Team

This work is made available by a community of people, which originated from the INRIA Parietal Project Team and the 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:

• `Alexandre Gramfort`_

• `Alexis Thual`_

• `Bertrand Thirion`_

• `Binh Nguyen`_

• `Elizabeth DuPre`_

• `Gael Varoquaux`_

• `Hao-Ting Wang`_

• `Jerome Dockes`_

• `Julia Huntenburg`_

• `Nicolas Gensollen`_

• `Taylor Salo`_

• `Thomas Bazeille`_

Triage team

The triage team is responsible for helping to review and prioritize issues related to Nilearn development, as described in the Maintenance. We are actively looking for more contributors to join the team. You can indicate your interest by contacting one of the Nilearn Core developers.

Other contributors

Some other past or present contributors are:

• `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.

`Nicolas Gensollen`_ is paid by the Human Brain Project .

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 Parietal 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.