Projets novateurs réalisés

Project Evaluation and Data Collection Support-Island FOod Network

The Island Food Network (IFN), based in Victoria County, Cape Breton, is one of the community partners delivering the province-wide Collaborative Food Network (CFN) program. Launched in April 2025, the CFN initiative supports community-led responses to food insecurity by promoting human dignity, choice, nutrition, adaptability, and efficiency in local food programs.

This project will evaluate IFN’s CFN programming during its first full year of implementation (April 2025 – March 2026). It will explore how IFN’s activities—such as food access initiatives, community meals, and outreach efforts—are helping to reduce food insecurity and build stronger social connections within the community. The project will collect both numbers and stories: how many people participated, how the programs were experienced, and whether they made participants feel included, respected, and supported.

A student intern will work closely with IFN staff and two academic supervisors from Cape Breton University to design and carry out the evaluation. This includes developing simple tools to document ongoing program activities, collecting feedback from participants, and analyzing the impact of the programming. The goal is to help IFN learn from its work, improve future programming, and meet provincial requirements for annual evaluation.

This is the first time the Island Food Network is participating in a formal evaluation of its CFN programming, but it builds on lessons learned from similar evaluations previously conducted in other Nova Scotia communities, including Glace Bay and Eskasoni.

Multimodal Sensing and Analytics for Remote Aquatic Ecosystem Monitoring

This project develops a unified multimodal sensory analytics framework to monitor remote aquatic ecosystems using video, sonar, and environmental sensors. By combining these complementary data sources, the system can operate continuously across a range of challenging conditions such as low visibility, night-time, or remote locations with limited infrastructure. The project is a collaboration between Simon Fraser University and the University of Hong Kong, advancing research in artificial intelligence of things (AIoT), edge computing, and environmental analytics. It supports student training, international knowledge exchange, and contributes to the development of scalable tools for fish monitoring, ecosystem assessment, and long-term environmental stewardship.

Strengthening Rigour in Mixed Methods Research

Mixed methods research—combining quantitative and qualitative approaches—has become increasingly important in psychology and the social sciences for addressing complex, real-world questions. However, there is no shared standard for defining and evaluating rigor across mixed methods studies. This project tackles that gap by conducting a Delphi study, an iterative method of gathering expert feedback to build consensus on best practices for rigor in psychological mixed methods research. Experts will evaluate proposed strategies, suggest new ones, and refine recommendations across multiple survey rounds, aiming to produce a coherent, community-informed framework.

Preliminary findings from a recent systematic review highlight why this work is urgently needed: although many researchers refer to concepts like “triangulation” or “reflexivity,” these are rarely defined or consistently applied, leading to methodological variability. The resulting framework from this project will offer researchers, educators, and policymakers practical, openly shared guidance for designing and evaluating rigorous mixed methods studies. By improving methodological clarity and transparency, this work will enhance the quality and credibility of mixed methods research, supporting evidence-based decision-making in areas like health, education, and social policy—both in Canada and globally.

A Scalable Nitrous Oxide (N2O) Emissions Predictor Utilizing Fuzzy Logic and Impulse Response Measurements

Nitrous oxide (N2O) is a powerful greenhouse gas with a global warming potential 298 times that of CO2, significantly contributing to climate change through agricultural activities, particularly the application of fertilizers. Accurate and scalable prediction of N2O emissions is essential for sustainable agriculture and climate mitigation. Current methods, such as LSTM-DLM neural networks proposed in previous MITACS projects, are computationally intensive, require extensive training data, and depend on costly equipment throughout the entire season (e.g., LICOR gas analyzers), which limits their practical application. This proposal outlines a scalable, cost-effective approach that combines fuzzy logic and impulse response measurements to rapidly and accurately predict N2O emissions across diverse agricultural landscapes.

Business Strategy Internship @ The forever Group

The Forever Group (TFG) is a 30-year-old Canadian owned and operated consumer-packaged-goods company that currently generates $2.5 million–$3 million in annual revenue across North America, the UK, Japan, and other export markets. To achieve its strategic goal of reaching $5 million–$10 million in the next three to five years, TFG must overcome the operational friction created by siloed legacy tools—AccountEdge for accounting, Shopify and Squarespace for e-commerce, Freightcom and ClickShip for logistics, Faire and Amazon FBA for wholesale and marketplace sales. These disconnected systems require heavy manual data entry, human errors, and inconsistent reporting, which in turn hinder timely, data-driven decisions. The business has loyal customer base, but it is unable to scale the business due to these hindrances which only increase cost of doing business with scale.

Toward a Volatile-Based Pest Management Strategy for the Lesser Clover Leaf Weevil

This project will support research on a pest insect called the lesser clover leaf weevil, which damages red clover seed crops and currently requires frequent insecticide use. The goal is to develop a safer and more targeted control method using natural scent cues that the insects rely on to find mates and food. To do this, I will spend two months at Murdoch University in Australia, working with experts to study the weevil’s sense of smell at the genetic level. By identifying the specific genes involved in detecting scent, we can better understand which natural compounds might be used to attract or confuse the pest. This will lay the foundation for designing traps that reduce the need for insecticides, protecting pollinators and other beneficial insects in the process. The research also supports international collaboration between the University of Saskatchewan and Murdoch University, while providing advanced training in molecular biology and bioinformatics. This work will contribute directly to my PhD, lead to a scientific publication, and help bring practical, environmentally friendly pest control solutions to Canadian agriculture.

