Summary
Yassine Benhajali is an applied machine learning and statistics project lead with 11 years of experience at the nexus of neuroimaging, anthropology, and mental health research. He builds data infrastructures and ethical access workflows for clinical data lakes and has delivered predictive and generative AI projects—such as 30-day psychiatric readmission models and a locally fine-tuned treatment-planning agent—within hospital research settings. His academic roots (PhD in neuro-anthropology) and hands-on work preprocessing thousands of brain scans give him rare fluency across study design, data curation, reproducible pipelines, and cluster-scale computation. Comfortable translating between clinicians and engineers, he has operationalized QC protocols, published methods, and launched citizen-science initiatives to broaden data use. Based in Quebec, he pairs deep domain expertise with a curiosity for cross-disciplinary tools, from Datalad and BIDS to Dask and generative models.
11 years of coding experience
9 years of employment as a software developer
PhD, Neuro-anthropology, PhD, PhD, Neuro-anthropology, PhD at Université de Montréal
Brevet de technicien supérieur (BTS), Electrical and Electronics Engineering, Brevet de technicien supérieur (BTS), Electrical and Electronics Engineering at Institut Superieur des Etudes Technologique de Radès ISETR
Online certificate, Machine learning in Python with scikit-learn, In progress, Online certificate, Machine learning in Python with scikit-learn, In progress at Inria Fun.MOOC
Online certificate, Deep learning and computer vision , In progress, Online certificate, Deep learning and computer vision , In progress at Pyimagesearch University
French, English, Arabic, Italian