This research project focuses on understanding how ringed seals communicate during haul-out events in the Northwest Territories. Ringed seals are vital to Arctic ecosystems but face threats from climate change and increased shipping. By analyzing acoustic and photo data provided by our partner organization, we aim to discover if these seals change their vocalizations when […]

The decline of Pacific salmon on the south and central coast of British Columbia has resulted in well-recognized economic, ecological, and cultural impacts. Numerous factors are considered to have contributed, including marine conditions, climate change, and changes to freshwater habitats. Forest harvesting is often considered to have altered freshwater habitats where salmon spawn and rear […]

This project aims to develop, evaluate, and apply advanced solutions and techniques for assisting industrial plant operators in decision-making during abnormal situations, thereby improving plant safety and reliability. Currently, plant operators receive too many alarms, making it difficult to respond effectively. In industrial facilities, developing strategies for sustainable Environmental, Health, and Safety (EH&S) performance and […]

Smart or intelligent classrooms utilize advanced interactive technologies to support instructors and learners in a hybrid learning environment. However, effectively integrating these technologies with the instructors’ curriculum and aligning them with students’ needs remains a challenge. Distinct from typical hybrid learning platforms, X2O’s OneRoom is designed to preserve the learning experiences of online students and […]

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La prévision de la charge, ou de la demande électrique, est une activité fondamentale pour les utilités électriques et en particulier pour Hydro-Québec. Dans un contexte opérationnel, elle vise à prévoir sur un horizon de temps relativement court, typiquement 24 ou 48 heures la quantité d’électricité qui sera consommée par un ensemble de clients donnés. […]

This research project addresses a common problem in studying medical data: understanding the true effects of different treatments when the data is not from a controlled experiment. Specifically, we are looking at patients with systemic lupus erythematosus (SLE) and the number of infections they get. Often, traditional methods need special, hard-to-find data to ensure accurate […]

This proposal aims to revolutionize the process of virtual home staging by using advanced technology called Generative Artificial Intelligence (GenAI). Traditional staging, which involves professionals arranging furniture and decorations in a home to make it more attractive to buyers, can be expensive and time-consuming. By harnessing GenAI, we can speed up this process and reduce […]

Violacein is a molecule naturally produced in some bacteria such as Chromobacterium violaceum. It has been shown that violacein has promising antibiotic, anti-tumor proliferation, anti-leishmanial and anti-fungal properties. Violacein is commercially available. However, it is very expensive. The objective of this proposed research study is to measure the effects of violacein produced by Escherichia coli […]

The following proposal aims to research and develop Net Zero Carbon sustainable design strategies for a chalet, serving as a pioneering study to inform broader net-zero carbon residential developments in Montreal. It is motivated by Canada’s goal of achieving net-zero greenhouse gas emissions by 2050. One intern will work with PLAPROS INC., under the supervision […]

Currently, embryo implantation success rates in in vitro fertilization (IVF) are low, partly due to subjective and invasive tests. An assay that can quantify embryo potential while preserving its integrity is necessary. Small RNA sequences, microRNAs (miRNAs), are promising, quantifiable, and non-intrusive markers of developmental potential in embryos. Due to ethical concerns with human embryos […]

The proposed research project aims to develop accurate and user-friendly models to forecast daily streamflow for the Oldman River in Alberta. This project will involve using advanced machine learning methods, such as Artificial Neural Networks (ANNs), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM), to improve the reliability of streamflow predictions. By enhancing the […]