Projets novateurs réalisés

Comparative Life Cycle Assessment and Uncertainty Evaluation of Seaweed-Based Biofertilizer Pathways for Climate-Smart Agriculture

The proposed project will compare different ways of turning seaweed into eco-friendly fertilizers by using a life cycle assessment (LCA) approach that includes uncertainty and regional differences. This research will help identify the most sustainable and scalable production methods, contributing to climate-smart agriculture and reducing reliance on synthetic fertilizers. The collaboration between the University of British Columbia and Cornell University combines strengths in environmental modeling and systems engineering, providing advanced training for the intern. Both institutions will benefit through shared expertise, new research data, and future opportunities for joint projects and innovation in sustainable agriculture.

COR Certification and HRM System/Online Onboarding Process

S3 Technical Inc., a growing manufacturer of aluminum and stainless-steel cladding products for the oil and gas industry, is undertaking a project to improve its internal processes and support continued growth. The company plans to update its standard operating procedures, work toward COR certification, and develop a Human Resources Management System (HRMS) to streamline onboarding and employee management. These improvements will help S3 Technical increase efficiency, meet industry safety standards, and access new business opportunities that require COR certification. With limited internal capacity, the company is working to bring on a qualified NAIT intern to support this work, gaining valuable hands-on experience while helping S3 Technical build a safer, more resilient, and scalable operation. The project will also contribute to Alberta’s workforce development and economic diversification by preparing future professionals and strengthening a small business’s ability to compete in evolving markets.

Prédiction de la rémission de l’asthme sévére sous biothérapie chez les enfants.

L’asthme est une des maladies chronique courante chez les enfants. Elle peut parfois devenir sévère, affectant gravement leur qualité de vie. Dans ces cas, des traitements appelés biothérapies peuvent aider à mieux contrôler les symptômes. Cependant, ces traitements sont très coûteux et ne sont prescrits qu’à un petit nombre d’enfants, souvent parce qu’il est difficile de savoir à l’avance quels patients en bénéficieront réellement.
Mon projet vise à combler cette lacune en développant un outil qui oriente la décision médicale. Cet outil utilisera des données cliniques issues de l’hôpital Sainte-Justine pour aider les médecins à identifier plus précisément quels enfants sont les meilleurs candidats pour les biothérapies.

Objectifs du projet:
Comparerl’efficacité de 2 types de biothérapie chez les enfants atteints d’asthme sévère afin de mieux comprendre leurs différences.

Définir des critéres capables de prédire la réponse aux biothérapies sur une période particuliére.

Tester ce modèle sur une nouvelle cohorte d’enfants pour s’assurer qu’il fonctionne dans différents contextes.

Ce projet pourrait permettre à plus d’enfants d’avoir accès à des traitements efficaces, tout en évitant les prescriptions inutiles. Il s’agit d’un pas important vers une médecine personnalisée et plus équitable pour les jeunes souffrant d’asthme.

Centre for Local Innovation & Collaboration Cohort 5 2025

The Centre for Local Innovation & Collaboration (CLIC) project will team up with small businesses from Richmond Hill’s Small Business Enterprise Centre. Interns from OCAD University’s Strategic Foresight and Innovation (SFI) Master of Design program will (through research) help these businesses with their innovation challenges using various methods like human-centered design, futures thinking, and strategic planning. This collaboration aims to boost growth and innovation for the businesses, producing action plans and strategies for success.

L2M -Vibrational Energy Harvester With Self-Resonant Frequency Adjusting For Wireless Sensing Network

This project will support the development and validation of a novel vibration energy harvester (VEH) with resonant frequency tuning. VEHs convert mechanical vibrations into electrical energy and can be used to power wireless sensor network (WSN) nodes for machine condition monitoring in manufacturing and processing. Conventional VEHs are resonant devices with inherently narrow bandwidths, making them effective only at a specific frequency, presenting a practical challenge as vibration conditions can vary. The proposed design uses a mechanism that can passively tune its resonant frequency, enabling energy harvesting over a wider range of operating conditions. By providing a more versatile power supply for WSN nodes, this technology can reduce battery dependence, lower operating costs, and enable wider adoption of machine condition monitoring. The project will engage stakeholders to ensure market fit and will test the system under representative conditions to advance commercialization for the partner organization.

Community Benefits Network in Prince Edward County

This project, in partnership with The County Foundation (TFC), supports the work of the Community Benefits Network (CBN), a coalition of 23 local organizations working to ensure that new development in Prince Edward County delivers lasting, positive outcomes for the community. With major public and private development projects on the horizon—including housing developments, a new hospital, long-term care facility, school, and water infrastructure—the County is at a turning point. Community Benefit Agreements (CBAs) offer a tool to align these developments with community-defined priorities such as affordability, workforce development, and social infrastructure.

Through this four-month research initiative, a graduate intern will lead a jurisdictional scan of rural CBA case studies, identify practical tools and governance approaches, and explore both legal and goodwill-based frameworks that can work in rural settings like PEC. Key deliverables will include a rural CBA case study report, an annotated resource guide, a draft CBA toolkit tailored to PEC, a plain-language brief for community and developer partners, and a final presentation of findings. The goal is to build local capacity, deepen community-developer collaboration, and support more inclusive, equitable development outcomes in the County.

Nonlinear adaptive neural controllers

Contemporary machine learning has been very successfully applied to processing static images and words in consumer applications, resulting in billions of dollars in recent acquisitions of machine learning companies by Microsoft, Amazon, Facebook, and Google. However, applications to dynamic information (e.g. movies, controlling robotics) has been less well-developed. In this project, will develop and apply a novel machine learning method to neural control system for a sophisticated robotic arm. We will use hierarchical optimal neural control, dynamic trajectory generation, and non-linear adaptive methods. These same algorithms lay the foundations for processing dynamic perceptual information as well. The methods allow for the generation of neural network controllers that require limited or no knowledge of the system, allow for one-shot learning, provide generalizable trajectory generation, exhibit online error correction, and provide a natural implementation in neuromorphic hardware. This will provide the company with a clear lead in state-of-the-art controllers for robotics applications.

