I am a postdoc at UC Berkeley in the Gallant Lab. I defended my Ph.D. in 2018, in the Image, Data, Signal department at Telecom ParisTech in France, supervised by Alexandre Gramfort and Yves Grenier. I graduated from Ecole polytechnique in 2013 and EPFL in 2015.

My work focuses on machine learning and signal processing for neuroscience.

I have been a core developer of scikit-learn since 2015.

• Sep. 2021 - Presented a tutorial at the conference on Cognitive Computational Neuroscience
• Sep. 2019 - Received a reviewer free registration for NeurIPS 2019
• Jun. 2019 - Won PhD thesis award - 1st prize in Signal, Image and Vision, from the Club EEA, GRETSI and GdR ISIS
• Feb. 2019 - Joined the Gallant Lab at UC Berkeley as a post-doc
• Nov. 2018 - Won PhD students award - 1st prize at Université Paris-Saclay STIC doctoral school
• Nov. 2018 - Defended my PhD - Non-linear models for neurophysiological time series

Blog posts

• March 2018 - Dask-Distributed and Joblib

2022

2021

2019

2018

2017

2021

2019

2018

2017

2016

scikit-learn

General machine learning package.

pactools

Estimation of PAC in neural time series. Implementation of driven auto-regressive (DAR) models.

alphacsc

Convolutional sparse coding, univariate and multivariate models, Gaussian and alpha-stable noise distributions.

himalaya

Regularized linear models, computational efficiency for large numbers of targets, CPU/GPU.

voxelwise

Voxelwise modeling is a framework to perform functional magnetic resonance imaging (fMRI) data analysis.

2019-

(current)

Research in Machine Learning for fMRI Neuroimaging.
Advised by Jack Gallant.

2015-2018

(3 years)

Research in Signal Processing and Machine Learning for Neuroscience
Thesis: Non-linear models for neurophysiological time series.
Advised by Alexandre Gramfort and Yves Grenier.
PhD student award 1st prize winner from STIC doctoral school at Université Paris-Saclay
PhD thesis award 1st prize winner in Signal, Image and Vision, from the Club EEA, GRETSI and GdR ISIS

2016-2017

(1 year)

Practical datascience (one-week data camp) - Université Paris-Saclay (M2)
Linear time series (SIGMA202a) - Télécom ParisTech (M1)
Advisor for a year-long innovative team project (PACT) - Télécom ParisTech (L3)

2015

(5 months)

Development of scikit-learn, an open source machine learning library in python.
Development of SAG and NMF algorithms, library maintenance.

2014

(6 months)

Image processing research on motion deblurring.
State of the art improvement (confidential).

2013

(3 months)

Research on a new calculus paradigm using stochastic binary signals.
Matlab simulations and implementation of these gates with analogic CMOS circuit (with Cadence).
Summa cum laude from Ecole polytechnique (top 10%).

2011

(7 months)

Lead a paramedical unit at Paris Fire Brigade.
Decision making in critical situations (childbirth, cardiac arrests, strokes, car accidents, ...)

2015-2018

Thesis: Non-linear models for neurophysiological time series.
Advised by Alexandre Gramfort and Yves Grenier

2013-2015

Signal Processing, Image Processing, Video compression, Machine Learning, Distributed Information Systems, Wireless Transmission Algorithms, Microwaves, Photonics.
Research project on Human Echolocation.

2010-2013

1st et 2nd years : cross-curricular formation, with Mathematics, Physics and Informatics.
3rd year : specialization in Electrical Engineering : Computer Architecture, Printed Circuit Board Design, Semiconductor Physics, Photovoltaic, Signal Processing, Opto-Electronic.

2008-2010

A 2-year intensive undergraduate program for admission to France's top engineering schools.
Mathematics, Physics.