Projets novateurs réalisés

Machine Learning-Driven Techno-Economic Optimization of Hybrid Renewable Energy Systems with Hydrogen Storage for rural electrification in developing countries

Achieving net-zero targets in developing countries requires deploying renewable energy in off-grid areas where grid expansion is impractical. High capital costs for renewable energy and hydrogen storage hinder adoption, with many systems being inefficient due to poor sizing or curtailment. This research focuses on developing a hybrid AI and optimization framework to enhance the sizing and economic analysis of renewable energy systems. It aims to create a cost-effective Hybrid Renewable Energy System (HRES) for off-grid electrification in Nigeria or similar locations in Canada or globally. Building predictive models using Linear Regression, Tree Support vector Machines (SVM), Ensemble, Gaussian Process Regression, neural Network, and Kernel models is proposed for estimating the Levelized Cost of Electricity (LCOE) of the systems. By leveraging innovative AI solutions, the study aims to promote net-zero technologies and address barriers to transitioning to a low-carbon economy.

Image-to-Video Generative Modeling for Controllable Image Animation

This project aims to develop an AI-driven system that transforms a single still image into a realistic, controllable animated video. Unlike traditional video production, which requires costly filming or manual animation, our approach leverages advanced diffusion models to automatically generate dynamic motion while preserving the original visual details of both characters and text. A key innovation is the creation of layered video outputs, where different elements—such as background, characters, and text overlays—are separated. This allows easy editing and customization, enabling creators to modify individual components without regenerating the entire video.

The technology directly addresses challenges faced by the digital marketing and creative media industries, where rapid production and personalization are essential. By providing a scalable solution for high-quality animation, the project reduces production costs and turnaround times, empowering companies to deliver engaging content across multiple campaigns and markets.

Beyond commercial applications, this work contributes to advancing Canada’s AI and creative technology ecosystem. It trains highly skilled talent in generative AI and fosters collaboration between academia and industry. The outcome will support small businesses, independent artists, and marketing teams with accessible, professional-grade animation tools, driving innovation in digital storytelling and interactive advertising.

Safeguarding Economic Rights in Irregular Migration: Practical Pathways for Protection and Regularisation

This research project seeks to explore two interrelated, critical questions: “how do States situated along key migration corridors safeguard irregular migrants’ economic rights?” and, more specifically, “to what extent are measures and models to prevent and prosecute labour exploitation and forced labour (incl. through anti-trafficking efforts) effective in practice?”

Kondan & Symss Consultancy Inc. is a Toronto-based international consulting firm that works globally across more than 30 countries. Over the past decade, the firm has developed strong expertise in irregular migration by evaluating various global return and reintegration platforms/facilities alongside multiple protection and migration-related projects.

Through these engagements, the firm has observed that while policymakers and practitioners often voice strong interest in upholding the economic rights of irregular migrants, there is little case study documentation that shows what has worked and why certain commitments fall short. This gap is especially pressing in States facing rising demand for labour migration but with limited experience in managing bilateral agreements or temporary migration schemes. Therefore, the project aims to address this evidence gap by producing research across the proposed objectives, alongside a series of public-facing briefs that synthesize findings into accessible lessons learned.

Equilibrium isotope effects in aqueous environment

Water is without a doubt the most studied chemical compound. Nonetheless, because water is at the center of all biological and many geological processes and because it has uncommon physical and chemical properties, there is always more to discover about it. Here we aim to understand how water affects isotopic equilibria in gases containing methane, carbon dioxide, hydrogen, etc. – all ubiquitous in geology. This is crucial for geochemical applications, as isotopic content of samples is routinely used to pinpoint the origin and the mechanism of formation of natural samples. In collaboration with quantum chemists from Tufts and experimental geochemists from Berkeley, we have already developed a robust framework for predicting these for gaseous molecules.

