Arthur Dehgan
PhD Candidate
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolArthur Dehgan is a PhD candidate in Neuro-AI with nine years of experience applying machine learning and deep learning to large-scale time-series neuroimaging data (MEG/EEG). He combines signal and image processing foundations with production-minded software skills—Python, PyTorch, NumPy/Pandas—and scalable Slurm/HPC workflows used on Compute Canada/Québec clusters. His research on terabyte-scale datasets like CamCAN produced widely cited publications and practical tools, including the open-source MEEGNet library that makes neural networks more interpretable for neuroscientists. Arthur has hands-on experience building reproducible pipelines, data visualizations for model interpretability, and Riemannian-based covariance methods for brain-signal classification. Based in Montreal, he bridges academic rigor and engineering discipline to translate Neuro-AI research into deployable machine learning solutions. A less obvious strength is his background in big-data cluster setup (Hadoop/Spark) from early CNRS work, giving him end-to-end expertise from infrastructure to models.
9 years of coding experience
Doctor of Philosophy - PhD, Neuro-AI, Doctor of Philosophy - PhD, Neuro-AI at Université de MontréalMPSI - PSI, MPSI - PSI at CPGE Janson de SaillyMaster of Science (M.S.), High Tech Imaging, Master of Science (M.S.), High Tech Imaging at Télécom SudParis
English, German, French
Github Skills (9)
science5
neuroscience5
classification4
python4
computer-science4
recall3
machine-learning3
statistics3
deep-learning2
Programming languages (2)
Github contributions (5)
arthurdehgan/config_files
May 2019 - Jul 2024
Contributions:42 pushes, 2 branches in 5 years 3 months
arthurdehgan/meegnet
Mar 2018 - Mar 2025
CAMCAN dataset analysis
Contributions:2 PRs, 548 pushes, 6 branches in 7 years 1 month
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