World's Best Scientists 2026 revealed!
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Computer Science
France
2025

D-Index & Metrics

Computer Science

D-Index
63
Citations
112545
World Ranking
2664
National Ranking
37

Research.com Recognitions

  • 2025 - Research.com Computer Science in France Leader Award
  • 2023 - Research.com Computer Science in France Leader Award
  • 2022 - Research.com Computer Science in France Leader Award

Overview

Gaël Varoquaux is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research primarily focuses on the field of computer science, with significant contributions to artificial intelligence and its applications in healthcare and neuroscience.

The main fields of study for Varoquaux include:

  • Computer Science

Their subfields of study emphasize specialized areas such as:

  • Artificial Intelligence
  • Cognitive Neuroscience
  • Statistics and Probability
  • Radiology, Nuclear Medicine and Imaging
  • Health Informatics

Varoquaux's research covers several important topics, including:

  • Functional Brain Connectivity Studies
  • Machine Learning in Healthcare
  • Statistical Methods and Inference
  • Artificial Intelligence in Healthcare and Education
  • Explainable Artificial Intelligence (XAI)
  • Topic Modeling
  • Advanced Causal Inference Techniques

They have coauthored multiple papers with several frequent collaborators, including:

  • Bertrand Thirion
  • Demián Wassermann
  • Alexandre Gramfort
  • Olivier Grisel
  • Julie Josse

Their recent papers exemplify the diverse range of their research interests and contributions:

  • "Machine learning for medical imaging: methodological failures and recommendations for the future," 2022, npj Digital Medicine
  • "Metrics reloaded: recommendations for image analysis validation," 2024, Nature Methods
  • "International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium," 2020, npj Digital Medicine
  • "Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers," 2020, eLife
  • "Understanding metric-related pitfalls in image analysis validation," 2024, Nature Methods

Varoquaux frequently publishes in several leading venues, with multiple publications in:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • GigaScience
  • HAL (Le Centre pour la Communication Scientifique Directe)
  • bioRxiv (Cold Spring Harbor Laboratory)

Best Publications

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • The NumPy Array: A Structure for Efficient Numerical Computation

    Stéfan van der Walt;S Chris Colbert;Gaël Varoquaux

  • Machine learning for neuroimaging with scikit-learn.

    Alexandre Abraham;Alexandre Abraham;Fabian Pedregosa;Fabian Pedregosa;Michael Eickenberg;Michael Eickenberg;Philippe Gervais;Philippe Gervais

  • The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

    Krzysztof J. Gorgolewski;Tibor Auer;Vince D. Calhoun;R. Cameron Craddock

  • API design for machine learning software: experiences from the scikit-learn project

    Lars Buitinck;Gilles Louppe;Mathieu Blondel;Fabian Pedregosa

  • Establishment of Best Practices for Evidence for Prediction: A Review.

    Russell A Poldrack;Grace Huckins;Gael Varoquaux

  • Mayavi: 3D Visualization of Scientific Data

    P Ramachandran;G Varoquaux

  • Assessing and tuning brain decoders: cross-validation, caveats, and guidelines

    Gaël Varoquaux;Pradeep Reddy Raamana;Denis A. Engemann;Andrés Hoyos-Idrobo

  • Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

    Alexandre Abraham;Michael P. Milham;Adriana Di Martino;R. Cameron Craddock

  • NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain

    Krzysztof J. Gorgolewski;Krzysztof J. Gorgolewski;Gael Varoquaux;Gabriel Rivera;Yannick Schwarz

  • Scikit-learn: Machine Learning Without Learning the Machinery

    G. Varoquaux;L. Buitinck;G. Louppe;O. Grisel

  • Cross-validation failure: Small sample sizes lead to large error bars.

    Gaël Varoquaux

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • Mayavi: a package for 3D visualization of scientific data

    Prabhu Ramachandran;Gaël Varoquaux

  • Predicting brain-age from multimodal imaging data captures cognitive impairment

    Franziskus Liem;Gaël Varoquaux;Gaël Varoquaux;Jana Kynast;Frauke Beyer;Frauke Beyer

  • Which fMRI clustering gives good brain parcellations

    Bertrand Thirion;Gaël Varoquaux;Elvis Dohmatob;Jean-Baptiste Poline;Jean-Baptiste Poline

  • Seeing it all: Convolutional network layers map the function of the human visual system

    Michael Eickenberg;Michael Eickenberg;Michael Eickenberg;Alexandre Gramfort;Gaël Varoquaux;Bertrand Thirion;Bertrand Thirion

  • Benchmarking functional connectome-based predictive models for resting-state fMRI.

    Kamalaker Dadi;Mehdi Rahim;Alexandre Abraham;Darya Chyzhyk

  • Why do tree-based models still outperform deep learning on tabular data?

    Unknown

  • Brain covariance selection: better individual functional connectivity models using population prior

    Gael Varoquaux;Alexandre Gramfort;Jean-baptiste Poline;Bertrand Thirion

  • Machine Learning for Neuroimaging with Scikit-Learn

    Alexandre Abraham;Fabian Pedregosa;Michael Eickenberg;Philippe Gervais

  • Which fMRI clustering gives good brain parcellations

    Bertrand Thirion;Gael Varoquaux;Elvis Dohmatob;Jean-Baptiste Poline

Frequent Co-Authors

Bertrand Thirion
Bertrand Thirion University of Paris-Saclay
Jean-Baptiste Poline
Jean-Baptiste Poline Montreal Neurological Institute and Hospital
Danilo Bzdok
Danilo Bzdok Montreal Neurological Institute and Hospital
Russell A. Poldrack
Russell A. Poldrack Stanford University
R. Cameron Craddock
R. Cameron Craddock Facebook (United States)
Krzysztof J. Gorgolewski
Krzysztof J. Gorgolewski Stanford University
Julien Mairal
Julien Mairal French Institute for Research in Computer Science and Automation - INRIA
Tal Yarkoni
Tal Yarkoni The University of Texas at Austin

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