Gaël Varoquaux

96.0k total citations · 10 hit papers
137 papers, 14.8k 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 137 papers receiving a total of 14.8k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Cognitive Neuroscience, 38 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 (33 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 (33 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

131 papers receiving 14.3k citations

Hit Papers

The NumPy Array: A Structure for Efficient Numerical Comp... 2011 2026 2016 2021 2011 2014 2011 2016 2019 2.0k 4.0k 6.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gaël Varoquaux France 37 5.0k 3.0k 2.2k 1.5k 1.3k 137 14.8k
Robert E. Kass United States 50 4.8k 1.0× 1.0k 0.3× 294 0.1× 4.3k 2.9× 1.8k 1.4× 158 23.8k
Gerald van Belle United States 71 2.1k 0.4× 2.3k 0.8× 766 0.3× 229 0.2× 2.7k 2.1× 299 25.0k
Stéfan van der Walt United States 11 641 0.1× 3.2k 1.1× 1.3k 0.6× 943 0.6× 1.4k 1.1× 24 11.8k
William T. Vetterling United States 24 1.8k 0.4× 5.0k 1.7× 1.9k 0.9× 3.7k 2.5× 3.9k 3.0× 62 47.5k
James P. Morgan United States 92 2.1k 0.4× 1.6k 0.5× 2.4k 1.1× 101 0.1× 17.4k 13.4× 779 41.5k
Sam T. Roweis Canada 35 809 0.2× 1.5k 0.5× 546 0.2× 8.7k 5.8× 1.7k 1.3× 62 23.6k
Stephen Roberts United Kingdom 60 1.5k 0.3× 761 0.3× 156 0.1× 2.4k 1.6× 596 0.5× 315 11.5k
R. Mead United Kingdom 21 743 0.1× 737 0.2× 759 0.3× 2.4k 1.6× 1.6k 1.2× 49 23.6k
Donald W. Marquardt United States 19 515 0.1× 923 0.3× 1.3k 0.6× 1.8k 1.2× 2.7k 2.1× 37 30.0k
Xiaogang Wang China 120 1.3k 0.3× 2.6k 0.9× 2.4k 1.1× 14.4k 9.8× 3.7k 2.9× 1.5k 81.9k

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

20 of 20 papers shown
1.
Delacroix, Sylvie, Diana Robinson, Umang Bhatt, et al.. (2025). Beyond Quantification: Navigating Uncertainty in Professional AI Systems. Research Portal (King's College London). 1(1).
2.
Varoquaux, Gaël, et al.. (2025). Confidence intervals for performance estimates in brain MRI segmentation. Medical Image Analysis. 103. 103565–103565. 3 indexed citations
3.
Varoquaux, Gaël, et al.. (2025). How to select predictive models for decision-making or causal inference. GigaScience. 14. 1 indexed citations
4.
Josse, Julie, et al.. (2022). Causal effect on a target population: A sensitivity analysis to handle missing covariates. SHILAP Revista de lepidopterología. 10(1). 372–414. 9 indexed citations
5.
Perez-Lebel, Alexandre, et al.. (2022). Benchmarking missing-values approaches for predictive models on health databases. GigaScience. 11. 20 indexed citations
6.
Dadi, Kamalaker, Gaël Varoquaux, Josselin Houenou, et al.. (2021). Population modeling with machine learning can enhance measures of mental health. GigaScience. 10(10). 25 indexed citations
7.
Kiar, Gregory, Eric Petit, Ariel Rokem, et al.. (2021). Numerical uncertainty in analytical pipelines lead to impactful variability in brain networks. PLoS ONE. 16(11). e0250755–e0250755. 8 indexed citations
8.
Varoquaux, Gaël, et al.. (2021). Preventing dataset shift from breaking machine-learning biomarkers. GigaScience. 10(9). 49 indexed citations
9.
Josse, Julie, et al.. (2020). NeuMiss networks: differentiable programming for supervised learning with missing values. arXiv (Cornell University). 9 indexed citations
10.
Engemann, Denis A., David Sabbagh, G Lemaître, et al.. (2020). Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers. eLife. 9. 63 indexed citations
11.
Varoquaux, Gaël, Yannick Schwartz, Russell A. Poldrack, et al.. (2018). Atlases of cognition with large-scale human brain mapping. PLoS Computational Biology. 14(11). e1006565–e1006565. 41 indexed citations
12.
Varoquaux, Gaël & Russell A. Poldrack. (2018). Predictive models avoid excessive reductionism in cognitive neuroimaging. Current Opinion in Neurobiology. 55. 1–6. 38 indexed citations
13.
Eickenberg, Michael, Gaël Varoquaux, Bertrand Thirion, & Alexandre Gramfort. (2017). Convolutional Network Layers Map the Function of the Human Visual Cortex.. ERCIM news/ERCIM news online edition. 2017. 2 indexed citations
14.
Eickenberg, Michael, Alexandre Gramfort, Gaël Varoquaux, & Bertrand Thirion. (2016). Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage. 152. 184–194. 180 indexed citations
15.
Varoquaux, Gaël, Pradeep Reddy Raamana, Denis A. Engemann, et al.. (2016). Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines. NeuroImage. 145(Pt B). 166–179. 478 indexed citations breakdown →
16.
Ng, Bernard, Gaël Varoquaux, Jean Baptiste Poline, Michael D. Greicius, & Bertrand Thirion. (2015). Transport on Riemannian Manifold for Connectivity-Based Brain Decoding. IEEE Transactions on Medical Imaging. 35(1). 208–216. 18 indexed citations
17.
Schwartz, Yannick, Bertrand Thirion, & Gaël Varoquaux. (2013). Mapping paradigm ontologies to and from the brain. neural information processing systems. 26. 1673–1681. 5 indexed citations
18.
Ramachandran, Prabhu & Gaël Varoquaux. (2012). Mayavi2: 3D Scientific Data Visualization and Plottin'. Astrophysics Source Code Library. 1 indexed citations
19.
Varoquaux, E. & Gaël Varoquaux. (2008). . Physics-Uspekhi. 51(2). 205–205. 4 indexed citations
20.
Varoquaux, Gaël, Nassim Zahzam, C. Chatterjee, et al.. (2007). I.C.E.: An Ultra-Cold Atom Source for Long-Baseline Interferometric Inertial Sensors in Reduced Gravity. HAL (Le Centre pour la Communication Scientifique Directe).

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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