Ahmed Halioui is a data scientist with nine years of experience building production-ready ML pipelines and large-scale data systems, currently focused on improving debit fraud detection at Desjardins using IBM Watson and CP4D. He pairs a PhD-level background in cognitive computing with hands-on cloud engineering—having designed graph-based knowledge models, recommender systems, and SQL/NoSQL architectures on Azure that handled hundreds of millions of edges and terabytes of metadata. His work spans the full lifecycle from data ingestion and indexing to A/B testing and stakeholder-facing reporting, yielding measurable gains such as faster data access and dramatically reduced storage. Comfortable bridging research and production, he has also taught data mining and bioinformatics, bringing clarity to complex analyses for investigators and scientists. Notably, he built automated cloud APIs that became daily tools for 10+ researchers, demonstrating an ability to operationalize research workflows at scale.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Cognitive Computing, Doctor of Philosophy - PhD, Cognitive Computing at Université du Québec à Montréal
Master's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at Institut supérieur d'informatique et de gestion de Kairouan
TGROWLeR system abstracts general patterns from workflow sequences previously extracted from texts. It comprises two modules –a workflow extractor and a pattern miner– both relying on a specific domain ontology.
Contributions:1 release, 33 commits, 2 PRs in 4 years 2 months
Contributions:5 PRs, 12 pushes, 2 branches in 1 year 1 month
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