Projets novateurs réalisés

High-throughput Synthesis of Cu-based Electrocatalysts for Carbon Dioxide Reduction using Multimodal Robotic Platforms

Efficient and low-cost electrocatalysts are crucial for numerous industrial clean energy applications. However, the traditional catalyst discovery framework is constrained by the lengthy duration required for synthesizing and testing one single catalyst, as well as the human error introduced that compromises experimental repeatability. This project will redefine the catalyst development pattern by employing a streamlined, multimodal robotic platform for the high-throughput synthesis, screening and validating of a library of electrocatalyst in a matter of hours to a few days. Using the Carbon Dioxide Reduction Reaction to Ethanol production as a model reaction, we will focus on copper catalyst, leveraging the automated platform to systematically tailor element types and concentrations to achieve highly selective production of ethanol with a target selectivity > 80%. The successful outcomes of this study will provide Canadian institutions, organizations and companies with accelerated pathways to identify high-performance clean energy materials, significantly contributing to the goal of achieving net-zero carbon emissions by 2050 and strengthening its competitiveness in the critical clean energy sector.

Understanding and Improving Female Representation at Michelin Nova Scotia

Michelin North America (Canada) Inc. is interested in understanding the reasons behind the underrepresentation of women in its Nova Scotia manufacturing workforce. Female representation in its workforce remains disproportionately low at approximately 15%, compared to a gender balance rate of staff recruitment at approx. 36%. Despite Michelin’s reputation for competitive wages, benefits, and career development, female applicant rates remain low. This study aims to uncover the root causes and barriers—cultural, geographic, educational, perceptual, and operational—that may deter women from pursuing careers in manufacturing.

Improving Agricultural Supply Chains Through Rail-Based Transportation: A Comparative Study of Canada and Sri Lanka

This joint research project between the University of Manitoba and SLIIT Sri Lanka will explore how rail transportation can help improve agricultural supply chains in both countries. By comparing grain logistics in Canada with paddy and other crop supply chains in Sri Lanka, the project will identify practical, low-cost ways to reduce transportation costs, support rural communities, and improve farmers’ access to markets. Students and researchers from both institutions will work together using basic data analysis, case studies, and mapping tools to study transportation options, including rail. This collaboration will strengthen international research ties, create opportunities for student training and exchange, and support shared learning on sustainable and efficient agricultural logistics.

Efficacy and Safety of Nanobody-Based Interventions Targeting Amyloid-ß and Tau aggregates in Alzheimer’s Disease: A Systematic Review

This project, conducted in collaboration with TÉLUQ University, aims to systematically review and evaluate the efficacy and safety of emerging nanobody-based therapies designed to target amyloid-ß and tau aggregates—the two hallmark proteins implicated in the development and progression of Alzheimer’s disease. Nanobodies, due to their small size, high stability, and strong binding specificity, represent a promising new class of therapeutic agents capable of penetrating brain tissue more effectively than conventional antibodies. By synthesizing findings from existing preclinical and clinical studies, this review will assess how these innovative interventions perform in reducing pathological protein accumulation, improving cognitive outcomes, and minimizing adverse effects. The project will also identify current research gaps, methodological limitations, and future opportunities to support the advancement of nanobody-based therapies as a potentially transformative approach for Alzheimer’s treatment.

Neuroinflammatory and Neuroimmune Mechanisms Linking Migraine and Multiple Sclerosis: A Systematic Review of Human and Animal Studies

This project will examine the connections between migraine and multiple sclerosis (MS), two common neurological conditions that affect millions of people worldwide. While migraine causes severe headaches and MS can lead to long-term physical and cognitive challenges, research suggests that these conditions may share underlying immune and inflammatory mechanisms. By systematically reviewing existing human and animal studies, this project aims to identify overlapping pathways or potential biomarkers that help explain why migraine is more common in people with MS. The results will provide valuable insights into shared disease mechanisms, guide future research, and potentially inform new therapeutic approaches. Participating institutions will benefit from this collaboration by strengthening international research ties, combining expertise in neuroscience and immunology, and producing a high-quality, organized resource that can support further studies and clinical applications in the field.

Learning Optimal Wildfire Evacuation Routes for Flin Flon 2025 Wildfire Case Study

This project develops a dynamic, self-learning wildfire evacuation routing system designed to improve public safety during fast-moving wildfire events. Traditional routing methods can identify effective paths but often fail to adapt quickly to rapidly changing fire behaviour and real-world driver responses. To address these limitations, the project introduces a Deep Reinforcement Learning (RL) framework in which an intelligent agent continuously learns and updates optimal evacuation routes within a simulated environment.
The 2025 Flin Flon wildfire, spanning Saskatchewan and Manitoba, serves as the primary case study. This incident provides a complex, cross-border dataset reflecting real traffic conditions, fire progression, and environmental impacts. Using Esri’s ArcGIS Pro and ArcGIS API for Python, the project will construct a high-fidelity simulation environment where the RL agent balances evacuation time with safety considerations such as fire proximity and smoke density. High-resolution GPS trajectory data will be incorporated to better understand evacuee movement patterns and improve model realism.
The final system will be delivered through an interactive ArcGIS Experience Builder interface and ArcGIS Dashboard, enabling emergency managers to access real-time, AI-optimized route guidance. This research advances GeoAI and demonstrates how Esri technologies and RL can transform wildfire evacuation planning across Canada.

