Projets novateurs réalisés

Stratégies de diversification économique et d’innovation pour la MRC des Laurentides

Ce projet vise à dresser un portrait approfondi de l’économie locale de la MRC des Laurentides en s’appuyant sur des données statistiques, des cartes interactives et des analyses territoriales. Il inclura également des comparaisons entre territoires et des analyses de différentes stratégies d’attractivité.
L’objectif est de comprendre comment se structure aujourd’hui l’économie du territoire, d’identifier les secteurs les plus dynamiques ou en émergence, de situer les entreprises dans l’espace, et de mieux saisir les forces naturelles et humaines du milieu. Cette compréhension permettra de dégager de nouvelles opportunités de diversification économique pour les prochaines années. Certaines pistes sont déjà envisagées et feront l’objet d’analyses plus poussées, notamment l’agroalimentaire et les sports de plein air.
Concrètement, le projet permettra de cartographier les activités économiques du territoire, de repérer les secteurs en croissance ou en transformation et de mettre en lumière les interactions entre les différents pôles économiques (nature, tourisme, plein air, bioalimentaire, économie sociale, etc.). En parallèle, il analysera l’influence des régions voisines, particulièrement celle de Montréal, ainsi que les externalités positives et négatives qu’elles génèrent. Le projet portera aussi une attention particulière à l’innovation, aux besoins des entreprises en matière de main-d’œuvre, de formation et d’infrastructures.
À partir de ces analyses, le projet proposera des stratégies concrètes pour aider la CDE à
renforcer l’attractivité du territoire pour les entreprises et les talents ;
soutenir l’innovation et l’économie du savoir ;
valoriser les ressources locales et les secteurs d’avenir ;
diversifier l’économie afin de la rendre plus résiliente et durable.

Preliminary Assessment of HOCl Electrolyzer Design Strategies for Field-Deployable Systems

This project addresses the challenge of designing compact, field-deployable electrolyzer systems for producing hypochlorous acid (HOCl), a safe and effective antimicrobial agent with growing relevance in wound care, humanitarian response, and combat casualty care. Despite HOCl’s broad-spectrum efficacy and favorable safety profile, current production systems are bulky, proprietary, and poorly suited to decentralized use.
The research will explore candidate technologies to guide the development of a modular, energy-efficient HOCl generator tailored to real-world deployment needs. Lab-scale evaluation will focus on identifying viable performance envelopes, assessing adaptability of existing electrolyzer designs, and defining pathways for integration into decentralized formats.
The anticipated benefits are both social and economic. The project contributes to innovation in health-related clean technologies, supports the training of skilled talent in electrochemical engineering, and strengthens Canada’s capacity to deliver scalable, locally manufactured solutions for infection control and emergency response. By advancing practical HOCl generation systems, the initiative aims to improve access to safe antimicrobial tools across dual use contexts, particularly in remote, under-resourced, or conflict-affected settings

Superposition of Spacetime

The aim of this project is to study and develop the formalism of spacetime superposition. The focus will be to understand the behaviour of simple quantum systems in the vicinity of black hole horizons. In this physical scenario, both quantum theory and general relativity remain valid, but the question of what happens cannot be answered by either of them on their own. The project is an extension of the long lasting collaboration between Prof. Mann and Prof. Kubiznák, which will establish the foundations for further research of this novel approach in Prague and reinforce its development in Waterloo.

Amélioration de la classification des arbres tropicaux à partir d’images prises par drone grâce à la fusion d’entrées multimodales

Les forêts tropicales sont de plus en plus menacées par la déforestation, les incendies et les perturbations climatiques. Afin de surveiller la biodiversité et de prévoir les tendances spécifiques à chaque espèce, les chercheurs ont commencé à utiliser des technologies aériennes sans pilote (i.e. drones) pour identifier les espèces et cartographier la forêt. Cependant, les modèles de vision par ordinateur ont du mal à classer les espèces d’arbres tropicaux à partir d’images par drone en raison du grand nombre d’espèces, de l’imagerie haute résolution limitée et de la distribution à longue traîne des données disponibles. Nous proposons de développer un modèle qui exploite différents types de données, à savoir des descriptions textuelles, le rang taxonomique et des images haute résolution telles que des images zoomées prises par drone, afin d’aider à identifier les espèces, en mettant l’accent sur l’amélioration de l’identification des espèces sous-représentées. En utilisant différents types de données, notre approche vise à relever les défis liés à l’identification des espèces lorsque les données sont rares ou que les espèces se ressemblent, et à soutenir à terme une surveillance évolutive et fiable des forêts tropicales au niveau des espèces.

