This project focuses on creating a smart, efficient energy management system for local communities powered by solar panels and batteries. By using advanced reinforcement learning (RL) techniques, the system will automatically control energy use, storing excess solar power in batteries to reduce costs and keep the grid stable. This approach helps communities rely more on […]

Antimicrobial resistant infections are a burgeoning threat to humankind. Unfortunately, antimicrobial resistance (AMR) programs have traditionally focused on bacteria and excluded fungi, which are now considered critical priority pathogens. Candida albicans, a commensal in many sites in the human body, can become pathogenic in immunocompromised patients. It is resistant to almost all classes of clinically-available […]

The mining sector plays a significant role in GHG emissions, contributing to climate change and environmental degradation. This proposal aims to investigate specific emissions associated with mining activities and evaluate the potential of zeolite membrane direct capture technologies as a viable solution for emission reduction. By addressing gaps in the current literature regarding the application […]

Wildland fires in Canada pose significant risks, causing extensive damage to ecosystems, property, and human life. The record-breaking 2023 wildfire season, which devastated 18 million hectares, underscores the urgent need for improved detection and mitigation strategies. Recent advancements in deep learning have demonstrated strong potential in early wildfire detection and fire spread prediction, providing critical […]

This project aims to improve solar energy conversion technology by exploring the self-assembly of cesium lead halide perovskite supercrystals (CsPbX3 SCs). These supercrystals have unique structural and photophysical properties that can be leveraged to make solar cells (and other optoelectronic devices) more efficient and longer-lasting. The project will focus on gaining a fundamental knowledge on […]

This project aims to study how organic carbon (OC) is preserved in marine sediments in the St. Lawrence Estuary and Gulf, a unique natural environment with a range of different conditions. By examining the way OC interacts with minerals in sediments, the research will help us understand how carbon can be stored long-term, rather than […]

This study seeks to conduct a comprehensive analysis to investigate the optimum process parameters for generating green hydrogen from waste materials (cocoa pod husk, rice husk, coconut husk, sawdust, etc.) and to assess the economic viability of the process. The use of the selected biomass as feedstock would provide a clearer scientific understanding of green […]

This projects aims to evaluate the corrosion rate of carbon steel in a 2:2 molar ratio (4M total molar concentration) of AMP: 1-(2-HE) PRLD environment as a function of absorber/desorber temperature, O2 concentration in the flue gas, and CO2 loading. This evaluation is to ensure that this novel amine blend can be used reliably with […]

This research sheds light on the mysterious force of dark energy, driving the universe’s accelerated expansion, and reveals how cosmic structures evolve. Since hydrogen makes up most of the universe, its natural radiation at radio wavelengths allows us to map large volumes of space and track the distribution of matter. The Hydrogen Intensity and Real-time […]

The aim of this research internship is to contribute to our group’s research program using laser­ cooled gases to explore fundamental phenomena of quantum materials and to use them to realize new quantum sensors. This research program has two main objectives – the use of ultra-cold atomic and molecular gases to (1) realize new quantum […]

Le cancer représente un défi majeur pour la santé mondiale avec des millions de nouveaux cas chaque année. L’intelligence artificielle (IA), notamment l’apprentissage profond, a amélioré la détection des tumeurs, mais transformer les grandes quantités de données médicales en informations cliniquement exploitables reste difficile. L’informatique quantique émerge comme une technologie prometteuse, notamment via l’apprentissage automatique […]

Research Internship with interdisciplinary artist and Associate Professor Hannah Heilmann at the Royal Danish Academy of Fine Arts, Copenhagen. The work will seek to build the intern’s capacity to create public-facing artistic research with Heilmann, an established expert, on concepts related to feminist embodiment, ecology, affect, and performance.