Team

This work is made available by a community of people, which originated from the INRIA MIND Project Team and scikit-learn but grew much further.

An up-to-date list of contributors can be seen in on GitHub.

Additional credit goes to Michael Hanke and Yaroslav Halchenko for data and packaging.

Core developers

The nilearn core developers are:

• Alexis Thual

• Bertrand Thirion

• Elizabeth DuPre

• Hao-Ting Wang

• Jerome Dockes

• Nicolas Gensollen

• Taylor Salo

• Yasmin Mzayek

Other contributors

Some other past or present contributors are:

• Alexandre Gramfort

• Binh Nguyen

• Gael Varoquaux

• Julia Huntenburg

• Thomas Bazeille

• Alexandre Abadie

• Alexandre Abraham

• Andrés Hoyos Idrobo

• Ben Cipollini

• Chris Gorgolewski

• Danilo Bzdok

• Elvis Dohmatob

• Fabian Pedregosa

• Jean Kossaifi

• Jerome-Alexis Chevalier

• Kamalakar Reddy Daddy

• Kshitij Chawla

• Loic Estève

• Martin Perez-Guevara

• Michael Eickenberg

• Philippe Gervais

• Pierre Bellec

• Salma Bougacha

• Vincent Michel

• Virgile Fritsch

Funding

Alexandre Abraham, Gael Varoquaux, Kamalakar Reddy Daddy, Loic Estève, Mehdi Rahim, Philippe Gervais were paid by the NiConnect. project, funded by the French Investissement d’Avenir.

Kshitij Chawla was paid by INRIA.

Yasmin Mzayek is paid by the Human Brain Project . Previously Nicolas Gensollen was funded by HBP.

NiLearn is also supported by DigiCosme and DataIA .

Citing nilearn

There is no paper published yet about nilearn. We are waiting for the package to mature a bit. However, the patterns underlying the package have been described in: Machine learning for neuroimaging with scikit-learn.

We suggest that you read and cite the paper. Thank you.

Citing scikit-learn

A huge amount of work goes into scikit-learn, upon which nilearn relies heavily. Researchers who invest their time in developing and maintaining the package deserve recognition with citations. In addition, the INRIA MIND Project Team needs citations to the paper in order to justify paying a software engineer on the project. To guarantee the future of the toolkit, if you use it, please cite it.

See the scikit-learn documentation on how to cite.