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

Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoit Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
NeurIPS, 2022
[pdf] [bibtex] [code]
Tom Dupré la Tour, Michael Eickenberg, Anwar O. Nunez-Elizalde, Jack L. Gallant
bioRxiv preprint, 2022
[pdf] [bibtex] [code]

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
PhD student award - 1st prize at Université Paris-Saclay STIC doctoral school [link]
PhD thesis award - 1st prize in Signal, Image and Vision, from the Club EEA, GRETSI and GdR ISIS [link] [news]
[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.