L’accompagnement des personnes aînées en perte ou à risque de perte d’autonomie et la préservation de l’indépendance et des relations sociales constituent des priorités en termes de santé publique. Dans ce contexte, le projet de stage vise à développer le robot d’assistance sociale T-Top pour soutenir les aînés en situation d’isolement social, en s’appuyant sur […]

Nearly half of adults live with at least one of the top ten chronic conditions—such as hypertension, osteoarthritis, or diabetes—and two in five people can expect a cancer diagnosis in their lifetime. These conditions are among the leading causes of morbidity worldwide, significantly reducing quality of life and increasing the risk of mental health challenges […]

In accordance with the Digital Policy Hub research foci on artificial intelligence, as well as digitization, security and democracy, the underlying purpose of the project is to research the limitations of language translation technologies in order to suggest updated policy for international institutions to responsibly use them. This directly supports the Digital Policy Hub’s objective […]

Agriculture must meet the needs of the continuously growing world population. To this end, sustainable strategies that improve resource use efficiency (human, fuel, water, herbicides, pesticides, and fertilizers), reduce inputs and environmental impacts, and sensing methodologies that provide actionable information are in demand. This research will increase the potential for collecting high-quality data in the […]

We aim to enhance AI learning of MR images by providing scans of the pectoralis major, deltoid, and gluteus maximus from young healthy adults to Deep Anatomical Federated Network (DAFNE). DAFNE is a decentralized AI software that improves over time through user refinement. Machine Learning (ML) models enable faster automated analysis, distinguishing anatomical structures and […]

This project will help Connected Canadians improve the way it delivers free digital literacy training to older adults. By observing, participating in, and helping lead technology workshops and other training sessions, the student intern will gather feedback and suggest ways to make the training offerings even more helpful and easy to follow. The intern will […]

A key goal in modern organic chemistry is the development of efficient synthetic routes to access industrially relevant structures starting from highly abundant feedstock chemicals, while minimizing the use of expensive rare-earth metals for catalysis. This project aims to synthesize urea-type containing heterocycles, which are a common structural feature found in many biologically active compounds, […]

This project explores the feasibility of using a hybrid sensing system that combines Near-Infrared Spectroscopy (NIR) and Electronic Nose (E-Nose) technologies, enhanced by machine learning, to detect early signs of spoilage and contamination in stored grains. By analyzing changes in grain structure and gas emissions, the study contributes to ongoing research on reliable, non-destructive, and […]

The increasing severity of climate change and glacial pace of emissions reform is requiring the development of new strategies for atmospheric CO2 drawdown. One of the approaches that has been gaining traction is Ocean Alkalinity Enhancement (OAE), a method that increases the physical absorption of atmospheric CO2 into the ocean by dispersing alkaline materials in […]

The rapidly increasing global use of cannabis and the increasing potency of ?9-tetrahydrocannabinol (?9-THC), the primary psychoactive component, necessitate rapid, sensitive, and portable detection methods for drug screening. Traditional chromatographic and spectroscopic techniques, while accurate, have limitations that hinder their use in point-of-care (POC) and real-life scenarios. Electrochemical sensors offer a promising alternative due to […]

The main objectives of the project are designing, developing, and integrating a high-resolution electromagnetic mapping instrument, with interchangeable sensor arrays or sensor suites for single-sided access, non-contact characterization of materials, by evaluating different electromagnetic properties (i.e., electric conductivity, magnetic permeability, dielectric constant) while using an intelligent modular architecture. Sustainability of new and improved manufacturing methods, […]

This project aims to enhance proficiency estimation in large-scale assessments by improving missing-data imputation techniques. Specifically, the study focuses on refining Multiple Imputation with Denoising Autoencoders (MIDAS)—a deep learning-based approach—by incorporating item response time as an additional contextual feature. Unlike traditional item response theory (IRT) or regression-based methods, which rely on strong assumptions, the proposed […]