I am a research master student in Applied Mathematics at Polytechnique Montreal. My bachelor degree is in industrial engineering. My research interests are oriented towards explainability in machine learning algorithms, meaning interpreting and explaining the results of a trained model. I am particularly interested in the usage of decision trees, such as gradient boosted trees, applied to supply chain problems. I am under the supervision of Louis-Martin Rousseau.
Gauthier Melançon G, Grangier P, Prescott-Gagnon E, Sabourin E, Rousseau L-M, (2020), A Machine-Learning-Based System for Predicting Service Level Failures in Supply Chains. INFORMS Journal on Applied Analytics.