Mic’d Up Iteration and Chatter Development

At Elements Athletics, we’re using technology to make sports safer and more enjoyable for everyone. Our flagship tool, Mic’d Up, uses artificial intelligence to analyze referee audio from games, detecting verbal abuse and helping sports organizations enforce their conduct policies.

Through this Mitacs project, we’ll improve our internal annotation dashboard to streamline audio review and training process. We’ll also launch a new feedback feature, Chatter, which provides referees with insights on tone, clarity, and communication—turning our abuse detection tool into a coaching resource.

Together, these innovations will strengthen referee retention, enhance the player and coach experience, and improve safety across youth and amateur sports. This project also offers valuable hands-on learning for students in AI, software development, and sport technology—helping develop the next generation of Canadian innovators in sport and data-driven innovation.

Chemical reaction mechanisms with eXplainable Machine Learning

Deep learning systems can predict properties of chemical substances but do so in a purely mathematical way. As a consequence, the user does not get any feedback on what are the essential properties a chemical must have to exhibit a certain property. This hampers getting any insight in to the relationship between molecular structure and the properties. In this project, the aim is to transform mathematical vectors that result from deep learning back to molecular properties that chemists understand and can use to their benefit to develop new molecules.

Deep Breathe Software Developer- Mobile

This project will contribute to the design and building of the systems behind our clinical-facing applications for automated point-of-care ultrasound interpretation. Working closely with our product, AI, and regulatory teams, the project focuses on building real-time respiratory imaging tools that bring immediate diagnostic answers to patients — whether at the bedside, in the back of an ambulance, or on the battlefield. Centered on Android app development, this project aims to expand the reach of our diagnostic platform, enabling access to a wider range of users and environments. The project demands innovative thinking, curiosity, and the ability to develop reliable solutions that perform under constrained computational environments, ultimately advancing the application development for how and where critical diagnostics are delivered.

Feasibility Assessment of Treatment Wetlands for Northern Riverbank Stabilization: An Exploratory Hydrodynamic Study of the Nechako River

The Nechako River in Prince George, British Columbia, suffers from eroding riverbanks and contaminated sediments left behind by past industrial activities. This project will investigate whether treatment wetlands, which are engineered ecosystems that use plants and natural processes to clean water and stabilize soil, could help address both problems at once. The student will use computer modeling software to study how water flows along the riverbanks and identify locations where treatment wetlands might work well. The project includes dedicated training on cold-climate treatment wetlands, allowing the student to gain leading-edge knowledge in an emerging field critical to Canada and other northern regions. For Canada, this research advances the development of low-cost, nature-based water infrastructure suited to northern communities, many of which face combined challenges of aging systems, legacy contamination, and limited resources for conventional engineering solutions. For UNBC, this work provides the initial site assessment needed before designing a pilot wetland system, directly supporting the university’s ongoing research on cold-climate water treatment. For Tecnológico de Monterrey, the collaboration extends their river modeling expertise into northern environments and establishes a partnership that can lead to future student exchanges and joint research projects between the two institutions.

Entrepôt inter-organisationnel de mutualisation de données

Lorsque vient le temps de concevoir des stratégies pour supporter l’innovation au Québec, le Conseil de l’innovation du Québec (CIQ) fait face à un défi important: les données relatives à la performance des différentes aides publiques sont dispersées à travers l’ensemble des organisations chargées d’administrer les aides financières ou les services.

