Julien Gadonneix

// PhD Student · AI Researcher · Engineer

Julien
Gadonneix

Deciphering the cerebral bases of language with self-supervised learning. Building AI at the intersection of neuroscience and deep learning.

GitHub LinkedIn juliengado.2001@gmail.com X Bluesky

01 // about

Who I am

Background

I'm a PhD student at Université Paris Cité, investigating the cerebral bases of language using self-supervised learning. Trained as an engineer at École Polytechnique and with an MSc in Computational Biomedical Engineering from Imperial College London, I work at the crossroads of AI, neuroscience, and signal processing.

Research interests

Deep learning · Self-supervised learning · EEG & brain signals · Medical computer vision · Reinforcement learning · Computational neuroscience · Brain-machine interfaces

Contact

📧 juliengado.2001@gmail.com
📞 +33 6 03 57 43 62
📍 Paris, France

Beyond the lab

When I'm not training models, you'll find me on a soccer pitch, by the sea, or chasing powder on a ski slope.

02 // publications

Publications

Gadonneix, J., Zhang, M., Rapin, J., Evanson, L., Bourdillon, P., & King, J. R. (2026). Temporal structure of the language hierarchy within small cortical patches. arXiv preprint arXiv:2604.03021.

03 // education

Academic path

Oct 2025 –
Current

PhD – AI & Neuroscience

Université Paris Cité · Hôpital Fondation Adolphe de Rothschild
Paris, France
  • Deciphering the cerebral bases of language with self-supervised learning.
  • Using AI as both a tool and a model for brain data processing.
  • Supervised by Pierre Bourdillon and Jean-Rémi King.
Sep 2024 –
Sep 2025

MSc Computational Biomedical Engineering

Imperial College London
London, United Kingdom
  • Research project in deep learning applied to medical images.
  • Coursework: Statistics, Reinforcement Learning, Digital Signal Processing, Computer Vision, Brain-Machine Interfaces, Computational Neuroscience.
Sep 2021 –
Sep 2025

Diplôme d'ingénieur

École Polytechnique
Palaiseau, France
  • Specialised in Computer Science, Applied Mathematics and Computational Biology.
  • Coursework: Statistics, Algorithm Design, Decision Theory, Neuroscience, Bioinformatics, Machine & Deep Learning, Advanced RL, Autonomous Agents.
Aug 2019 –
Jul 2021

Preparatory Classes PCSI-PC*

Lycée privé Sainte-Geneviève
Versailles, France
  • Two-year intensive program in Mathematics, Physics, and Chemistry leading to top Grandes Écoles entrance exams.

04 // experience

Work experience

Jan 2025 –
Sep 2025

AI Research Scientist Intern – Medical Computer Vision

Imperial College London · Department of Bioengineering
London, United Kingdom
  • Implemented state-of-the-art deep learning architectures for medical images of eczema.
  • Data-efficient fine-tuning of large pre-trained foundation models and pre-training from scratch.
  • Uncertainty calibration using generative models, supervised by Prof. Reiko Tanaka.
Mar 2024 –
Jul 2024

AI Research Scientist Intern – Applied Neuroscience

Biomedical Signal Processing Lab · DTU
Copenhagen, Denmark
  • Developed and optimized deep learning models and signal processing techniques for EEG analysis.
  • Adapted pre-trained foundation models and self-supervised learning techniques.
  • Achieved state-of-the-art performance on emotion recognition from EEG signals.
Jun 2023 –
Aug 2023

Software Developer & Neuro-Engineering Intern

g.tec medical engineering GmbH
Schiedlberg, Austria
  • Data analysis and signal processing on EEG signals.
  • Designed API for data processing pipelines.
Sep 2021 –
Apr 2022

Firefighter

Marseille Fire Brigade
Marseille, France
  • Trained at the Marine Firefighting Academy for two months.
  • Worked as vehicle crew member and first responder.