Graduate Course Lecturer In Artifical Intelligence
Sherbrooke, Quebec, Canada
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Summary
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Senior
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Gabriel Lauzier is an AI researcher and educator with nine years of hands-on experience building and deploying machine learning systems across academia and industry. As a graduate course lecturer and AI specialist at Université de Sherbrooke, he teaches Bayesian inference, clustering, and neural networks while mentoring students on image preprocessing and capstone projects. His applied research includes industrial image segmentation using Transformers, real-time ML deconvolution on FPGAs for time-of-flight CT, and edge MLOps tooling with MLflow, Kubernetes and Docker. Comfortable across embedded systems, ROS, web stacks and cloud-native deployments, he bridges low-level, real-time constraints with product-driven research outcomes. Colleagues value his drive to find practical solutions and his knack for translating advanced algorithms into deployable systems.
9 years of coding experience
1 year of employment as a software developer
Master of Science in Electrical Engineering, Master of Science in Electrical Engineering at Université de Sherbrooke
High School Degree, Mathematics and Computer Science, High School Degree, Mathematics and Computer Science at Cégep de Sherbrooke
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