معرفی
Christopher Blier-Wong is an Assistant Professor in the Department of Statistical Sciences within the Faculty of Arts and Science at the University of Toronto, where he joined in 2024 after completing a postdoctoral fellowship at the University of Waterloo. He holds a PhD in Actuarial Science from Université Laval (2023), along with multiple graduate degrees in Computer Science (AI specialization) and Actuarial Science from the same institution.
His research lies at the intersection of actuarial science, machine learning, and statistics, with a particular focus on dependence modelling and e-variables. His work explores non-life insurance, risk theory, risk-sharing mechanisms, and the application of machine learning techniques to actuarial problems. Recent publications demonstrate his expertise in constructing high-dimensional copulas, developing efficient risk allocation methods, and pioneering the use of image data in insurance pricing.
His research portfolio shows a strong trend toward developing computationally efficient methods for complex actuarial problems, particularly those involving dependence structures. He has made significant contributions to the understanding of Farlie-Gumbel-Morgenstern (FGM) copulas and their generalizations, creating methods that scale effectively to high dimensions while maintaining computational tractability.
Scientific Awards and Recognition:
- NSERC Postdoctoral Fellowship (2023-2025)
- ARC Graduate Student Presentation Award from Society of Actuaries (2022)
- Canada Graduate Scholarships Michael Smith Foreign Study Supplements (2022)
- Multiple research grants from NSERC, Université Laval, and industry partners
- Honor Roll for Academic Excellence at Université Laval (2018, 2020)
Blier-Wong currently leads research funded by a major sponsored research agreement titled 'Dependence, inference and unstructured data in actuarial science' (2025-2030). He has supervised graduate students through teaching courses such as 'STA 2536 Data Science for Risk Modelling' at the University of Toronto and previously taught 'ACT-1003 Complements in Mathematics' at Université Laval. His research group focuses on developing novel statistical methodologies with practical applications in insurance and risk management.
