This Master’s thesis project, conducted under a Mitacs Globalink research internship, aims to address persistent challenges in hospital pharmaceutical supply management—such as fluctuating medication demand, supply-chain delays, and inefficient manual forecasting—by developing an end-to-end AI-enabled solution. Using a large dataset of 6 million prescription records and 2 million stock movement entries, the student will apply […]

This project explores whether surgical expertise can be measured from the way instruments move during a realistic neurosurgical simulation. The goal is to develop machine learning models that learn motion patterns from recorded instrument movements and use them to classify different levels of surgical skill. The dataset includes recordings from participants performing a surgical simulation […]

Dans les systèmes de monitoring physiologique (comme l’ECG ou l’EEG), certains événements rares, par exemple une crise d’épilepsie ou un épisode d’hypoglycémie sévère, peuvent avoir des conséquences graves s’ils ne sont pas détectés à temps. Ces événements, souvent brefs et peu fréquents, sont pourtant cruciaux à identifier rapidement pour permettre une alerte précoce et prévenir […]

IoT device security has become a major concern as these resource-constrained devices are increasingly deployed at scale, limiting the feasibility of advanced onboard security mechanisms. This challenge is particularly critical for Mobile Network Operators (MNOs), who must protect their infrastructure and customers from faulty or malicious IoT devices. To address this, MNOs rely on IoT […]

This research project aims to advance the development of reliable, interpretable, and causally grounded Artificial Intelligence (AI) methods by integrating neuro-symbolic reasoning into Large Language Models (LLMs), with a specific application to energy storage systems such as lithium-ion battery systems. While modern LLMs demonstrate impressive linguistic capabilities, they remain limited in their ability to reason […]

The proposed project aims to develop and validate a computational method for estimating how brain tissue moves and reacts to surgical tools using only videos captured from a microscope. The student will test both classical and modern deep-learning optical-flow algorithms, adapt them to the specific challenges of microscope imaging, and evaluate how well they can […]

Les systèmes tutoriels intelligents sont de plus en plus utilisés pour offrir un apprentissage personnalisé dans les environnements numériques. Ils permettent d’adapter les activités aux besoins de chaque apprenant, de suivre sa progression en temps réel et de fournir un accompagnement individualisé. Ces technologies génèrent une grande quantité de données sur la façon dont les […]

Le diabète de type 2 est une maladie chronique en forte augmentation qui touche des millions de personnes et représente un défi majeur pour les systèmes de santé. Il résulte de l’interaction de plusieurs facteurs, dont la génétique, l’état de santé, le mode de vie et l’environnement. Une détection tardive peut entraîner des complications graves, […]

This project aims to make power grids smarter and more efficient by using a type of artificial intelligence called Graph Neural Networks along with Deep Reinforcement Learning. Just like a GPS finds the best route for a car, our system will find the optimal paths for electricity to travel, especially from clean but unpredictable sources […]

This project develops a simulation-based framework to evaluate and optimize the sustainability performance of university value chains, supporting higher education institutions in their transition to net-zero carbon emissions. The primary goal is to systematically identify and prioritize key emission sources and impactful activities within university operations. A comprehensive literature review will inform the analysis of […]

The proposed research project aims to enhance transportation logistics in Quebec’s forestry sector by developing models that incorporate economic, environmental, and social factors. The intern will identify and measure key indicators, including transportation costs, CO2 emissions, and community impacts, using tools such as GIS and expert consultations. These indicators will be integrated into decision-support models […]

Le projet vise à initier le développement d’un cadre méthodologique ESG que les organisations pourront utiliser pour mieux évaluer l’impact environnemental, éthique et social de leurs projets numériques, et qui pourrait être intégré dans l’outil d’évaluation des projets numériques de Prompt.