While telematics data with measurements of specific driving behaviors such as speeding, breaking, and turning, have shown significant predictive power in modeling accident risk, its usability has been challenged due to the low proportion of auto insurance policyholders that agree to provide their telematics data to the insurance companies. In this regard, we propose a […]

Les sécheresses extrêmes constituent un enjeu majeur dans un contexte de réchauffement climatique, affectant l’agriculture, les ressources en eau, la production énergétique et les écosystèmes. Leur caractère multi-échelle, dépendant des interactions entre précipitations, évapotranspiration, humidité du sol et stockage souterrain, rend leur détection et leur prévision complexes. Les indices traditionnels (SPI, SPEI, SSI) apportent une […]

Nowadays, many young Canadians [2] and newcomers [1] begin their financial journey with limited access to guidance on saving and investing, which leaves them at risk of debt and missed opportunities to build wealth. Existing tools are often complex and designed for experienced investors, not beginners. This project aims to develop and validate GradientX, an […]

The project focuses on Variational Mean-Field Games: it will provide theoretical guarantees for the convergence of numerical algorithms currently used and possibly develop also novel machine learning methods for it.

Beeye développe des algorithmes avancés d’optimisation automatisée des tâches, spécialement conçus pour résoudre des problématiques complexes liées à la gestion des ressources. Ses activités principales comprennent la création d’un système de planification automatisé qui s’attaque au problème de la planification multi-objectifs sous contraintes (MORCPSP). Ce système permet de gérer efficacement l’allocation des ressources, tout en […]

This project address the so-called Quantum Marginal Problem from a mathematical, physics and computational perspective. It develops the mathematical theory of optimal transport adapt to quantum states in order to make fundamental advances in physical aspects and computational algorithms solving the quantum marginal problem.

This project aims to develop new driving protocols and investigate the exotic physical properties of hyperbolic quantum materials using time-periodically modulated (“Floquet”) electrical circuits under magnetic driving. By leveraging these programmable circuits, we will explore how curvature and periodic modulation influence energy flow, spectral features, and effective magnetic behavior in synthetic hyperbolic lattices. The collaboration […]

Picton Mahoney Asset Management (“PICTON Investments”) was founded in 2004 to provide unique investment solutions to institutional, retail, and high-net-worth investors in Canada and globally. The Quantitative Research and Risk team at PICTON Investments is dedicated to developing and maintaining models that support investment decisions and risk assessments. With the increasing complexity of financial markets […]

Cortland Credit is a rapidly growing alternative investment manager specializing in private debt and public bond portfolios. Five years ago, the firm operated with fewer than 15 employees; today, the team has expanded to over 30 professionals. With this growth, the firm’s existing data management system – based primarily on Excel and CSV files stored […]

Picton Mahoney Asset Management (PICTON Investments) was founded in 2004 to provide unique investment solutions to institutional, retail and high net worth investors in Canada and around the world. They are 100% employee-owned and manage approximately $15.3 billion in sub-advisory, pension plan and hedge fund assets on behalf of their clients. The Multi-Strategy Team at […]

One of the fastest growing product categories in the investment industry in the United States is personalized direct indexing. This is a meaningful innovation that allows client specific requirements to be included in the delivery of investment solutions, such as considering concentrated risk positions held by the client, environmental social and governance related preferences, and […]

The study of complex systems using networks has become a central theme across disciplines, from social sciences and economics to biology and information systems. Graph theory, which models entities as nodes and their pairwise relations as edges, has provided a powerful framework for analyzing such systems. Graph-based methods have enabled advances in tasks such as […]