In order to broaden the scope and impact of our research, we seek expertise in modeling complex many-body effects from the theoretical and computational physics group from lead by Prof. Sakhnyuk at the Volyn National University in Lutsk, Ukraine. The intern, Dmytro Skorubskyi, guided by Prof. Korol will utilize his background in theoretical and computational physics to overcome the challenges of simulating such a complex environment as liquid water. The interdisciplinary and inter-continental connection will thus be established.

Développement de films composites PLA/Biochar conducteurs et biodégradables pour des applications électroniques écoresponsables

La demande croissante de matériaux électrochimiques durables et respectueux de l’environnement a stimulé l’intérêt pour le développement de polymères biodégradables contenant des charges conductrices renouvelables. L’acide poly-lactique (PLA) est un biopolymère largement considéré comme respectueux de l’environnement, mais sa faible conductivité électrique limite son utilisation dans les applications énergétiques avancées. Pour surmonter cette limitation, le biochar – obtenu par pyrolyse de la biomasse – apparaît comme un candidat prometteur en raison de sa surface spécifique élevée, de sa stabilité et de ses propriétés électriques intrinsèques. Dans ce projet, nous présentons la fabrication et la caractérisation de films composites PLA/biochar, en étudiant l’effet de la teneur en charge carbonée sur les propriétés structurelles, mécaniques et électrochimiques. Des analyses thermiques et physicochimiques seront réalisées pour évaluer les interactions biochar/PLA et la stabilité du matériau, tandis que la microscopie électronique sera utilisée pour étudier la dispersion du biochar. Les propriétés électrochimiques seront également étudiées afin de déterminer la conductivité et la capacité de stockage du composite. Ces résultats devraient confirmer le potentiel des films PLA/biochar comme matériaux biodégradables et conducteurs, adaptés aux électrodes flexibles et aux dispositifs de stockage d’énergie écologiques, contribuant ainsi à la transition énergétique et à l’économie circulaire.

Enhancing Visibility and Long-Term Sustainability of the Whitecourt ISGA Tourism Association through Strategic Case Study Development

This project will help the Whitecourt ISGA Tourism Association (WITA) share its story and show the positive impact it has on the community. WITA offers land-based tourism experiences such as workshops, trail walks, and cultural activities that support local entrepreneurs and celebrate Nakota culture. Working in partnership with Catalyste+, which has supported WITA through 15 projects since 2022, this initiative will create a case study that highlights WITA’s history, achievements, and long-term goals. The case study will make it easier for WITA to attract funding, build partnerships, and grow its programs, helping the organization become more visible and sustainable for the future.

Transformation numérique et expérience citoyenne : une approche d’ingénierie ontologique pour l’intégration et l’automatisation des processus municipaux avec l’IA

Les villes, comme d’autres organisations, cherchent à utiliser l’intelligence artificielle (IA) pour automatiser leurs processus internes et améliorer leur fonctionnement. Mais contrairement aux autres niveaux de gouvernement, les municipalités sont en contact direct avec les personnes citoyennes. Elles doivent donc offrir des services de qualité, rapides et concrets, ce qui complique leur transformation numérique.
Des technologies récentes comme les modèles de langage (LLM), les générateurs de texte (GPT), les graphes de connaissances (KG) et le raisonnement sémantique (SR) permettent aujourd’hui de mieux répondre à ces défis. En combinant ces outils, les villes peuvent adapter plus facilement leurs processus tout en s’appuyant sur des modèles existants.
Pour explorer ces solutions, un projet de recherche est lancé en collaboration avec la ville de Gatineau. Une étudiante au doctorat mènera des consultations afin de mieux comprendre leurs attentes en matière de services. Ces données serviront ensuite à une autre équipe de stagiaires pour créer des « ontologies », c’est-à-dire des structures de connaissances, permettant d’intégrer l’IA dans les systèmes de gestion municipale.
L’objectif global est de proposer une méthode pratique pour moderniser les services municipaux grâce à l’IA, en mettant l’accent sur l’expérience citoyenne et l’efficacité des processus internes.

