معرفی
Dries Benoit is an Associate Professor in Data Analytics at Ghent University, specializing in Bayesian Statistics and its applications in business engineering. He teaches advanced courses in Bayesian Statistics, Statistical Modeling & Datamining, and Pricing & Revenue Management. Additionally, he serves as a visiting professor at Université de Namur and IESEG School of Management, where he contributes cross-institutional expertise in statistical modeling.
- Primary Affiliation: Ghent University
- Secondary Affiliations: Université de Namur, IESEG School of Management
Research Focus:
Dries Benoit's work bridges methodological advancements in Bayesian statistics with real-world applications across business domains. Core areas include marketing modeling, customer relationship management (CRM), learning analytics, and operations research. His interdisciplinary collaborations extend to medicine, energy, and education sectors, leveraging data science to solve complex problems in churn prediction, demand forecasting, and multimodal analysis.
Publications & Research Trends:
His recent publications highlight:
- Machine learning techniques for question difficulty estimation
- Uncertainty quantification in industrial AI
- Transformer-based models for ordinal regression
- Churn prediction in business-to-business contexts
- Deep learning applications in cultural analytics
- Ensemble methods for robust classification
