The research project aims to explore rain droplet kinetic energy harvesting for advanced engineering applications in the emerging Internet of Things (IoT) technology. As the world increasingly seeks renewable energy sources and sustainable technologies, the concept of harvesting wasted energy forms from the environment gains significance. One promising avenue is reverse electrowetting on dielectric (REWOD), […]

L‘art asiatique et canadien connaissent un intérêt grandissant auprès des consommateurs et, malgré les sources variées, il est difficile d’acquérir une œuvre. Acquérir une œuvre en provenance d’Asie pour les Canadiens est complexe en raison de nombreuses barrières comme la langue, la crainte de fraude ou de contrefaçon. L’acheteur n’est pas en confiance. Il en […]

This project aims to explore the mechanical behaviors of ferroelectric polymers, focusing on P(VDF-TrFE), through atomic force microscopy (AFM) techniques. By investigating the frictional properties of P(VDF-TrFE) and similar materials using AFM-based methods such as transverse shear microscopy (TSM) and friction force microscopy (FFM), the project seeks to uncover the relationship between electrical polarization and […]

Ce projet vise à améliorer la participation sociale des enfants autistes et de leur famille en utilisant des activités de loisir immersives basées sur la réalité virtuelle (RV), en particulier dans un environnement de type CAVE. Actuellement, les enfants autistes rencontrent des obstacles à la participation sociale en raison de divers facteurs, tels que des […]

Most computers and materials work on scales such that quantum effects can be comfortably ignored. But as we aim to make computers ever smaller, quantum effects will cause difficulties; however, they also provide opportunities. Spin-crossover (SCO) materials are molecules that can “Flip” between two states: either high or low spin binary states, making them essentially […]

La prévision de la demande d’électricité à court terme est un des enjeux majeurs de l’exercice des activités d’Hydro-Québec. Cette tâche requiert de calibrer les paramètres de modèles de prévision complexes par rapport à un grand nombre de données. Or, un des systèmes de calibration utilisé quotidiennement éprouve des difficultés d’adaptation face à la nouvelle […]

This proposal is devoted to two areas of sheep production: animal health (parasitic infection) and feed efficiency, which both impact profitability and sustainability. We will investigate potential machine learning using biomarkers indicating parasite resistance and feed efficiency in differentiated animals early in life. One postdoctoral fellow (PDF) will use metabolomics, genomics, and machine learning to […]

Au cours des dernières années, la recherche en reconnaissance gestuelle a connu une forte effervescence, principalement appuyée sur la démocratisation de l’intelligence artificielle. Cependant, les approches actuelles rencontrent souvent des défis en termes de robustesse et demandent un grand effort de calibration. Pour remédier à ces limitations, ce projet propose d’employer la fusion de signaux […]

The proposed project aims to enhance the interpretability of machine learning models, particularly in the context of time series data analysis. By extending the capabilities of the tsfresh library, a widely used tool for time series feature extraction, the project seeks to make complex models more transparent and understandable. This effort will improve confidence in […]

Ultrafast electron diffraction (UED) is an established tool to record atomic motion on very short timescales well below one picosecond. The sample, typically less than 100 nanometers thick, is first excited with an optical pump-pulse leading to the rearrangement of its atomic or molecular constituents. Subsequently, the structural changes are probed by a short electron […]

This research project aims to significantly improve the way data are managed in a specific self-driving laboratory in the AUTODIAL group of Prof. Hattrick-Simpers at the University of Toronto, focusing on discovering new materials that are resistant to corrosion. This class of labs, known as Self-driving labs (SDL) or Materials Acceleration Platforms (MAPs), use advanced […]

The project between Plato Testing Inc. and NBCC has been built to support indigenous students of the software testing program to gain industry experience and utilize the skills they have developed in class. The software testing industry is ever growing, and requires talented students with an understanding of programming and software development to make software […]