Portrait de Guillaume Dumas

Guillaume Dumas

Membre académique associé
Professeur agrégé, Université de Montréal, Département de psychiatrie et d’addictologie
Professeur adjoint, McGill University, Département de psychiatrie
Sujets de recherche
Apprentissage automatique médical
Apprentissage par renforcement
Apprentissage profond
Biologie computationnelle
Neurosciences computationnelles
Systèmes dynamiques
Théorie de l'apprentissage automatique
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Google Scholar
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Biographie

Guillaume Dumas est professeur agrégé de psychiatrie computationnelle à la Faculté de médecine de l'Université de Montréal et chercheur principal du laboratoire de psychiatrie de précision et de physiologie sociale du Centre de recherche du CHU Sainte-Justine. Il est titulaire de la chaire IVADO IA en santé mentale et chercheur-boursier junior 1 du Fonds de recherche du Québec - Santé (FRQS) dans le domaine de l’ IA en santé et de la santé numérique. En 2023, il a été retenu dans le cadre du Programme des chercheurs mondiaux CIFAR-Azrieli pour le programme de recherche Cerveau, esprit et conscience. Il a également été nommé parmi les Futurs leaders canadiens de la recherche sur le cerveau par la Fondation Brain Canada.

Il a auparavant été chercheur permanent en neurosciences et en biologie computationnelle à l'Institut Pasteur (Paris, France), ainsi que chercheur postdoctoral au Center for Complex Systems and Brain Sciences à l’Université Florida Atlantic (FAU), aux États-Unis. Il est titulaire d'un diplôme d'ingénieur en ingénierie avancée et informatique (École centrale Paris), de deux masters (physique théorique, Université Paris-Saclay; sciences cognitives, ENS/EHESS/Paris 5) et d'un doctorat en neurosciences cognitives (Sorbonne Université).

Ses recherches visent à combiner l’intelligence artificielle, les neurosciences cognitives et la médecine numérique à travers un programme interdisciplinaire suivant deux axes principaux :

- L’intelligence artificielle en santé mentale, par la création de nouveaux algorithmes pour étudier le développement de l'architecture cognitive humaine et pour fournir une médecine personnalisée en neuropsychiatrie grâce à des données allant du génome à celles des téléphones intelligents;

- Les neurosciences sociales en intelligence artificielle, par la traduction de la recherche fondamentale sur le cerveau et le formalisme des systèmes dynamiques en des modèles hybrides neurocomputationnels et d’apprentissage automatique (NeuroML) et de nouvelles architectures présentant des capacités d'apprentissage social (NeuroIA Sociale et IHM).

Étudiants actuels

Juan David Vargas
Maîtrise recherche - UdeM
Kastel Natalie
Doctorat - UdeM
Mahta Ramezanian
Maîtrise recherche - UdeM
Superviseur⋅e principal⋅e :
Irina Rish
Zahra Sheikhbahaee
Postdoctorat - UdeM
Co-superviseur⋅e :
Irina Rish
Github
Pascal Tikeng Notsawo
Doctorat - UdeM
Superviseur⋅e principal⋅e :
Guillaume Rabusseau
Site web
Github
Google Scholar
Tommaso Tosato
Postdoctorat - UdeM
Site web
Github
Google Scholar