Pour répondre à cet enjeu, le CIQ pilote une initiative de mutualisation de données, en partenariat avec plusieurs organisations partenaires.
Or, la mutualisation des données amène plusieurs grandes questions, notamment en lien avec la valeur stratégique et la gestion éthique des données.

Le projet consiste donc à concevoir et déployer une architecture infonuagique permettant de soutenir l’effort de mutualisation de données, en tenant compte des différents enjeux de gouvernance de la donnée et ce, sur la base de recommandations d’un comité d’experts.

Training for Transformation: An Initiative to Embed Climate Resilience in Engineering and Infrastructure Practices

This internship project supports the development of a global training initiative led by the Climate Risk Institute (CRI) in partnership with the World Federation of Engineering Organizations (WFEO), aimed at enhancing engineering and infrastructure climate resilience worldwide. Over a four-month period, the intern will contribute to the design and development of training materials across three key phases of the program: strategic planning, creation of a foundational asynchronous course, and the global adaptation of existing professional resilience courses. The intern will engage in research, content drafting, and instructional design, producing key deliverables such as course syllabi, draft modules, case studies, and training support materials. This work will directly support CRI and WFEO’s goal of advancing climate adaptation capacity within the engineering community. The project will also link training resources, efforts, and participants through a new, AI-enabled digital platform called CanAdapt. At the heart of CanAdapt is a growing ecosystem of practitioner networks—communities of practice that bring together professionals working on climate adaptation and resilience in areas such as infrastructure, forestry, mining, and energy. By tying these networks to CanAdapt’s course and program portal and using AI to help define learning pathways for shared interests among individual members of the networks, CanAdapt will become an adaptation accelerator. It will enhance knowledge systems, practitioner collaboration, and access to resources, all to support work and specific projects on climate and low-carbon resilience. The internship offers a unique opportunity for the intern to gain hands-on experience in international climate resilience training development while providing the partner organizations with dedicated support to accelerate content creation, course design, enhance global relevance, and strengthen the foundation for broad program implementation.

Staffworks Submission

Project Overview: Recruitment Workflow Innovation at Staffworks

About Staffworks
Staffworks is a Toronto-based staffing firm with 25 years of experience helping businesses stay agile and competitive through strategic recruitment services.

The Challenge
Recruiters face increasing administrative workloads—posting jobs across multiple platforms, managing large applicant volumes, screening candidates, coordinating interviews, and updating databases. These repetitive tasks consume significant time and limit the team’s ability to focus on high-value activities like engaging top talent and strengthening client relationships.

The Innovation Priority
Staffworks aims to redesign and streamline recruitment workflows using technology. This initiative is not about doing the same tasks faster; it’s about creating new, technology-enabled processes, testing automation tools, and implementing evidence-based improvements that transform how recruitment operates. These innovations require dedicated research, prototyping, and evaluation beyond normal business operations.

The Project
To achieve this, Staffworks is launching a Recruitment Assistant Internship focused on process analysis, automation techniques, and digital tools for routine recruiting functions. The goal is to reduce manual effort, accelerate service delivery, and improve candidate and client experiences. By minimizing administrative burden, Staffworks will enhance productivity, speed up response times, and strengthen its competitive edge—supporting long-term growth.

AI-Powered Fish Monitoring: Supporting Indigenous-led Conservation in Deadman Watershed

Secwépemc Fisheries Commission (SFC) currently relies on a semi-automated system that requires biologists and technicians to manually review video footage to confirm fish counts. This process is time-consuming, delays reporting, and limits access to real-time information. The interns will develop an automated fish-counting tool that uses computer vision and artificial intelligence (YOLOv2 object detection, ByteTracker, and custom counting logic) to detect and count salmon in the Deadman Watershed, part of the traditional territory of the Skeetchestn Indian Band. By integrating the resulting dashboard into the existing infrastructure, the system will reduce the manual validation and free up staff resources to focus on higher-value conservation work. Beyond operational efficiency and technical product development, this project also strengthens Indigenous-led monitoring efforts and builds the foundation for long-term collaborative relationships between Indigenous communities and TRU.