Gaël Varoquaux

441 total papers · 95.7k total citations
135 papers, 14.7k citations indexed

About

Gaël Varoquaux is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Gaël Varoquaux has authored 135 papers receiving a total of 14.7k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Cognitive Neuroscience, 39 papers in Radiology, Nuclear Medicine and Imaging and 32 papers in Artificial Intelligence. Recurrent topics in Gaël Varoquaux's work include Functional Brain Connectivity Studies (72 papers), Neural dynamics and brain function (34 papers) and Advanced Neuroimaging Techniques and Applications (32 papers). Gaël Varoquaux is often cited by papers focused on Functional Brain Connectivity Studies (72 papers), Neural dynamics and brain function (34 papers) and Advanced Neuroimaging Techniques and Applications (32 papers). Gaël Varoquaux collaborates with scholars based in France, United States and Germany. Gaël Varoquaux's co-authors include Stéfan van der Walt, Bertrand Thirion, Alexandre Gramfort, Alexandre Abraham, Prabhu Ramachandran, Fabian Pedregosa, Andreas Mueller, Russell A. Poldrack, Michael Eickenberg and Jean‐Baptiste Poline and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Gaël Varoquaux

129 papers receiving 14.2k citations

Hit Papers

The NumPy Array: A Struct... 2011 2026 2016 2021 2011 2014 2011 2016 2019 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. The NumPy Array: A Structure for Efficient Numerical Computation
    2011 6.7k citations Stéfan van der Walt, Gaël Varoquaux et al. Computing in Science & Engineering profile →
  2. Machine learning for neuroimaging with scikit-learn
    2014 1.3k citations Alexandre Abraham, Fabian Pedregosa et al. Frontiers in Neuroinformatics profile →
  3. Mayavi: 3D Visualization of Scientific Data
    2011 491 citations Prabhu Ramachandran, Gaël Varoquaux Computing in Science & Engineering profile →
  4. Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines
    2016 474 citations Gaël Varoquaux, Pradeep Reddy Raamana et al. NeuroImage profile →
  5. Establishment of Best Practices for Evidence for Prediction
    2019 435 citations Russell A. Poldrack, Grace Huckins et al. JAMA Psychiatry profile →
  6. Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
    2016 418 citations Alexandre Abraham, Michael P. Milham et al. NeuroImage profile →
  7. Scikit-learn
    2015 415 citations Gaël Varoquaux, Lars Buitinck et al. GetMobile Mobile Computing and Communications profile →
  8. NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain
    2015 378 citations Krzysztof J. Gorgolewski, Gaël Varoquaux et al. Frontiers in Neuroinformatics profile →
  9. Machine learning for medical imaging: methodological failures and recommendations for the future
    2022 315 citations Gaël Varoquaux, Veronika Cheplygina npj Digital Medicine profile →
  10. Predicting brain-age from multimodal imaging data captures cognitive impairment
    2016 301 citations Franziskus Liem, Gaël Varoquaux et al. NeuroImage profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Gaël Varoquaux 4.9k 2.9k 2.2k 1.5k 1.3k 135 14.7k
Robert E. Kass 4.8k 1.0× 998 0.3× 294 0.1× 4.3k 2.9× 1.8k 1.4× 158 23.7k
Gerald van Belle 2.1k 0.4× 2.4k 0.8× 763 0.3× 227 0.2× 2.7k 2.1× 301 25.0k
William T. Vetterling 1.8k 0.4× 5.0k 1.7× 1.9k 0.9× 3.7k 2.5× 3.9k 3.1× 62 47.5k
Stéfan van der Walt 634 0.1× 3.1k 1.1× 1.3k 0.6× 938 0.6× 1.4k 1.1× 24 11.6k
R. Mead 739 0.1× 737 0.3× 756 0.3× 2.4k 1.6× 1.6k 1.2× 49 23.5k
James P. Morgan 2.1k 0.4× 1.6k 0.6× 2.4k 1.1× 101 0.1× 17.4k 13.5× 778 41.5k
Sam T. Roweis 807 0.2× 1.5k 0.5× 548 0.2× 8.6k 5.9× 1.7k 1.3× 62 23.5k
Stephen Roberts 1.5k 0.3× 755 0.3× 155 0.1× 2.4k 1.6× 592 0.5× 316 11.4k
Peter Li 653 0.1× 736 0.3× 288 0.1× 1.0k 0.7× 1.8k 1.4× 149 13.0k
Bernhard E. Boser 972 0.2× 150 0.1× 1.5k 0.7× 6.7k 4.6× 1.3k 1.0× 158 24.3k

Countries citing papers authored by Gaël Varoquaux

Since Specialization
Citations

This map shows the geographic impact of Gaël Varoquaux's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gaël Varoquaux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaël Varoquaux more than expected).

Fields of papers citing papers by Gaël Varoquaux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gaël Varoquaux. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gaël Varoquaux. The network helps show where Gaël Varoquaux may publish in the future.

Co-authorship network of co-authors of Gaël Varoquaux

This figure shows the co-authorship network connecting the top 25 collaborators of Gaël Varoquaux. A scholar is included among the top collaborators of Gaël Varoquaux based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gaël Varoquaux. Gaël Varoquaux is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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