Guillaume Dumas is an associate professor and interdisciplinary computational psychiatrist who builds models and tools to bridge genes, neural dynamics, and social cognition across scales. With 12+ years of experience spanning academia and research institutes (Mila, Institut Pasteur, CHU Sainte-Justine, Université de Montréal), he blends dynamical systems, neurogenetics, and machine learning to study embodied social brains and develop digital-medicine applications. He contributes to open science—cofounding HackYourPhD—and to prominent open-source neurotech projects such as Brian2 and MNE-Python, reflecting hands-on expertise in spiking neural simulations and EEG/MEG tooling. Equally at home in art and public engagement, he translates complex science for radio and journals and runs design-infused projects that probe human–machine interaction.
12 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Mathematics, Physics, Bachelor of Science - BS, Mathematics, Physics at Lycée Sainte-Geneviève
Doctor of Philosophy - PhD, Cognitive Neurosciences, Highest honors, Doctor of Philosophy - PhD, Cognitive Neurosciences, Highest honors at Sorbonne Université
Master of Science - MS, Cognitive Science, Honours, Master of Science - MS, Cognitive Science, Honours at Ecole normale supérieure
Habilitation à Diriger des Recherches (HDR, Accreditation to Direct Research), Medicine, Highest honor, Habilitation à Diriger des Recherches (HDR, Accreditation to Direct Research), Medicine, Highest honor at Université de Paris
Diploma in Engineering, Advanced Systems Engineering, Diploma in Engineering, Advanced Systems Engineering at CentraleSupelec
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
QA Engineer / Test Automation Engineer
Contributions:13 commits, 1 PR, 39 comments in 5 days
Contributions summary:Guillaume primarily contributed to improving the quality and reliability of the MNE-Python library. Their work involved fixing encoding issues in EDF file imports, adding tests to cover edge cases like overlapping annotations, and updating the testing dataset. They also addressed code style issues and updated documentation to reflect changes in the library.
Brian is a free, open source simulator for spiking neural networks.
Role in this project:
Back-end Developer
Contributions:5 commits, 2 PRs, 1 comment in 5 days
Contributions summary:Guillaume primarily worked on implementing a spiking neural network simulation based on the Izhikevich 2007 paper. The contributions include creating and updating a Python script within the `examples/frompapers` directory. These updates involved defining neuron models, synaptic connections, and dopamine signaling, demonstrating a focus on computational neuroscience and the Brian2 simulation framework. Modifications to the code also involved adjusting model parameters and visualization elements for simulation output.
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