Oxygen vs. Metabolites: investigating Mechanistic Drivers of Skeletal-Muscle Hypertrophy in Low-Load Hypoxic Resistance Training

Many athletes and patients use blood-flow-restriction (BFR) cuffs to make light-weight exercise feel like heavy training, but no one is sure why this type of exercise causes improvements similar to traditional exercise. Is it because the cuff blocks oxygen from entering the muscle, or because it traps byproducts (metabolites) that signal the muscle to grow? Our project will carefully tease apart these two ideas. We will have volunteers exercise in four conditions: (1) regular exercise with low weight, (2) low weight with inflated BFR cuffs (similar to a blood pressure cuff), (3) low weight while breathing low-oxygen air (like training at altitude), and (4) low weight with inflated BFR cuff and low-oxgen air together. We will match the amount of oxygen within the exercising muscle between the BFR and low-oxygen conditions, allowing us to see whether the lack of oxygen or metabolite build-up is the real driver of strength and size gains. The findings will help Delfi, a Canadian company that makes smart BFR devices, fine-tune their algorithms so users from rehab spaces to elite athletes get maximum benefit with minimal risk, strengthening Canada’s position in cutting-edge sports-medicine technology.

Exploration du rôle du complément dans la glomérulosclérose segmentaire et focale dans le syndrome néphrotique de l’enfant

Ce projet de recherche vise à mieux comprendre une maladie rénale fréquente chez les enfants, appelée syndrome néphrotique idiopathique (SNI). Cette maladie peut prendre deux formes principales, dont l’une (la HSF) est plus grave et répond mal aux traitements habituels. Aujourd’hui, il est très difficile de distinguer ces deux formes dès le début de la maladie, ce qui peut entraîner des traitements inutiles et des effets secondaires graves. Le stagiaire participera à une étude qui cherche à valider un marqueur présent dans les urines, appelé sC5b-9, qui pourrait permettre de différencier rapidement les deux formes de SNI. Ce biomarqueur pourrait éviter des biopsies douloureuses et aider les médecins à choisir le bon traitement plus tôt, ce qui améliorerait grandement la prise en charge des enfants atteints.

AI for Airplane Engine Inspection

This project aims to develop an AI-powered visual inspection system using image data from P&WC’s existing Computer Vision Inspection System (CVIS) to enhance aircraft engine assembly issue detection. By leveraging deep learning techniques, the proposed solution will address current limitations in accuracy and consistency, targeting a 100% visual detection rate for anomalies such as: part at wrong orientation, missing or extra component, and not-tospec installation. The model will be trained on historical CVIS images, validated against expert annotations, and integrated into a streamlined inspection workflow with human-in-the-loop capabilities for continuous improvement. This initiative will replace a less reliable visual inspection system currently used, reduce time and energy resources expended when out-of-spec parts are shipped by or require off-site repair, and establish a scalable foundation for future smart inspection technologies within aerospace manufacturing and maintenance environments.

Optimization and Expansion of Eventlinx

TicketWindow Inc. is a Canadian ticketing company providing digital event management solutions to promoters, venues, and organizations. Its new platform, EventLinx, is a comprehensive, cloud-based event management ecosystem that includes a promoter portal, patron website, mobile point-of-sale (POS) application, and administrative backend. The system is deployed via edge computing infrastructure using Cloudflare Workers and Pages, with real-time interactivity, Stripe payments, Supabase for authentication, and GitHub-based DevOps.

While the platform is functional and in active beta testing, TicketWindow faces challenges in elevating user interface (UI) consistency, responsiveness, and accessibility across multiple devices and user types (e.g., promoters, patrons, and mobile staff). Additionally, there is a pressing need to improve the platform’s user experience (UX) to support scale-up operations and increase adoption by larger venues and organizations. The current interfaces are based on rapid prototyping and beta-level UI decisions, and are not optimized for production-level user flow or visual coherence.

Stratégie climatique et réduction des émissions de GES en entreprise agroalimentaire

Le projet de recherche « Stratégie climatique et réduction des émissions de GES en entreprise agroalimentaire » vise à contribuer à la réduction de l’empreinte carbone des activités industrielles d’une grande entreprise de biofabrication alimentaire au Canada. Cette visée d’optimisation environnementale de processus de production industrielle vise à contribuer à la recherche de solutions à la lutte contre les changements climatiques sous l’angle d’un enjeu rencontré par plusieurs industries de tous les secteurs, quel que soit leur domaine d’activité.

Data Collection and Evaluation Support to Nova Scotia’s Collaborative Food Networks_Glace Bay Town House

Glace Bay Citizen’s Service League – Town House is addressing a critical issue that affects many communities: food insecurity. Although progress has been made through programs such as community meals, cooking classes, and a social supermarket, food insecurity is not only about access to food. It also relates to people’s dignity, health, and their sense of inclusion in the community. This evaluation project aims to better understand whether these programs are effectively addressing these broader needs. Are they reducing food insecurity in a meaningful way? Are they helping people feel more connected and respected?

The purpose of this evaluation is to assess the impact of Town House programs, identify areas for improvement, and provide recommendations for strengthening services over the long term. The project involves developing an evaluation plan, collecting and analyzing both qualitative and quantitative data, engaging with program participants, and producing insights that are grounded in evidence.

This initiative builds on a previous evaluation conducted for the period from April 1, 2024, to March 31, 2025. That evaluation, completed in collaboration with Town House, found that regular monitoring data was limited, making it difficult to assess program outcomes fully. Since the province—through its Collaborative Food Network funding—requires not-for-profit organizations to conduct annual evaluations, there is a need to strengthen data systems.

The current project is a continuation of this effort. Over the next six months, the intern will support Town House in organizing and documenting monitoring data, helping to ensure that the next evaluation is more evidence-based and useful for decision-making. This work will improve the quality of evaluation findings and support the organization in better meeting the needs of the community.