Defended my PhD in Computer Engineering with grade Excellent at École de technologie supérieure (ÉTS), University of Quebec.
Predicting Intermittent Job Failure Categories for Diagnosis Using Few-Shot Fine-Tuned Language Models accepted at FSE 2026 Industry Track.
Towards Open-Ended Discovery for Low-Resource NLP accepted at UncertaiNLP @ EMNLP 2025.
Presented Efficient Detection of Intermittent Job Failures Using Few-Shot Learning at ICSME 2025 in Auckland, New Zealand.
Awarded the Arbour Foundation Doctoral Scholarship ($30,000 CAD) for academic excellence, leadership, and social impact.
SLID, artifact of « Efficient Detection of Intermittent Job Failures Using Few-Shot Learning », accepted at the ICSME 2025 Artifact Track.
Joined the Computer Research Institute of Montreal (CRIM) as a part-time R&D Scientist Intern, working on applied AI research projects.
Build Optimization: A Systematic Literature Review accepted at ACM Computing Surverys (CSUR).
Efficient Detection of Intermittent Job Failures Using Few-Shot Learning accepted at ICSME 2025.
Presented Towards Build Optimization Using Digital Twins at PROMISE 2025 (co-located with FSE 2025) in Trondheim, Norway.
Started as Lecturer at École de technologie supérieure (ÉTS).
Presented On the Diagnosis of Flaky Job Failures: Understanding and Prioritizing Failure Categories at ICSE SEIP 2025 in Ottawa, Canada.
Towards Build Optimization Using Digital Twins accepted at PROMISE 2025.
FlakeRanker, artifact of « On the Diagnosis of Flaky Job Failures », accepted at the ICSE 2025 Artifact Evaluation Track.
On the Diagnosis of Flaky Job Failures: Understanding and Prioritizing Failure Categories accepted at ICSE SEIP 2025.
Started as Teaching Assistant at École de technologie supérieure (ÉTS).
Started a Mitacs Accelerate Fellowship with TELUS on AI-powered CI/CD reliability.
Started PhD in Computer Engineering at École de technologie supérieure (ÉTS), University of Quebec, under Prof. Francis Bordeleau.
Graduated Valedictorian with highest honors (mention Très Bien) from the M.Sc. in Big Data: Decision Intelligence and Machine Learning at the University of Rennes.
Joined Energiency as a full-time Data Scientist under a work-study program.
Joined Worldline as a Software Engineer Intern.