L2M – Combined Gamma Probe and Ultrasound Imaging System for Cancer Surgery

Breast cancer is the leading cause of cancer among women, with over 30,000 new cases diagnosed across Canada every year. Most patients undergo breast conserving surgery to remove the tumour, but in over 20% of cases, some of the cancerous tissue is missed, requiring the patient to have a second surgery. We are currently developing […]

Read More
L2M – Market Assessment to Support the Commercialization of an Innovative Structural Thermal Break

Thermal bridging is a significant challenge in building design, increasing heat loss, raising energy demand, and reducing occupant comfort. As awareness of its impact grows, Canadian building standards are evolving to mandate more sustainable and energy-efficient construction practices. However, existing solutions for mitigating thermal bridging, particularly in balconies, are often ineffective, difficult to install, or […]

Read More
Trend Emergence and Evolution Prospection using Machine Learning in Fully Developed Insurance Claims

This Mitacs Business Strategy Internship project unites Intact Insurance’s extensive insurance data and industry expertise with Western University’s Banking Analytics Lab’s advanced skills in deep learning, actuarial science, and data analysis. The project’s goal is to build an unsupervised deep learning model for detecting significant changes in claim patterns, surpassing the limitations of traditional change-point […]

Read More
Greenhouse gas emissions monitoring and remediation approaches during wastewater treatment using partial denitrification anammox process

Wastewater treatment plants contribute to greenhouse gas emissions through the release of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), which are produced during various treatment processes. During biological nutrient removal in wastewater treatment, processes such as activated sludge can generate N2O (a potent greenhouse gas) during total nitrogen removal processes. Further energy consumption […]

Read More
Developing a Brand Health Framework for Canadian Post-Secondary Institutions

The proposed project is to develop a unique brand health framework and measurement tools for the Canadian higher education marketplace to help Canadian post-secondary institutions more accurately and effectively assess the effectiveness of their branding and marketing efforts. This project will benefit the partner organization by providing a more accurate client brand assessment tool than […]

Read More
N2SOLVE: A Canadian/French Coordination Chemistry Partnership for Climate Change Solutions

N2SOLVE OVERVIEW: This research pairing between France and Canadian researchers will develop new functional molecules: ligands, transition metal, and main group compounds that promote the equitable use of resources, specifically with regard to the global nitrogen cycle. To ensure the well-being of future generations, innovative approaches that engage sustainable practice must be adopted. With an […]

Read More
Biocontrol in large-scale cricket rearing facility

Aspire Food Group is the largest commercial cricket rearing facility in the world and has recently encountered a significant presence of mites in their facility. The main objectives of this research will utilize the taxonomic and biocontrol expertise to: 1) identify the mite species present in the Aspire facilities, 2) make recommendations based on identifications […]

Read More
Automated fault detection in commercial refrigeration systems

A refrigerant leak is one of the major contributors of commercial refrigeration unexpected breakdowns. Conventional methods of leak detection using physical sensors are expensive, have limited capability of square footage coverage, and incapable of detecting slow and progressive refrigerant leaks. Accordingly, the development of a smart leak detection system without the need to include additional […]

Read More
Machine Learning-Based Modeling of Spreading Dynamics in Complex Interfacial Systems

Understanding droplet interactions with surfaces is crucial for large-scale oil recovery, coating industries, and microfluidic devices. To address the remaining challenges, including the need for a universal timescale and improved theoretical and computational models, this project brings together the SoftSimu group at Western University and the Soft Materials Modelling (SMM) group at Aalto University, Finland. […]

Read More