From Constraints to Inclusion: Identifying Leisure Barriers in Accessible Tourism in Canada Using Text Mining of Hotel Online Reviews

The project aims to improve the travel experience for people with accessibility needs by identifying and analysing the leisure constraints faced by travellers with disabilities in Canadian tourism. Using user-generated content from Tripadvisor hotel reviews, the study will focus on four- and five-star hotels in Toronto, an advanced tourism hub and policy leader under the Accessible Canada Act, where accessibility is both expected and publicly promoted. Using text mining and machine learning techniques, the review data will be classified to uncover accessibility-related barriers, with particular attention to structural, interpersonal, and intrapersonal constraints.

By identifying recurring accessibility barriers and examining how advertised accessibility features align with guest experiences, the project will generate insights to support more inclusive tourism services. The expected outcome is an analytical framework and practical recommendations to help Destination Marketing Organisations (DMOs), hotel operators, and policymakers strengthen accessibility standards and enhance the inclusion of travellers with disabilities. Beyond its applied impact, the project also contributes to international research collaboration. Mount Saint Vincent University (Canada) and the Federal University of Paraná (Brazil) will benefit from strengthened academic exchange, capacity-building in computational social science, and shared advancement of accessible tourism research.

Development of an Established Protocol for 3D scanning for Capture of Residual Limb Shape in Fitting of Prosthetic Sockets

There is a lack of an established protocol for the use of 3D scanning for capturing the residual limb shape in prosthetics and orthotics daily clinical practice. A lack of consistency in scanning procedures, scanner choice, and shape of artefact in current studies presents a need for standardization of protocols and a benchmark for measuring scanner performance. The aim of this work is to establish a protocol for determining acceptable scanners for shape capture in prosthetics and orthotics clinics.

A Feasibility Study on Soil Suitability and Safe Urban Farming in the Town of The Blue Mountains

This project will study whether soil in the Town of The Blue Mountains is safe and suitable for urban and community farming. The Town has a long history of farming, particularly in apple production, where older agricultural practices may have left behind small amounts of chemicals or metals in the soil. With growing interest among residents in growing fruits and vegetables at home or in community gardens, it is essential to understand where the soil is clean and healthy for food production.

Using historical maps, satellite images, and modern mapping tools, the research will identify areas that are likely safe for farming and others that may need further testing. The results will help the Town of The Blue Mountains make informed decisions about land use and guide residents in starting safe and sustainable gardens. This work will also help the Town strengthen local food security and promote environmentally friendly urban farming practices.

Fear-avoidance, function, and infrared thermography in injured professional football players

Chronic pain is one of the most common and debilitating conditions worldwide, placing a significant burden on healthcare systems. (1) In musculoskeletal injury rehabilitation, fear-avoidance beliefs—where athletes avoid movement due to fear of pain or reinjury—are strongly associated with greater pain, reduced function, and prolonged recovery. (2) Yet, this psychosocial dimension has yet to be correlated with tissue pathology using imaging. In addition, psychosocial constructs like fear avoidance are often overlooked in CFL rehabilitation protocols, where the focus remains primarily on tissue pathology healing rather than the athlete’s psychological response to injury. There is a clear disconnect between lesion site damage and the resulting pain experience. Despite this, no studies to date have examined the relationship between imaging of the lesion site using infrared thermography and pain-related fear measures, leaving a critical gap in our understanding of how physiological and psychosocial factors interact throughout recovery. Infrared thermography is an eco-responsible, non-invasive, non-radiating, and low-cost imaging tool capable of detecting temperature changes related to inflammation and blood flow in injuries. Integrating infrared thermography with psychosocial screening could provide a more comprehensive and efficient approach to monitoring musculoskeletal recovery, aligning with both performance and player goals.

Smart Management of Hospital Blood Bank Operations: Optimizing Units, Donors, and Stock

This Mitacs project aims to transform hospital blood bank operations into a predictive, efficient, and data-driven system using ten years of real hospital data. Traditional blood bank systems lack analytical and forecasting capabilities, leading to shortages, overstocking, and wastage. The project will develop an end-to-end AI framework that forecasts blood demand, optimizes inventory, detects shortages early, and supports decision-making through an interactive dashboard. By integrating time-series forecasting, deep learning, optimization models, anomaly detection, and rigorous model validation, the project seeks to minimize wastage, prevent stockouts, and enhance clinical reliability. Beyond improving local hospital operations, the research will generate generalizable methodologies and academic contributions that can benefit blood banks in Canada and internationally.

Empowering Neurodivergent Readers: The Role of AI-Personalized Stories in Supporting Literacy Development

This project will examine whether personalized, AI-generated stories in the StoryMii app can help children who have both ADHD and reading difficulties learn new words, comprehend stories, and stay engaged with reading. Children with these challenges often have trouble sustaining attention and decoding letters, so generic texts often cannot keep them engaged long enough to support learning. Personalized stories and multimedia supports, such as listening while reading, have been shown to help many children, but it is still unclear whether these benefits extend to children with both attention and reading difficulties. Over six months, the Mitacs intern will work with Western University and MiiApps, the company behind StoryMii, which creates custom AI-generated storybooks from user prompts. The intern will run an experiment testing whether personalization in StoryMii improves short-term word learning and story comprehension, and will also analyze anonymized data from roughly 16,000 StoryMii users to evaluate long-term reading engagement. The findings will provide MiiApps with its first scientific evidence on how well StoryMii supports neurodivergent learners, helping guide product design and strengthening its value for families, educators, and clinicians, while advancing research on children’s reading development.