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy using Deep Learning, Annals of Surgery, 2021
  • P. Mascagni, M. R. Rodriguez-Luna, T. Urade, E. Felli, P. Pessaux, D. Mutter, J. Marescaux, G. Costamagna, B. Dallemagne, N. Padoy, Intraoperative time out to promote the implementation of the critical view of safety in laparoscopic cholecystectomy: a video-based assessment of 343 procedures, Journal of The American College of Surgeons, arXiv preprint, 2021
  • S. Kannan, G. Yengera, D. Mutter, J. Marescaux, N. Padoy, Future-State Predicting LSTM for Early Surgery Type Recognition, IEEE Transactions on Medical Imaging (TMI), arXiv preprint, doi:10.1109/TMI.2019.2931158, 2019
  • A.P. Twinanda, G. Yengera, D. Mutter, J. Marescaux, N. Padoy, RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations, IEEE Transactions on Medical Imaging (TMI), arXiv preprint, 2018

Full List of Publications

Selected Lectures & Keynotes

  • 2023: Invited Keynote at Digital Health Summit (Munich, Germany)
    Title: AI and the Future of Surgery
  • 2023: Invited Keynote at 1st ICCV Workshop on Scene Graphs and Graph Representation Learning (Paris, France)
    Title: Modeling Surgeries with Differentiable Graph Representations
  • 2023: Invited talk at Department of Biomedical Engineering, University of Basel (Basel, Switzerland)
    Title: Deploying AI Methods for Safe Laparoscopic Cholecystectomy
  • 2023: Invited talk at Indian Institute of Technology (Delhi, India)
    Title: Artificial Intelligence Approaches for Cognitive Assistance in the Operating Room
  • 2023: Invited talk at All India Institute of Medical Science (Delhi, India)
    Title: Artificial Intelligence Approaches for Cognitive Assistance in the Operating Room
  • 2022: Invited talk at Policlinico Universitario Fondazione Agostino Gemelli (Rome, Italy)
    Title: Surgical Data Science at IHU Strasbourg
  • 2022: Invited Lecture at Summer School on Medical Robotics, Shanghai Jiao Tong University (Shanghai, China)
    Title: AI-Driven Safety Monitoring in Laparoscopic Procedures
  • 2022: Invited Talk at 109. Jahreskongress der Chirurgie (Bern, Switzerland)
    Title: Artificial Intelligence in the Operating Room
  • 2021: Annual Crossgrove Lecture at University Health Network (Toronto, Canada)
    Title: Surgical Data Science: Impact on Safety and Workflow in the Operating Room
  • 2020: Invited talk at University of Ulm (Ulm, Germany)
    Title: Artificial Intelligence for Surgical Activity Monitoring in the Operating Room
  • 2019: Invited talk at CVPR Workshop on 3D Computer Vision for Medical Environments (Long Beach, USA)
    Title: Computer Vision for Monitoring Safety in the Operating Room
  • 2019: Invited lecture at Collège de France (Paris, France)
    Title: Vers une tour de contrôle intelligente des blocs opératoires
  • 2018: Invited lecture at Hamlyn Winter School on Surgical Imaging and Vision (London, UK)
    Title: Computer Vision Approaches for Surgical Workflow Analysis
  • 2018: Invited talk at SophIA Summit (Sophia-Antipolis, France)
    Title: Monitoring Surgical Activities with Artificial Intelligence
  • 2018: Invited keynote at OR2.0 ‘Context-Aware Operating Theaters’ Workshop (Granada, Spain)
    Title: Monitoring Surgical Activities with Artificial Intelligence
  • 2018: Invited talk at B.E.S.T. Innovation Symposium (Strasbourg, France)
    Title: Big Data and Machine Learning: A New Frontier in Surgical Innovation
  • 2018: Invited talk at Hamlyn Symposium – Workshop on Deep Learning in Medical Robotics (London, UK)
    Title: Deep Learning for Real-time Predictions from Endoscopic Videos
  • 2018: Invited talk at Congress of European Association of Endoscopic Surgery (London, UK)
    Title: Automated Predictions from Surgical Videos for OR Workflow Assistance
  • 2018: Invited keynote at High Tech Périphérique Radiology Congress (Nantes, France)
    Title: A Global Radiation Awareness System using Augmented Reality and Monte Carlo Simulations
  • 2018: Invited talk at Beyond Gynecologic Surgery Congress (Clermont-Ferrand, France)
    Title: Real-time Analysis of the Surgical Workflow : Moving towards a Surgical Control Tower
  • 2017: Invited lecture at Hamlyn Winter School on Surgical Imaging and Vision (London, UK)
    Title: Computer Vision Approaches for Surgical Workflow Analysis
  • 2017: Invited talk at Séminaire conjoint des académies de médecine et des sciences “Mathématiques, Big Data et Cancérologie” (Paris, France)
    Title: Science des données chirurgicales: vers une tour de contrôle des blocs opératoires?
  • 2017: Invited talk at INRIA (Grenoble, France)
    Title: Multi-view Activity Detection and Analysis in the Operating Room
  • 2016: Invited talk at ARTORG Center (Bern, Switzerland)
    Title: Activity Perception and Analysis in the Operating Room: Moving Towards a Surgical Control Tower
  • 2016: Invited talk at University of Berkeley (Berkeley, USA)
    Title: Activity Perception and Analysis in the Operating Room: Moving Towards a Surgical Control Tower
  • 2016: Invited talk at CVPR Workshop on Medical Computer Vision (Las Vegas, USA)
    Title: Clinician Detection and Pose Estimation in the Operating Room
  • 2016: Invited keynote at GDR ISIS event ‘Vision et modélisation 3D d’environnements dynamiques’ (Paris, France)
    Title: Articulated Clinician Detection Using 3D Pictorial Structures on RGB-D Data
  • 2016: Invited keynote at Conference Cosine6 (Bordeaux, France)
    Title: Activity Perception and Analysis in the Operating Room: Moving Towards a Surgical Control Tower

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