Short Bio

I am currently senior research scientist manager at Meta Reality Labs in Paris. I work on machine learning technologies to decode surface EMG signals (see paper). Previously I was research director (DR, HdR) at Inria, leading the MIND Team, known formerly as Parietal. My work is on statistical machine learning, signal and image processing, optimization, scientific computing and software engineering with primary applications in neuroscience and biosignal processing. Before joining Inria, I was an assistant professor for 5 years at Telecom Paris in the signal processing and machine learning department and before I was at the Martinos Center for Biomedical Imaging at Harvard University in Boston. I was also a co-director of the Center for Data Science at Université Paris-Saclay. In 2015, I got an ERC Starting Grant for my project called Signal and Learning Applied to Brain data (SLAB) and in 2019 a grant ANR Chaire on Artificial Intelligence called BrAIN.

See my list of publications.

Contact

Email @ Inria: alexandre.gramfort@inria.fr

Email @ Meta: agramfort@meta.com

Software

  • scikit-learn - A Python project for machine learning.
  • MNE - A complete package to process EEG and MEG data: forward and inverse problems, preprocessing, stats, time-frequency analysis.
  • openmeeg - C++ package for low-frequency bio-electromagnetism including the EEG/MEG forward problem. OpenMEEG implements the Symmetric BEM which has shown to provide very accurate solutions. Some features: parallel processing, Python Bindings, Matlab integration with Fieldtrip and BrainStorm.

More on my Github Page

Ex- Inria Team

With my academic activities, I work closely with the following people:

PhD Students

Alumni

Teaching