PeopleofSuperintelligence

Researcher

Julien Cohen-Adad

Julien Cohen-Adad is a neuroimaging researcher whose Polytechnique Montréal lab builds open-source AI tools for spinal cord and brain MRI. He earned dual PhDs, in applied mathematics from École Centrale de Paris and in biomedical imaging from Université de Montréal, and completed a postdoctoral fellowship at the MGH Martinos Center at Harvard University. In 2017 he co-authored the NeuroImage paper on the Spinal Cord Toolbox; in 2021, the ivadomed deep learning framework; and in 2023, a deep learning method for contrast-agnostic spinal cord segmentation. Quebec Science selected his work among its Top 10 Discoveries of the Year in 2022, and Polytechnique Montréal gave him its Prize for Excellence in Research and Innovation in 2026. At Polytechnique Montréal, he is a full professor and director of the NeuroPoly lab, and an associate member of Mila – Quebec AI Institute.

Timeline

  1. 2008

    Two PhDs and a Harvard postdoc

    He holds dual PhDs, in applied mathematics from École Centrale de Paris and in biomedical imaging from Université de Montréal, where he finishes in 2008. A three-year postdoctoral fellowship in ultra-high field MRI at the MGH Martinos Center at Harvard University follows.

  2. 2017

    The Spinal Cord Toolbox paper

    In 2017, he co-authors the NeuroImage paper "SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data" with Benjamin De Leener, Simon Lévy and colleagues. His lab develops the toolbox and the IVADOMED framework as open-source software for reproducible, multi-site neuroimaging analysis.

  3. 2021

    ivadomed and the spine generic protocol

    In February 2021, the Journal of Open Source Software publishes ivadomed, a PyTorch-based deep learning framework for medical image analysis, with him among the authors alongside Charley Gros and Andreanne Lemay. In August 2021, he is first author of the Nature Protocols paper on the spine generic protocol for quantitative spinal cord MRI at 3T, and a companion paper reports data from 260 participants across 42 centers.

  4. 2022

    Quebec Science top 10 selection

    In 2022, his work is selected among Quebec Science's Top 10 Discoveries of the Year.

  5. 2022

    A Bavaria–Québec AI project

    In 2022, the Bavarian State Ministry of Science and the Arts and the Fonds de recherche du Québec fund a bilateral project on artificial intelligence for an integrative approach to brain and spinal cord analysis. He is the Québec partner, and Mark Mühlau of TUM Klinikum rechts der Isar is the Bavarian partner.

  6. October 2023

    Contrast-agnostic spinal cord segmentation

    In October 2023, he co-authors "Towards contrast-agnostic soft segmentation of the spinal cord" with Sandrine Bédard, Enamundram Naga Karthik and others. The deep learning method trains a U-Net on the Spine Generic Public Database to produce soft segmentations, and it reduces variability in spinal cord cross-sectional area across MRI contrasts.

  7. 2026

    A Polytechnique research prize

    Polytechnique Montréal's Academic Council awards him the 2026 Prize for Excellence in Research and Innovation, worth $10,000. His work spans spinal cord MRI, radiofrequency antenna design and deep learning image analysis tools, and protocols from his team are adopted in more than 100 imaging centers and hospitals worldwide.

  8. As of October 2026

    Professor and NeuroPoly director

    He is a full professor in the Department of Electrical Engineering at Polytechnique Montréal and director of the NeuroPoly neuroimaging lab. As an associate member of Mila – Quebec AI Institute, he applies AI to neuroimaging, from segmenting pathologies to bringing AI methods into clinical radiology.

Career

  1. NowPolytechnique MontréalFull professor
  2. NowMilaAssociate member
  3. From 2008Harvard UniversityPostdoctoral fellow

Education

  1. 2008Université de MontréalPh.D.
  2. École Centrale ParisPh.D.

From the biography.

  1. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Mila. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Mila. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  3. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Mila. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Polytechnique Montréal. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Julien Cohen-Adad — NeuroPoly documentation neuro.polymtl.ca. Checked 21 October 2026.
  2. Cohen-Adad Julien | CRIUGM criugm.qc.ca. Checked 21 October 2026.
  3. Citing SCT - Spinal Cord Toolbox documentation spinalcordtoolbox.readthedocs.io. Checked 21 October 2026.
  4. ivadomed: A Medical Imaging Deep Learning Toolbox | Journal of Open Source Software joss.theoj.org. Checked 21 October 2026.
  5. Home — ivadomed documentation ivadomed.readthedocs.io. Checked 21 October 2026.
  6. Generic acquisition protocol for quantitative MRI of the spinal cord | Nature Protocols nature.com. Checked 21 October 2026.
  7. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers | Scientific Data nature.com. Checked 21 October 2026.
  8. Professor Julien Cohen-Adad receives Polytechnique Montréal award bayfor.org. Checked 21 October 2026.
  9. Towards contrast-agnostic soft segmentation of the spinal cord arxiv.org. Checked 21 October 2026.
  10. Julien Cohen-Adad | Mila mila.quebec. Checked 21 October 2026.