Records Management Review Implementation

Our proposed records management modernization project will include deployment of records management classification system TOMRMS across the organization, updates to by-laws and policies, the development of new procedures, exploration of a new records management solution, enhanced staff communication and training.

Optimizing Community Paramedicine: Evaluating System Efficiencies & Innovation

This project, in partnership with Middlesex-London Paramedic Service (MLPS), focuses on evaluating and expanding the Community Paramedicine program as a strategy to address Ontario’s primary healthcare access crisis. By collecting and analyzing data on 911 calls, patient outcomes, and program impacts, the research will identify opportunities to expand services and demonstrate the cost savings and efficiency gains of this model. The findings will support MLPS in optimizing resource use, reducing pressure on emergency departments, and positioning the organization to secure future funding and policy support. Thus, overall enabling the MLPS to deliver more effective and sustainable healthcare to the community.

Canadian Robotics Case Study Library & Strategic Partnerships

The Canadian Robotics Council (CRC), a non-profit organization with the agility of a startup, is launching a National Case Study Library to accelerate robotics and Physical AI adoption across Canada. This initiative will collect and analyze real-world examples of how robotics is being used, providing valuable insights on what works, what doesn’t, and where opportunities lie. By creating a clear framework to evaluate these case studies, the project will highlight trends, best practices, and gaps in adoption. These findings will guide CRC in supporting industry partners, improving service delivery, and shaping future strategies.

Beyond building knowledge, the project will also design a sustainable business model to ensure the library remains a long-term resource for members. It will demonstrate how the collection of unique, practical content can add value to partners, attract new members, and strengthen CRC’s role as a national leader in robotics innovation. The initiative will also introduce digital transformation practices—streamlining submissions, automating partner communications, and building efficient, modern workflows.

By engaging industry partners and associations, the project will expand its reach and ensure the content is diverse and relevant. Furthermore, for the CRC’s partners, this project offers a direct benefit: access to high-quality, practical insights that reduce risk, accelerate adoption, and unlock new business opportunities in robotics and Physical AI. In short, this project will provide the tools and knowledge needed to innovate faster, strengthen competitiveness, and position Canada as a leader in robotics-driven transformation.

Co-creating a toolkit for senior-led community programs

Social isolation and loneliness are major challenges for older adults, affecting their mental, physical, and cognitive health. This project aims to promote older adults’ social participation in their neighbourhoods and reduce risk of social isolation by collaboratively creating a practical, evidence-based toolkit that older adults can use to develop and lead neighbourhood-based social programs. The project will actively involve older adults as co-creators and leaders, and will help older adults build leadership skills, stay socially connected, and contribute their ideas to local initiatives. For the City of London, the project will increase their ability to offer innovative and cost-effective programs that meet older adults’ needs and interests in a sustainable way. The resulting toolkit will provide clear, adaptable, and long-term guidance for older adults and community partners, helping create age-friendly communities where older adults can remain active, engaged, and supported.

Artificial Intelligence-Driven Predictive Modeling for Canine Pain Assessment and Personalized Analgesic Recommendations

Accurately assessing and managing pain in dogs is one of the most challenging aspects of veterinary medicine because animals cannot verbally communicate their discomfort. Current methods rely heavily on behavioral observations and standardized scoring tools, which are often subjective and prone to inconsistencies. This project aims to address these limitations by developing an AI-powered predictive modeling framework that leverages publicly available veterinary datasets to improve pain detection and optimize treatment strategies for companion animals. Through advanced machine learning techniques, the project will analyze clinical records, treatment histories, and behavioral data from open-access sources such as VetCompass, CBPI, and C-BARQ to create predictive models capable of assessing pain severity, forecasting recovery patterns, and recommending personalized analgesic treatments. The proposed framework will be validated against widely used pain assessment tools, ensuring higher accuracy and reliability in veterinary decision-making. This research will enhance animal welfare, empower veterinarians with data-driven decision-support tools, and promote innovations in veterinary informatics