معرفی
Roel Henckaerts is a Research Fellow at the Insurance Research Group, KU Leuven. His work centers on integrating advanced computational methods with actuarial science to optimize insurance pricing models.
Research Focus: Henckaerts specializes in machine learning applications for insurance, including telematics-based dynamic pricing, interpretable AI for regulated industries, and data-driven risk assessment. His methodologies emphasize neural networks, tree-based models, and transparent surrogate systems to balance accuracy with regulatory compliance.
Publication Trends: Recent articles (2019–2025) demonstrate a shift toward neural networks and model interpretability, while earlier work (2016–2018) established foundations in tree-based methods and risk factor engineering. Thematic evolution shows consistent focus on bridging machine learning scalability with actuarial rigor.
Affiliations: As part of KU Leuven's Insurance Research Group, Henckaerts collaborates on industry-facing projects, though specific lab/team structures are undisclosed.
