PeopleofSuperintelligence

Researcher

Ariel Rokem

Ariel Rokem is a neuroscientist and AI researcher who develops machine-learning and computer-vision tools for brain imaging. He grew up in Jerusalem, Berkeley, and Stockholm, trained in neuroscience and computational neuroimaging, and served in research roles at the University of Washington before joining CAMH. His work includes fractional ridge regression, studies of infant myelin and glaucoma, and a 2025 editorial on data-driven brain mapping; he also coauthored a data-science book for neuroimaging research and received two field awards. Since 2026, he is a Senior Scientist at CAMH's Krembil Centre for Neuroinformatics, where he develops AI-informed tools to study brain connectivity and mental health.

Now at
Centre for Addiction and Mental Health

Timeline

  1. 2002–2015

    Degrees and Stanford training

    Ariel Rokem grows up in Jerusalem, Berkeley, and Stockholm and earns a B.Sc. in biology and psychology at the Hebrew University of Jerusalem in 2002. At Humboldt University in Berlin, he completes a computational neuroscience postbac with Andreas Herz from 2002 to 2003, then earns an M.A. in cognitive psychology with Merav Ahissar at the Hebrew University in 2005. In 2010, he completes a neuroscience PhD with Michael Silver at UC Berkeley and trains in computational neuroimaging with Brian Wandell at Stanford from 2011 to 2015.

  2. 2015–2026

    Senior data scientist to faculty

    At the University of Washington eScience Institute, he works as a Senior Data Scientist from 2015 to 2020. In 2020, he joins the University of Washington's Department of Psychology faculty and is a Research Associate Professor there in 2024; he remains on the faculty through 2026.

  3. 2020

    Fractional ridge regression

    In 2020, he and Kendrick Kay propose fractional ridge regression, which reparameterizes ridge regression through the ratio of regularized to unregularized coefficient L2 norms. They provide open-source Python and MATLAB implementations and show that the method is fast and scalable for large-scale data problems.

  4. 2023

    Myelin develops more slowly after birth

    In 2023, he is senior author of a PNAS study that uses new software to compare MRI scans from 300 babies and finds that myelin develops more slowly after birth.

  5. 2023–2024

    A book and two honors

    In 2023, he receives the Neuro–Irv and Helga Cooper Foundation Open Science Prize as a member of the Brain Imaging Data Structure steering group. The 2024 paperback edition of Data Science for Neuroimaging: An Introduction, which he coauthors with Tal Yarkoni, covers data-science methods and their application in neuroimaging research. In 2024, he receives the Organization for Human Brain Mapping Education in Neuroimaging Award.

  6. 2024

    A glaucoma classification study

    In 2024, he coauthors a study that classifies glaucoma with convolutional neural networks using tissue properties from the optic radiations.

  7. 2025

    Human brain mapping at the Singularity

    In 2025, he publishes the Aperture Neuro editorial Human Brain Mapping at the Singularity, which examines frictionless reproducibility through open data, code re-execution, and the common task framework.

  8. Since 2026

    Senior Scientist at CAMH

    In 2026, he joins CAMH's Krembil Centre for Neuroinformatics as a Senior Scientist. His work develops brain-imaging analysis tools inspired by machine learning, computer vision, and AI, with a focus on brain connectivity and the links between brain structure and mental health.

Career

  1. Since 2026Centre for Addiction and Mental HealthSenior Scientist
  2. 2015–2020University of WashingtonSenior Data Scientist
  3. 2011–2015Stanford University

Education

  1. 2010University of California, BerkeleyNeuroscience PhD
  2. 2005Hebrew University of JerusalemM.A.
  3. 2002Hebrew University of JerusalemB.Sc.

From the biography.

  1. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Stanford University. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Washington. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Washington. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes University of Washington. 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.

Colleagues

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

Sources and credits

Photo: We have no published photo of Ariel Rokem yet. Send us a free-licensed photo.

  1. Ariel Rokem talks/slides - Hello 👋 slides.arokem.org. Checked 21 October 2026.
  2. Ariel Rokem - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.
  3. Interview with Prof. Ariel Rokem, 2024 Winner of the Education Award — OHBM Communications ohbm-com.com. Checked 21 October 2026.
  4. Fractional ridge regression: a fast, interpretable reparameterization of ridge regression arxiv.org. Checked 21 October 2026.
  5. Q&A: How new software is changing our understanding of human brain development washington.edu. Checked 21 October 2026.
  6. Dr. Ariel Rokem | CAMH camh.ca. Checked 21 October 2026.
  7. Data science for neuroimaging : an introduction : paperback | NDL Search | National Diet Library ndlsearch.ndl.go.jp. Checked 21 October 2026.
  8. Convolutional neural network-based classification of glaucoma using optic radiation tissue properties nature.com. Checked 21 October 2026.
  9. Human brain mapping at the Singularity | Published in Aperture Neuro apertureneuro.org. Checked 21 October 2026.