Benjamin Quost

Benjamin Quost is a Professor at the University of Technology of Compiègne affiliated with the Computer Engineering Department at the Royallieu Research Center. His research focuses on theoretical frameworks for handling uncertainty and imprecision in AI, including belief functions and imprecise probability.

• Machine learning with imperfect data
• Safe AI and fairness constraints
• Model explainability and partial decision analysis
• Classifier combination and information fusion
• Probability theory and Dempster-Shafer theory

He teaches modules ranging from foundational statistics for engineers (SY02) to advanced data mining and machine learning (SY09/SY19), covering topics like hypothesis testing, linear regression, principal component analysis, and support vector machines.