Hubert Banville - AI Research Scientist at Meta

Hubert Banville

AI Research Scientist at Meta

Greater Montreal Metropolitan Area Canada

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Summary

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Senior

🎓

Top School

Hubert Banville is an AI research scientist with 11 years of experience applying deep learning to real-world biosignals, currently working at Meta FAIR after a PhD in computer science at Université Paris‑Saclay. His doctoral work and long collaboration with Muse focused on improving EEG time-series processing, including practical signal-processing solutions like notch filters, epoching, and channel-wise validation. He has contributed to the widely used MNE-Python library by improving test coverage and robustness for core EEG/MEG functionality, blending rigorous research with production-quality engineering. Hubert’s background spans biomedical engineering, telecommunications, and hands-on neurotech development—from building SSVEP and P300 experiments to an interactive EEG tutorial app—giving him a rare mix of experimental, algorithmic, and software QA skills. Colleagues value his ability to turn noisy physiological data into reliable inputs for learning systems and to bridge open-source ecosystems with industrial research.

11 years of coding experience

7 years of employment as a software developer

Bachelor’s Degree, Biomedical Engineering, Bachelor’s Degree, Biomedical Engineering at Université de Montréal - Ecole polytechnique de Montréal

International Exchange Program, Biomedical Engineering, International Exchange Program, Biomedical Engineering at Nanyang Technological University

Master’s Degree, Telecommunications, Master’s Degree, Telecommunications at Institut national de la recherche scientifique

Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université Paris-Saclay

French, English

Github Skills (14)

ec10

ceph10

data-visualizations10

data-visualization10

data-visualisation10

el10

ereg10

pytest10

python10

signal-processing10

mage10

testing10

neuroimaging9

jupyter-notebook9

Programming languages (4)

JavaScriptHTMLJupyter NotebookPython

Github contributions (5)

alexandrebarachant/muse-lsl

Sep 2017 - Jan 2021

Python script to stream EEG data from the muse 2016 headset

Role in this project:

Data Scientist

Contributions:11 commits, 5 PRs, 13 comments in 3 years 4 months

Contributions summary:Hubert contributed to the development of EEG data analysis notebooks and stimulus presentation scripts within the context of the `muse-lsl` repository. The primary focus was on experiments involving Steady State Visual Evoked Potentials (SSVEP), Auditory P300, and Spatial Frequency tasks. Their work included setting up epoching, frequency domain visualizations, and integrating notch filters to improve data analysis, demonstrating an understanding of signal processing techniques applied to EEG data. The user updated notebooks to incorporate the use of utility functions for data loading, and added scripts for the Spatial Grating Task, improving the versatility of the repository.

pythonheadsetpython-scriptmusestream

mne-tools/mne-python

Sep 2018 - Aug 2021

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

Role in this project:

QA Engineer / Test Automation Engineer

Contributions:5 commits, 6 PRs, 55 comments in 2 years 11 months

Contributions summary:Hubert contributed to the `mne-python` repository by identifying and addressing bugs, implementing test cases, and updating documentation. They added new tests for event handling, data type validation, and channel-wise function application. Their work focused on improving the robustness of the codebase and ensuring the correct behavior of core functionalities within the MNE library.

visualizationneuroimagingneurosciencepythonstatistics

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