Publications

Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind
Mouad Abrini
Omri Abend
Dina M. Acklin
Henny Admoni
Gregor Aichinger
Nitay Alon
Zahra Ashktorab
Ashish Atreja
Moises Auron
Alexander Aufreiter
Raghav Awasthi
Soumya Banerjee
Joseph Barnby
Rhea Basappa
Severin Bergsmann
Djallel Bouneffouf
Patrick Callaghan
Marc Cavazza
Thierry Chaminade
Sonia Chernova … (voir 88 de plus)
Mohamed Chetouan
Moumita Choudhury
Axel Cleeremans
J. Cywinski
Fabio Cuzzolin
Hokin Deng
N'yoma Diamond
C. D. Pasquasio
Guillaume Dumas
Max J. van Duijn
Mahapatra Dwarikanath
Qingying Gao
Ashok Goel
Rebecca R. Goldstein
Matthew C. Gombolay
Gabriel Enrique Gonzalez
Amar Halilovic
Tobias Halmdienst
Mahimul Islam
Julian Jara-Ettinger
Natalie Kastel
Renana Keydar
Ashish K. Khanna
Mahdi Khoramshahi
Jihyun Kim
Mihyeon Kim
Youngbin Kim
Senka Krivic
Nikita Krasnytskyi
Arun Kumar
JuneHyoung Kwon
EunJu Lee
Shane Lee
Peter R. Lewis 0001
Xue Li
Yijiang Li
Michal Lewandowski
Nathan Lloyd
Matthew B. Luebbers
Dezhi Luo
Haiyun Lyu
Dwarikanath Mahapatra
Kamal Maheshwari
Mallika Mainali
P. Mathur
Patrick Mederitsch
Shuwa Miura
Manuel Preston de Miranda
Reuth Mirsky
Shreya Mishra
Nina M. Moorman
Katelyn Morrison
John Muchovej
Bernhard Nessler
Felix Nessler
Hieu Minh Jord Nguyen
Abby Ortego
F. Papay
Antoine Pasquali
Hamed Rahimi
C. Raghu
Amanda L. Royka
Stefan Sarkadi
Jaelle Scheuerman
Simon Schmid
Paul Schrater
Anik Sen
Zahra Sheikhbahaee
Ke Shi
Reid G. Simmons
Nishant Singh
Mason O. Smith
Ramira van der Meulen
Anthia Solaki
Haoran Sun
Viktor Szolga
Matthew E. Taylor
Travis Taylor
Sanne van Waveren
Juan David Vargas
R. Verbrugge
Eitan Wagner
Justin D. Weisz
Ximing Wen
William Yeoh
Wenlong Zhang
Michelle Zhao
Shlomo Zilberstein
2025-04-28
ArXiv (prépublication)
arxiv.org
arxiv.org
Cortical differences across psychiatric disorders and associated common and rare genetic variants
Kuldeep Kumar
Zhijie Liao
Jakub Kopal
Clara Moreau
Christopher R. K. Ching
Claudia Modenato
Will Snyder
Sayeh Kazem
Charles-Olivier Martin
Anne-Marie Bélanger
Valérie K. Fontaine
Khadije Jizi
Rune Boen
Guillaume Huguet
Zohra Saci
Leila Kushan
Ana I. Silva
Marianne B.M. van den Bree
David E.J. Linden
Michael J. Owen … (voir 15 de plus)
Jeremy Hall
Sarah Lippé
Guillaume Dumas
Bogdan Draganski
Laura Almasy
Sophia I. Thomopoulos
Neda Jahanshad
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Armin Raznahan
Carrie Bearden
Tomas Paus
Paul M. Thompson
Sébastien Jacquemont
2025-04-19
medRxiv (prépublication)
doi.org
Online HD-tRNS over the right temporoparietal junction modulates social inference but not motor coordination
Quentin Moreau
Vincent Chamberland
Lisane Moses
Gabriela Milanova
Guillaume Dumas
2025-04-19
bioRxiv (prépublication)
doi.org
Contemporary review of critical illness following allogeneic hematopoietic stem cell transplant in adults.
Laveena Munshi
Guillaume Dumas
Bruno Ferreryro
Cristina Gutierrez
Boris Böll
Pedro Castro
Sanjay Chawla
Matteo Di Nardo
Antoine Lafarge
Colleen McEvoy
Djamel Mokart
Antonio Paulo Nassar
Judith Nelson
Frédéric Pène
Peter Schellongowski
Elie Azoulay
2025-04-16
Intensive Care Medicine (publié)
doi.org
Alcohol related hepatitis in intensive care units: clinical and biological spectrum and mortality risk factors: a multicenter retrospective study
Maxime Gasperment
Léa Duhaut
Nicolas Terzi
Côme Gerard
Luc Haudebourg
Alexandre Demoule
Mialy Randrianarisoa
Vincent Castelain
Sacha Sarfati
Fabienne Tamion
Charlene Le Moal
Christophe Guitton
Gabriel Preda
Arnaud Galbois
Thibault Vieille
Gaël Piton
Marika Rudler
Guillaume Dumas
Hafid AIT-OUFELLA
Background Alcohol related hepatitis is responsible for high morbidity and mortality, but little is known about the management of patients w… (voir plus)ith hepatitis specifically in intensive care units (ICU). Methods Retrospective study including patients with alcohol related hepatitis hospitalized in 9 French ICUs (2006–2017). Alcohol related hepatitis was defined histologically or by an association of clinical and biological criteria according to current guidelines. Results 187 patients (median age: 53 [43–60]; male: 69%) were included. A liver biopsy was performed in 51% of cases. Patients were admitted for impaired consciousness (71%), sepsis (64%), shock (44%), respiratory failure (37%). At admission, median SOFA and MELD scores were 10 [7–13] and 31 [26–40] respectively. 63% of patients received invasive mechanical ventilation, 62% vasopressors, and 36% renal replacement therapy. 