Antoine Théberge
PhD Internship at Cardiff University Brain Research Imaging Centre (CUBRIC)
Sherbrooke, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolAntoine Théberge is a PhD candidate in Computer Science specializing in deep learning and neuroimaging, with nine years of software and research experience bridging academia and open-source. He has completed multiple PhD internships at leading imaging centers (UCL, CUBRIC) and teaches neural networks, translating cutting-edge research into reproducible code and coursework. As a contributor to DIPY — a well-regarded Python library for medical imaging — he improved tractography workflows by implementing seed management and tests that ensure spatial consistency of streamlines. Comfortable across back-end development, data science, and teaching, he brings both practical engineering rigor and academic depth to imaging-focused ML problems. Based in Sherbrooke, Canada, he pairs long-term research goals with hands-on contributions that make complex neuroimaging pipelines more robust and testable.
9 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université de SherbrookeDiplôme d'études collégiales, Administration et gestion de l''informatique / technologies de l''information, Diplôme d'études collégiales, Administration et gestion de l''informatique / technologies de l''information at Cégep Édouard-Montpetit
French, English
Github Skills (8)
medical-imaging10
diffusion-mri10
tractography10
python10
neuroimaging10
trac9
machine-learning8
bundle7
Programming languages (9)
Github contributions (5)
dipy/dipy
Mar 2019 - May 2019
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:7 commits, 1 PR, 19 comments in 1 month
Contributions summary:Antoine implemented features to save and manage seeds associated with streamlines in the tractogram. They modified existing workflows for local fiber tracking and particle filtering tracking to include the saving of seeds. Further, they added tests to verify that seeds are correctly returned and are in the same space as the streamlines. These changes focused on improving tractography functionality within the library.
signalpythonmicrostructurespatialtractography
AntoineTheb/RNN-RL
Jan 2020 - Jun 2021
Experiments with reinforcement learning and recurrent neural networks
Contributions:3 reviews, 24 commits, 3 PRs in 1 year 4 months
pytorchactor-criticrecurrent-neural-networksreinforcement-learningneural-networks
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