I am currently an Associate Professor in the Department of Mathematics and Statistics at the University of Montreal.
My specialization is in Financial and Actuarial Mathematics and my current research interests are in the fields of Applied Machine Learning in banking and in responsible investment. Other general fields of interest of mine are Mathematical Finance and Risk Theory.
More specifically, current topics of interest to me now go beyond classical Ruin Theory, ranging from novel applications of Learning Algorithms in Finance and Banking to Micro-structural Modeling in High Frequency Finance.
More recently I have participated in the Artificial Intelligence transformation initiative of the National Bank of Canada. As the Chief AI Scientist I led the scientific efforts of the bank's strategy to leverage AI technologies accross all verticals. I had the opportunity to work on a wide variety of projects from wealth management to retail banking applications. I also led the first works towards laying down a AI governance framework.
Since 2018, I am General Director of the FinML Network.
Finance and Stochastics
High Frequency Finance
Past and Ongoing Research: At the Crossroads between Financial Mathematics and Actuarial Science
Over the years, my research interest have diversified and they now span a wide range of theoretical and applied questions in the fields of Insurance Ruin Theory, Mathematical Finance and more recently Applied Machine Learning in Banking. Representation Learning in banking, Deep Learning methods in high frequency market surveillance, explainabiliity in the context of model governance, leveraging alternative data to assess environmental, societal and governance (ESG) factors in the context of responsible investment are some of my research interests nowadays. These are some examples of my research.
Research Contracts: Applied Projects in Partnership with Industry
Having started my career studying applications of Lévy processes in finance and insurance I now have a particular interests in Statistical Learning Algorithms and High-Frequency Modeling in Finance. Although I continue to work on classical problems in Ruin Theory, I now also have research projects in partnership with key industrial quantitative research teams in the finance sector. These projects are carried out under industry-funded research contracts that were possible thanks to a professional network that I built over the years and that now allows me to explore applied directions in new exciting fields. These are some examples of this research.
COURSES AND STUDENT SUPERVISION
Courses and Graduate Supervision: Building a Research and Training Program
I actively participate in developing our programs in actuarial and financial mathematics, both at at the undergraduate and graduate level. I also organize various activities to promote and diversify research and professional opportunities for our students. As for graduate supervision, I have built a team of Master's and Ph.D. students with whom I work on a wide range of projects in Insurance Mathematics and Mathematical Finance.