Sharing knowledge
Teaching & mentoring
Teaching is central to my work, from a first Python exercise to an analysis of brain signals.
I create courses and hands-on workshops, teach cognitive neuroscience, and mentor research projects. The materials below are available to explore and reuse.
Courses & materials
Start with a workshop or work through a course at your own pace.
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Foundation models for M/EEG: from classical decoding to pretrained representations
Brainhack Montréal Fall 2026Thomson House, Montréal
A hands-on comparison of classical EEG decoding and pretrained foundation models on the same motor-imagery data, from frozen representations to fine-tuning.
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CoCo Lab crash course
CoCo Lab
A practical introduction for new lab members, covering Git, Python, MNE-Python, Alliance Canada computing, machine learning, and source estimation.
- Tool taught in the courseMNE-Python
Workshops & tutorials
Hands-on learning in AI and computational neuroscience.
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Indigenous Pathfinders in AI
Mila — Quebec AI InstituteMontréal, Canada
Designed and delivered sessions on programming in the age of AI, supervised learning, model evaluation, and building AI systems. Held office hours and supported exercises and participant projects.
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Future Imaginaries Workshop Series
Abundant IntelligencesUSA & Canada
- Nitsitapi Pod, University of Lethbridge (March): introduction to AI with hands-on activities.
- Haudenosaunee Pod, Western University (March): language-modeling concepts and a technical working session on LLMs.
- Tkaronto Pod, OCAD University (June): introduction to AI and hands-on activities using CNNs and LLMs.
- Huwai Pod (November): an additional workshop is scheduled.
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Representational Similarity Analysis with MEG
MAIN educational sessionsMontréal, Canada
A hands-on introduction to representations and representational similarity analysis, working through MEG data and analysis code.
- NewsEducational Tutorial @ MAIN 2024
- Related methodsPerception in brains & models
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Computational Neuroscience Summer School
Arabs in NeuroscienceOnline
Supported coding tutorials in probability, calculus, linear algebra, and statistics, and mentored a two-day project applying machine learning to fMRI decoding.
University courses
Teaching assistant roles in cognitive neuroscience at Université de Montréal.
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PSY2008: Methods in Cognitive Neuroscience I
Department of Psychology, Université de MontréalMontréal, Canada
Led question-and-answer and recap sessions, supported students throughout course activities, and assessed session assignments.
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PSY2007: Cognitive neuroscience laboratory
Department of Psychology, Université de MontréalMontréal, Canada
Taught Python programming and computational EEG analysis. Designed hands-on tutorials spanning preprocessing and cleaning through machine-learning analyses of data collected during the course.
Research mentoring
Projects I have supported across brain-signal analysis, machine learning, and neural representations.
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Maryem Benslimane
EEG–ANN representational similarity analysis of emotion processing, from an engineering graduation internship through ongoing MSc work.
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Syrine Mattousi
EEG-based analysis of epilepsy versus non-epilepsy using electrophysiological features, machine learning, and foundation models.
- Related researchClinical questions & EEG
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Fouad Lbakali
Foundation-model development for MEG data.
- Related researchBrain-signal models & methods
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Alexandre Louis
Classification of low versus high dream recallers using Riemannian geometry and machine learning.
- Related researchBrain states & cognition
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Mehdi Jerbi
ADHD versus non-ADHD classification from pediatric EEG using machine-learning methods.
- Related researchClinical questions & EEG
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Anis Abdeladim
Face-identity classification extending computational analyses developed during my MSc research.
- Related researchPerception in brains & models
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Meriem Rebaani
The effect of loss functions on learned representations in face-recognition models. Subsequently completed her engineering degree.
- Related researchPerception in brains & models