66% of patients received corticosteroids, and liver transplantation was performed in 16 patients (8.5%). ICU and in-hospital mortality were 37% and 53% respectively. By multivariate analysis, ICU mortality was associated with SOFA score (without total bilirubin) (SHR 1.08 [1.02–1.14] per one-point increase), arterial lactate (SHR 1.08 [1.03–1.13] per 1 mmol/L) and MELD score (SHR 1.09 [1.04–1.14] per 1 point), while employment was associated with increased survival (HR 0.49 [0.28–0.86]). After propensity score weighting, the use of corticosteroids did not affect ICU mortality in the overall population but had a beneficial effect in the subgroup of patients with histological proof. Patient prognosis was also better in responders assessed by Lille score at day 7 (OR 6.67 [2.44–20.15], p  0.001). Conclusion Alcohol related hepatitis is a severe condition leading to high mortality in ICU patients. Severity of organ failure
2025-04-15
Annals of Intensive Care (publié)
doi.org
Genetic modulation of brain dynamics in neurodevelopmental disorders: the impact of copy number variations on resting-state EEG
Adrien Dubois
Elisabeth Audet-Duchesne
Inga Sophia Knoth
Charles-Olivier Martin
Khadije Jizi
Petra Tamer
Nadine Younis
Sébastien Jacquemont
Guillaume Dumas
Sarah Lippé
2025-04-11
Translational Psychiatry (publié)
doi.org
Collective decision making by embodied neural agents
Nicolas Coucke
Mary Katherine Heinrich
Axel Cleeremans
Marco Dorigo
Guillaume Dumas
Abstract Collective decision making using simple social interactions has been studied in many types of multiagent systems, including robot s… (voir plus)warms and human social networks. However, existing multiagent studies have rarely modeled the neural dynamics that underlie sensorimotor coordination in embodied biological agents. In this study, we investigated collective decisions that resulted from sensorimotor coordination among agents with simple neural dynamics. We equipped our agents with a model of minimal neural dynamics based on the coordination dynamics framework, and embedded them in an environment with a stimulus gradient. In our single-agent setup, the decision between two stimulus sources depends solely on the coordination of the agent’s neural dynamics with its environment. In our multiagent setup, that same decision also depends on the sensorimotor coordination between agents, via their simple social interactions. Our results show that the success of collective decisions depended on a balance of intra-agent, interagent, and agent–environment coupling, and we use these results to identify the influences of environmental factors on decision difficulty. More generally, our results illustrate how collective behaviors can be analyzed in terms of the neural dynamics of the participating agents. This can contribute to ongoing developments in neuro-AI and self-organized multiagent systems.
2025-03-25
PNAS Nexus (publié)
doi.org
arxiv.org
Grokking Beyond the Euclidean Norm of Model Parameters
Tikeng Notsawo Pascal Junior
Guillaume Dumas
Guillaume Rabusseau
Grokking refers to a delayed generalization following overfitting when optimizing artificial neural networks with gradient-based methods. I… (voir plus)n this work, we demonstrate that grokking can be induced by regularization, either explicit or implicit. More precisely, we show that when there exists a model with a property
2025-03-05
ICLR.cc/2025/Workshop/SLLM (publié)
openreview.net
openreview.net
Towards Multi-Brain Decoding in Autism: A Self-Supervised Learning Approach
Ghazaleh Ranjabaran
Quentin Moreau
Adrien Dubois
Guillaume Dumas
This study introduces a self-supervised learning (SSL) approach to hyperscanning electroencephalography (EEG) data, targeting the identifica… (voir plus)tion of autism spectrum condition (ASC) during social interactions. Hyperscanning enables simultaneous recording of neural activity across interacting individuals, offering a novel path for studying brain-to-brain synchrony in ASC. Leveraging a large-scale, single-brain EEG dataset for SSL pretraining, we developed a multi-brain classification model fine-tuned with hyperscanning data from dyadic interactions involving ASC and neurotypical participants. The SSL model demonstrated superior performance (78.13% accuracy) compared to supervised baselines and logistic regression using spectral EEG biomarkers. These results underscore the efficacy of SSL in addressing the challenges of limited labeled data, enhancing EEG-based diagnostic tools for ASC, and advancing research in social neuroscience.
