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Marc Frappier is a Full Professor in the Department of Computer Science at the Université de Sherbrooke. He earned his Ph.D. in Computing Science from the University of Ottawa in 1995. Frappier has extensive experience in academia, having served as a full professor since 1995. His teaching repertoire includes formal methods in software engineering and discrete mathematics. His recent research interests focus on the evaluation of deep unsupervised learning algorithms for intrusion detection systems, robust anomaly detection, and the challenges posed by inaccurate contamination ratios in data. Moreover, he actively contributes to several interdisciplinary projects that leverage artificial intelligence to analyze financial markets and enhance cybersecurity. Frappier has published numerous papers in prestigious journals and arXiv, and his work is frequently cited. He is also an active member of various research communities, continually seeking collaboration aimed at advancing the field of computer science.
Université de Sherbrooke • Sherbrooke, QC, Canada
Full professor at the Department of Computer Science with a focus on formal methods and machine learning.
The University of Sherbrooke is primarily a French-language institution; functional French (B2/C1 level) is typically required for most programs unless specified for research-based paths.