Main research fields

Machine learning

My research in machine learning focuses on applying machine learning methods, such as boosting and neural networks, to enhance predictive modeling in a way that aligns with actuarial objectives.

Insurance pricing

My work in insurance pricing aims to improve fairness, calibration, and predictive performance in advanced insurance pricing models.

Loss reserving

My work in loss reserving centers on individual claim reserving, developing statistical models that improve accuracy by capturing claim-specific development patterns and heterogeneity over time.

Dependence modeling

My research on dependence is dedicated to developing statistical tools for measuring and testing dependence structures in insurance data, particularly in zero-inflated contexts.

Editorial duties

Co-Editor for the European Actuarial Journal (2021–Present).

Associate Editor for Astin Bulletin: The Journal of the International Actuarial Association (2018–Present).

Associate Editor for Methodology and Computing in Applied Probability (2015–2024).