L2M Validation / QC Automne 2025 / Apertum – Pierre-Briac METAYER / Validation du potentiel commercial de la plateforme Apertum : Analyse des applications des biomarqueurs multimodaux pour le dépistage en santé

Ce projet vise à mieux comprendre les marchés et les partenaires auxquels s’adresse Apertum, une entreprise québécoise en santé numérique qui cherche à combler le fossé entre les innovations développées en laboratoire et leur application concrète dans la société. Trop souvent, des outils prometteurs comme les biomarqueurs numériques pouvant détecter précocement des troubles comme la maladie d’Alzheimer ou la dépression restent confinés aux laboratoires et n’atteignent jamais les citoyens.

Apertum souhaite faire tomber ces barrières en développant une plateforme technologique qui standardise la manière dont on collecte, structure et analyse les données en santé (voix, vidéo, questionnaires, capteurs, etc.), tout en assurant l’interopérabilité des protocoles et la robustesse scientifique des résultats. L’objectif est d’accélérer le transfert de ces innovations vers la clinique et la vie quotidienne, dans un cadre éthique/transparent.

Dans ce projet, le stagiaire mènera une étude de terrain pour aller à la rencontre des professionnels de santé, des institutions publiques, des entreprises du secteur, des laboratoires, mais aussi des experts en propriété intellectuelle et en valorisation de l’innovation. L’objectif est de mieux comprendre les besoins réels, les obstacles actuels et les opportunités de collaboration pour orienter le développement d’Apertum en cohérence avec les attentes du marché.

L2M – BioRush

Forensic analysis of biological evidence typically takes weeks, sometimes years. Through years of research, we have developed tools that can automate the workflow in a forensic lab, enabling processing complex samples such as sexual assault evidence in 4 hours. BioRush enables forensic labs to treat all cases as rush cases. BioRush integrates and automates all the required lab functionalities into one easy-to-use instrument that performs the required microscopy, differential extraction, forensic DNA analysis and more, enabling rapid, on-site, fully automated forensic sample processing. BioRush’s vision is to enable every case to be treated with the urgency that it deserves. To achieve this vision, we developed two modules: automated microscopy and automated DNA analysis. The automated microscopy is performed using patent-pending AI-driven virtual staining technology. The automated DNA analysis is performed via a liquid handling technology called digital microfluidics. This project aims to establish product-market fit as a first step in commercialization efforts. This project will enable the research to have real world impact. By establishing product-market fit, this will enable maximizing benefits to Canada and beyond. Faster forensic analysis leads to faster, more informed and efficient investigations, enabling investigators to apprehend violent criminals before they can re-offend, ultimately saving lives.

L2M – Early detection of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) affects up to 20% of pregnancies in Canada and is often diagnosed late, between 24–28 weeks, leaving limited time for preventive action. This delay can lead to serious complications for both mother and child, including preterm birth, macrosomia, and long-term risk of type 2 diabetes. Women with infertility, PCOS, insulin resistance, obesity, or advanced maternal age are particularly vulnerable—yet current screening practices fail to support them early enough. Our project, developed by the MUN Fertility Research Team, addresses this critical gap by introducing a digital health platform that uses AI to predict GDM risk and offer lifestyle interventions as early as preconception or the first trimester. The app collects medical, behavioral, and biometric data—such as age, BMI, physical activity, and sleep patterns—via wearable tech and user input. It then delivers personalized recommendations for physical activity, nutrition, and stress management, alongside behavior-change tools and a peer-support community. Our innovation not only empowers individuals to manage their health proactively but also provides clinicians with a scalable, time-saving tool for improving outcomes in high-risk pregnancies. Postpartum support is included to help reduce future diabetes risk.

L2M – Lumos Smart Light Therapy Glasses for Sleep and Mental Wellness Commercialization

This project will help an intern develop Lumos, a made-in-Canada light therapy glasses venture that aims to improve sleep and alertness. With support from the Lab2Market program, the intern will gain practical experience in identifying target users, developing a go-to-market strategy, and collecting early product feedback. Lab2Market will provide mentorship, training, and access to a national network of entrepreneurs to guide the intern in turning a science-based innovation into a real business. This partnership will help move Lumos from lab to market while giving the intern key entrepreneurial skills and experience.

Caractérisation fonctionnelle des protéines TRM au cours du développement précoce du fruit chez Arabidopsis thaliana et Capsella rubella

Les protéines TRM, identifiées par le groupe de recherche Contrôle Spatial de la Division Cellulaire (IJPB, INRAE de Versailles) sont des déterminants de la taille et de la forme du pistil (gynécée) et du fruit. Ce projet vise à comprendre les fonctions des protéines TRM au cours de la morphogenèse du gynécée, à savoir comment elles régulent et coordonnent l’organisation des réseaux de microtubules et les directions de croissance et de division cellulaire au cours de ce processus développemental complexe. Ce projet est basé sur une analyse comparative de 2 espèces proches, Arabidopsis et la Capselle, pour lesquelles les propriétés de croissance des tissus du gynécée sont très différentes. Il combine l’analyse d’un ensemble de matériel végétal unique produit par l’équipe de l’IJPB (INRAE de Versailles-Université Paris-Saclay) et de l’imagerie longue durée et haute résolution (expertise du laboratoire de D. Kierzkowski -IRBV- Université de Montréal).