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
Site web
Google Scholar
LinkedIn
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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

Saskia Helbling
Postdoctorat - UdeM
Site web
Github
Google Scholar
Mahta Ramezanian
Maîtrise recherche - UdeM
Superviseur⋅e principal⋅e :
Irina Rish
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

Longitudinal intergenerational hyperscanning reveals indices of relationship formation and loneliness
Ryssa Moffat
Guillaume Dumas
Emily S. Cross
2025-10-15
bioRxiv (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
2025-10-08
eNeuro (publié)
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
2025-10-08
eNeuro (publié)
doi.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. In… (voir plus) 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
2025-10-06
Proceedings of the 42nd International Conference on Machine Learning (publié)
proceedings.mlr.press
Grokking Beyond the Euclidean Norm of Model Parameters
Tikeng Notsawo Pascal Junior
Pascal Notsawo
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
2025-10-06
Proceedings of the 42nd International Conference on Machine Learning (publié)
doi.org
openreview.net
Asymmetric developmental bifurcations in polarized environments: a new class of human variants, which may include autism.
Laurent Mottron
Alix Lavigne-Champagne
Boris C. Bernhardt
Guillaume Dumas
Sébastien Jacquemont
D. Gagnon
2025-09-29
Molecular Psychiatry (publié)
doi.org
Asymmetric developmental bifurcations in polarized environments: a new class of human variants, which may include autism.
Laurent Mottron
Alix Lavigne-Champagne
Boris C. Bernhardt
Guillaume Dumas
Sébastien Jacquemont
D. Gagnon
2025-09-29
Molecular Psychiatry (publié)
doi.org
Asymmetric developmental bifurcations in polarized environments: a new class of human variants, which may include autism.
Laurent Mottron
Alix Lavigne-Champagne
Boris C. Bernhardt
Guillaume Dumas
Sébastien Jacquemont
D. Gagnon
2025-09-29
Molecular Psychiatry (publié)
doi.org
Acute respiratory distress syndrome in patients with cancer: the YELENNA prospective multinational observational cohort study.
Peter Schellongowski
Michael Darmon
Philipp Eller
Laveena Munshi
Tobias Liebregts
Victoria Metaxa
Luca Montini
Tobias Lahmer
F. Taccone
Andry Van de Louw
Martin Balik
P. Pickkers
Pleun Hemelaar
Hemang Yadav
Andreas Barratt-Due
T. Karvunidis
Jordi Riera
G. Martucci
I. Martín-Loeches
Pedro Castro … (voir 6 de plus)
Nina Buchtele
Virginie Lemiale
Stefan Hatzl
Guillaume Dumas
T. Staudinger
Elie Azoulay
2025-09-25
Intensive Care Medicine (publié)
doi.org
Acute respiratory distress syndrome in patients with cancer: the YELENNA prospective multinational observational cohort study.
Peter Schellongowski
Michael Darmon
Philipp Eller
Laveena Munshi
Tobias Liebregts
Victoria Metaxa
Luca Montini
Tobias Lahmer
Fabio S. Taccone
Andry Van de Louw
Martin Balik
Peter Pickkers
Pleun Hemelaar
Hemang Yadav
Andreas Barratt-Due
Thomas Karvunidis
Jordi Riera
Gennaro Martucci
Ignacio Martin-Loeches
Pedro Castro … (voir 6 de plus)
Nina Buchtele
Virginie Lemiale
Stefan Hatzl
Guillaume Dumas
Thomas Staudinger
Elie Azoulay
2025-09-25
Intensive Care Medicine (publié)
doi.org
Acute respiratory distress syndrome in patients with cancer: the YELENNA prospective multinational observational cohort study.
Peter Schellongowski
Michael Darmon
Philipp Eller
Laveena Munshi
Tobias Liebregts
Victoria Metaxa
Luca Montini
Tobias Lahmer
F. Taccone
Andry Van de Louw
Martin Balik
P. Pickkers
Pleun Hemelaar
Hemang Yadav
Andreas Barratt-Due
T. Karvunidis
Jordi Riera
G. Martucci
I. Martín-Loeches
Pedro Castro … (voir 6 de plus)
Nina Buchtele
Virginie Lemiale
Stefan Hatzl
Guillaume Dumas
T. Staudinger
Elie Azoulay
2025-09-25
Intensive Care Medicine (publié)
doi.org
Acute respiratory distress syndrome in patients with cancer: the YELENNA prospective multinational observational cohort study
Peter Schellongowski
Michael Darmon
Philipp Eller
Laveena Munshi
Tobias Liebregts
Victoria Metaxa
Luca Montini
Tobias Lahmer
F. Taccone
Andry Van de Louw
Martin Balik
P. Pickkers
Pleun Hemelaar
Hemang Yadav
Andreas Barratt-Due
T. Karvunidis
Jordi Riera
G. Martucci
I. Martín-Loeches
Pedro Castro … (voir 6 de plus)
Nina Buchtele
Virginie Lemiale
Stefan Hatzl
Guillaume Dumas
T. Staudinger
Elie Azoulay
Purpose Acute respiratory failure is the leading reason for intensive care unit (ICU) admission among critically ill patients with cancer. W… (voir plus)e aimed to describe the clinical characteristics, risk factors, and outcomes of patients with cancer and acute respiratory distress syndrome (ARDS) and to evaluate associations of venovenous extracorporeal membrane oxygenation (ECMO) with outcomes in the subgroup with severe ARDS. Methods We conducted a multinational, prospective, observational cohort study of patients with cancer and ARDS in 13 countries in Europe and North America. The primary endpoint was 90-day mortality. Results Among 715 included patients, 73.4% had hematologic malignancies and 26.6% solid tumors; 31.2% had undergone hematopoietic stem-cell transplantation (168 allogeneic). ICU, hospital, and 90-day mortality rates were 55.3%, 70.9%, and 73.2%, respectively. By multivariate analysis, independent predictors of higher 90-day mortality were older age, peripheral vascular disease, severe ARDS at inclusion, acute kidney injury, and ICU admission as a time-limited trial (vs. full code). Conversely, lymphoma was associated with lower 90-day mortality. Among the 322 patients (45.7%) with severe ARDS at inclusion, 90-day mortality was 82.2%; with no difference between patients who received ECMO (n = 58, 18%) and those who did not (82.6% vs. 80.7%, P = 0.89). This finding remained unchanged in a double-adjusted overlap- and propensity-weighted Cox mixed-effects model (adjusted hazard ratio, 1.12; 95% confidence interval 0.65–1.94; P = 0.69). Conclusion Patients with cancer and ARDS, particularly severe forms, experience high 90-day mortality, irrespective of ECMO use. These findings suggest a need for nuanced ICU goals-of-care discussions and raise concerns about the generalizability of ECMO guidelines to this population. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-025-08113-7.
2025-09-25
Intensive Care Medicine (publié)
doi.org