Controlled Self-Injection Techniques for Enhanced Laser Dynamics in Silicon Photonic Systems

The growing demand for high-performance computing (HPC), artificial intelligence (AI), and cloud applications is pushing traditional semiconductor technologies to their limits. This project advances silicon photonics, which uses light for faster, more efficient, and scalable data transmission, making it critical for next-generation computing and communication systems. Focusing on hybrid quantum light sources and nonlinear optical […]

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ÉTUDE COMPARATIVE DU COUPLAGE DE COLLECTEURS SOLAIRES AVEC UNE THERMOPOMPE

Près de 98 % de l’énergie électrique québécoise provient de l’hydro-électricité, une source d’énergie propre et renouvelable. Il apparaît donc important d’utiliser au mieux cette énergie. Dans cette optique, le Québec devrait favoriser l’utilisation de pompes à chaleur qui possèdent des performances supérieures à celles des plinthes électriques. Leurs performances sont toutefois affectées à mesure […]

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Intelligent Data Framework for Crane Safety: Learning from Past Incidents to Predict Future Risks

Cranes are essential equipment in construction sites lifting and moving heavy loads. Due to the large structure, accidents can lead to significant casualties and property damage. Studies shows crane accidents are due to human error and miscommunication, and identifying the person responsible is important for preventing future accidents. A large number of reports are generated […]

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Contrôle d’un ergocycle à bras couplé à une stimulation électrique fonctionnelle

Le projet de recherche Ergocycle S2M vise à créer une version embarquée de l’Ergocycle S2M, un dispositif destiné à la rééducation des personnes à mobilité réduite. Ce système inclut un vélo à bras instrumenté et utilise la stimulation électrique fonctionnelle, qui envoie des impulsions électriques pour activer les muscles paralysés ou faibles, facilitant ainsi le […]

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Visualizing the Performance of Scientific Applications Executing with Space-Time Domain Decomposition

Today’s high performance computers offer the possibility of computing complex large scale computational fluid dynamics (CFD) simulations in a reasonable time. In practice, exploting the thousands of computing cores to achieve the desired solution time is very challenging. These challenges include finding enough work to keep all these cores busy, and assigning work to different […]

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Développement d’un Modèle d’Analyse Automatique des Angiographies Coronaires pour la Génération de Rapports Cliniques

L’objectif de cette recherche est de développer un modèle capable d’analyser automatiquement les vidéos d’angiographies coronaires pour générer un rapport textuel contenant la gravité des sténoses ainsi que la fonction du ventricule gauche et du ventricule droit (VG / VD). Ce modèle repose sur l’intégration d’un encodeur vidéo pour extraire des caractéristiques spatio-temporelles, un tokenizer […]

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Digital twinning opportunity for circular economy in construction

This study aims to examine the use of Building Information Modelling (BIM) and 3D scanning technologies in the design, construction and deconstruction phases of the circular economy. Additionally, it seeks to identify the limitations and gaps in existing research. To this aim, the study first analyses the use of BIM in the design phase of […]

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L2M – Optimizing Energy Efficiency in Sea Transportation Using Machine Learning

Our project tackles the critical challenge of optimizing energy efficiency in electric boats, a vital issue in the growing market of sustainable marine transportation. The primary problem lies in the inefficient energy consumption of electric motors used in electric boats when navigating varying wave conditions, leading to reduced range and increased operational costs. This research […]

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L2M – MicroTrap

Microplastics, plastic particles smaller than 5 millimeters, are observed to have significant negative impacts on human health and the environment as they decompose extremely slowly, release toxic chemicals, and transport contaminants. Among the major sources of microplastics are microfibers, tiny thread-like fibers released during laundry. In Canada and the United States, 878 tonnes of these […]

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L2M – Deep Learning-Based Detection and Classification of Biofouling on Marine Surfaces

The maritime industry faces significant challenges from biofouling—the buildup of marine organisms on vessel hulls—which leads to higher fuel costs, increased carbon emissions, and frequent maintenance. Traditionally, biofouling inspections are manual, costly, and time-consuming, offering limited real-time insights. Our project seeks to address these inefficiencies by developing an AI-powered model to automate the detection and […]

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