Mazid Osseni
Conseiller En Intelligence Artificielle Et Valorisation Des Données
Quebec, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolMazid Osseni is a Machine Learning researcher and PhD candidate at Université Laval with 10 years of experience applying interpretable, parsimonious models to healthcare and bioinformatics problems. Currently advising on AI and data valorization at the Institut universitaire de cardiologie et de pneumologie de Québec, he blends research leadership with hands-on Python development and a track record of conference publications. He is skilled in both supervised and unsupervised methods, with a preference for transparent techniques (set covering machines, decision trees, random forests) and a special interest in natural language processing. His background includes industry-facing roles at Leap Conseil and Valence Discovery and long-standing academic teaching and research positions, giving him a rare combination of applied impact and rigorous scientific grounding. Colleagues value his intellectual curiosity and ability to communicate complex predictive concepts clearly to multidisciplinary teams.
10 years of coding experience
8 years of employment as a software developer
Ph.D Candidate in Machine Learning, Ph.D Candidate in Machine Learning at Université Laval
French, English
Github Skills (16)
decay10
regularization9
sparse9
python-bindings5
bioinformatics4
web3py4
genomics3
machine-learning3
python3
cython3
dynamic-programming2
core-library2
genome2
toolbox2
genome-analysis2
Programming languages (2)
Github contributions (5)
dizam92/pyTorchReg
Feb 2019 - May 2022
Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.
Contributions:12 commits, 2 PRs, 7 pushes in 3 years 3 months
l1-regularizationneuronal-networksparseelasticnetl2-regularization
dizam92/multiomic_predictions
Mar 2021 - Sep 2022
Contributions:41 commits, 3 PRs, 54 pushes in 1 year 6 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.