2025-01-30
bioRxiv (prépublication)
doi.org
La communication financière à l’épreuve de la crise COVID : une gestion des impressions ?
Corinne Bessieux-Ollier
Grégoire Davrinche
Guillaume Dumas
Nous étudions l’impact de la crise du COVID-19 sur la gestion des impressions pratiquée par les entreprises françaises cotées. Cette c… (voir plus)rise ayant eu un impact fort sur l’activité des entreprises, nous observons si les dirigeants modifient la manière de présenter l’information liée aux résultats non-GAAP, à travers l’utilisation de stratégies d’obscurcissement. Les données sur la gestion des impressions ont été collectées manuellement dans les communiqués de résultats annuels des entreprises du SBF 120 sur la période 2018-2020. Nous constatons une diminution générale du niveau de gestion des impressions en période de crise, notamment pour les entreprises des secteurs ayant été les plus impactés par la crise COVID. Cette diminution est toutefois moins prononcée pour les entreprises ayant sous-performé par rapport à leur secteur d’activité et pour les entreprises dont la performance a le plus diminué (indépendamment du secteur auquel elles appartiennent). Nos résultats suggèrent que les entreprises dont la baisse de performance pourrait être attribuée à des causes internes (résultats très défavorables, résultats en deçà du secteur d’activité) demeurent soucieuses de l’image qu’elles renvoient et maintiennent leur niveau de gestion des impressions malgré la crise.
2025-01-29
Comptabilité Contrôle Audit (publié)
doi.org
A multivariable prediction model for invasive pulmonary aspergillosis in immunocompromised patients with acute respiratory failure (IPA-GRRR-OH score).
Alice Friol
Guillaume Dumas
Frédéric Pène
Alexandre Demoule
Achille Kouatchet
Laurent Argaud
Naike Bigé
Anne-Sophie Moreau
François Barbier
Djamel Mokart
Virginie Lemiale
Elie Azoulay
2025-01-24
Intensive Care Medicine (publié)
doi.org
Mirror effect of genomic deletions and duplications on cognitive ability across the human cerebral cortex
Kuldeep Kumar
Sayeh Kazem
Guillaume Huguet
Thomas Renne
Worrawat Engchuan
Martineau Jean-Louis
Jakub Kopal
Zohra Saci
Omar Shanta
Bhooma Thiruvahindrapuram
Jeffrey R. MacDonald
Josephine Mollon
Laura Schultz
Emma E M Knowles
David Porteous
Gail Davies
Paul Redmond
Sarah E. Harris
Simon R. Cox
Gunter Schumann … (voir 9 de plus)
Zdenka Pausova
Celia M. T. Greenwood
Tomas Paus
Stephen W Scherer
Laura Almasy
Jonathan Sebat
David C. Glahn
Guillaume Dumas
Sébastien Jacquemont
Regulation of gene expression shapes the interaction between brain networks which in-turn supports psychological processes such as cognitive… (voir plus) ability. How changes in level of gene expression across the cerebral cortex influence cognitive ability remains unknown. Here, we tackle this by leveraging genomic deletions and duplications - copy number variants (CNVs) that fully encompass one or more genes expressed in the human cortex - which lead to large effects on gene-expression levels. We assigned genes to 180 regions of the human cerebral cortex based on their preferential expression across the cortex computed using data from the Allen Human Brain Atlas. We aggregated CNVs in cortical regions, and ran a burden association analysis to compute the mean effect size of genes on general cognitive ability for each of the 180 regions. When affected by CNVs, most of the regional gene-sets were associated with lower cognitive ability. The spatial patterns of effect sizes across the cortex were correlated negatively between deletions and duplications. The largest effect sizes for deletions and duplications were observed for gene-sets with high expression in sensorimotor and association regions, respectively. These two opposing patterns of effect sizes were not influenced by intolerance to loss of function, demonstrating orthogonality to dosage-sensitivity scores. The same mirror patterns were also observed after stratifying genes based on cell types and developmental epochs markers. These results suggest that the effect size of gene dosage on cognitive ability follows a cortical gradient. The same brain region and corresponding gene-set may show different effects on cognition depending on whether variants increase or decrease transcription. The latter has major implications for the association of brain networks with phenotypes
2025-01-07
bioRxiv (prépublication)
doi.org