About me

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.

News

Blog posts

Publications

2022

Tom Dupré la Tour, Michael Eickenberg, Jack L Gallant
bioRxiv preprint, 2022
[pdf] [bibtex]

2021

Tom Dupré la Tour, Michael Lu, Michael Eickenberg, Jack L Gallant
NeurIPS workshop SVRHM, 2021
[pdf] [bibtex]

2019

Laetitia Grabot, Tadeusz W. Kononowicz, Tom Dupré la Tour, Alexandre Gramfort, Valérie Doyère, Virginie van Wassenhove
Journal of Neuroscience, 2019
[pdf] [bibtex]

2018

Tom Dupré la Tour
PhD Thesis, 2018
[pdf] [book_pdf] [tel] [pastel] [bibtex] [slides]
Tom Dupré la Tour*, Thomas Moreau*, Mainak Jas, Alexandre Gramfort
NeurIPS, 2018
[pdf] [arxiv] [bibtex] [poster] [code]
Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort
ICASSP, 2018
[pdf] [bibtex] [poster]

2017

Tom Dupré la Tour, Lucille Tallot, Laetitia Grabot, Valérie Doyere, Virginie van Wassenhove, Yves Grenier, Alexandre Gramfort
PLOS Computational biology, 2017
[pdf] [biorxiv] [bibtex] [poster] [slides] [code]
Mainak Jas, Tom Dupré la Tour, Umut Şimşekli, Alexandre Gramfort
NeurIPS, 2017
[pdf] [arxiv] [bibtex] [poster] [code]
Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort
ICASSP, 2017
[pdf] [bibtex] [poster] [code]

Talks

2021

with Fatma Deniz, Jack Gallant, and Matteo Visconti di Oleggio Castello
CCN Keynote and Tutorial, 2021, online
[tutorial] [video]
with Matteo Visconti di Oleggio Castello
Cognitive Neuroscience Colloquium, 2021, Berkeley
[slides]

2018

2017

Coupling and Causality in Complex Systems (C3S), 2017, Cologne
[slides]
Organization for Human Brain Mapping (OHBM), 2017, Geneva
[poster]
International Biomedical and Astronomical Signal Processing (BASP) Frontiers workshop, 2017, Villars-sur-Ollon
[poster]

2016

PyParis, 2016, Paris
[slides]

Software

Machine Learning
General machine learning package.
Python - Core developer

Phase amplitude coupling
Estimation of PAC in neural time series. Implementation of driven auto-regressive (DAR) models.
Python - Main developer

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

Multiple-target linear models
Regularized linear models, computational efficiency for large numbers of targets, CPU/GPU.
Python - Main developer

Tutorials for the voxelwise modeling framework
Voxelwise modeling is a framework to perform functional magnetic resonance imaging (fMRI) data analysis.
Python - Main developer

Experience

2019-

(current)
Postdoc - UC Berkeley
Research in Machine Learning for fMRI Neuroimaging.
Advised by Jack Gallant.

2015-2018

(3 years)
PhD student - Telecom ParisTech
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)
Teaching assistant - Telecom ParisTech
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)
Research developer - Telecom ParisTech
Development of scikit-learn, an open source machine learning library in python.
Development of SAG and NMF algorithms, library maintenance.

2014

(6 months)
Research intern - DxO Labs
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)
Full time first responder - Paris Fire Brigade
Lead a paramedical unit at Paris Fire Brigade.
Decision making in critical situations (childbirth, cardiac arrests, strokes, car accidents, ...)

Education

2015-2018

Télécom ParisTech - PhD in Signal Processing for Neuroscience
Thesis: Non-linear models for neurophysiological time series.
Advised by Alexandre Gramfort and Yves Grenier

2013-2015

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

2010-2013

Ecole polytechnique - Engineer degree (Master)
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

CPGE at Lycée Saint Louis - Undergraduate study
A 2-year intensive undergraduate program for admission to France's top engineering schools.
Mathematics, Physics.