Alexandre Gramfort - AI ML Research Scientist at Meta

Alexandre Gramfort

AI ML Research Scientist at Meta

Paris, Ile-de-France

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Summary

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Alexandre Gramfort is an AI/ML research scientist with 19 years of experience at the intersection of machine learning, signal processing and neuroimaging, currently working on neural and bio time series at Meta Reality Labs. He combines deep academic roots—PhD-level work and senior research roles at Inria, CEA and Harvard/MGH—with hands-on software engineering as a core contributor to scikit-learn and major neuroimaging Python ecosystems (nilearn, MNE, nibabel). His contributions span algorithm design, reproducible scientific software and CI tooling, reflecting both theoretical rigor and production-quality coding. Based in Paris, he also serves in a technical civil service role at the French Ministry of Industry, an unusual blend of public-sector engineering and industrial research. Known for making complex neuroimaging formats and pipelines easier to use, he often bridges MATLAB and Python toolchains to accelerate brain-data science.

19 years of coding experience

12 years of employment as a software developer

BS, Applied Maths, Computer Science, BS, Applied Maths, Computer Science at École Polytechnique

Master, Image Processing, Applied Maths, Computer Science, Master, Image Processing, Applied Maths, Computer Science at Télécom Paris

Master, Image Processing, Medical Imaging, Machine Learning, Master, Image Processing, Medical Imaging, Machine Learning at Ecole Normale Supérieure de Cachan

French, English

Stackoverflow

Stats

64reputation

7kreached

2answers

0questions

Github Skills (46)

data-formats10

github-ci10

pytest10

python10

sphinx10

brain-imaging10

scikit10

testing10

machine-learning10

analyse10

matlab10

workflow-engine10

surf10

data-format10

cicd10

Programming languages (23)

C++CSSCCMakeHolyCMakefileTeXHTML

Github contributions (5)

scikit-learn/scikit-learn

Mar 2010 - Mar 2022

scikit-learn: machine learning in Python

Role in this project:

Data Scientist

Contributions:172 reviews, 1096 commits, 485 PRs in 12 years 2 months

Contributions summary:Alexandre's commits primarily focused on modifications and enhancements to existing machine learning models within the scikit-learn library, specifically within the realm of unsupervised learning, feature selection, and linear modeling techniques. The contributions included refactoring and improving the robustness of the code, as well as adding tests, examples, and features, such as incorporating support for diverse output types for several models and improving internal processing within the functions. Additionally, the user has been actively involved in making core changes to enhance and modernize the codebase for the next release.

data-analysispythonstatisticsdata-sciencelearn-machine-learning

mne-tools/mne-python

Dec 2010 - Jan 2023

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Role in this project:

Data Scientist & Backend Developer

Contributions:5 releases, 1622 reviews, 2496 commits in 12 years 2 months

Contributions summary:Alexandre's commits focus on enhancing examples, which mainly involve the application and integration of machine learning techniques such as the use of multi-taper spectral analysis for time-frequency representation. They have implemented features relating to data visualization, and have also worked on code related to the inverse solution. The user primarily utilized the MNE-Python library for performing these tasks, demonstrating skills in EEG data analysis and related source localization techniques.

visualizationneuroimagingneurosciencepythonstatistics

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