Innovative Projects Realized

Generalized Thermodynamically Admissible 13-Moment Equations

This project explores how to better model gas flows in situations where traditional fluid equations break down, such as in very small systems or low-pressure environments. Instead of relying on costly molecular simulations, the research develops advanced extensions of classical fluid models that remain mathematically stable and thermodynamically consistent, while being flexible enough to describe different gases. The student will spend time at a leading German institution to refine and test these models with international experts, combining rigorous theory with modern numerical methods. By bringing this expertise back to Canada, the project will strengthen national research capacity and support innovation in industries such as aerospace, vacuum technology, and micro-systems, while also deepening long-term collaboration between Canadian and German institutions.

Intelligence artificielle dans les entreprises B2B au Québec: défis et opportunités

Ce projet de recherche porte sur l’adoption de l’intelligence artificielle (IA) par les entreprises québécoises qui œuvrent dans le secteur du commerce entre entreprises (B2B). L’objectif est de mieux comprendre comment ces organisations intègrent l’IA dans leurs activités, quels bénéfices elles en retirent, mais aussi quels défis humains, financiers et organisationnels elles rencontrent. Pour y parvenir, une étudiante au doctorat mènera un sondage auprès d’un large échantillon d’entreprises. Les résultats permettront de dresser un portrait inédit de l’utilisation de l’IA dans ce secteur et d’identifier les meilleures pratiques. Pour l’organisation partenaire, une firme spécialisée en marketing B2B, ce projet offrira des données précieuses afin d’améliorer ses services et de mieux accompagner ses clients dans leur transformation numérique. De manière plus large, cette recherche contribuera à soutenir l’innovation et la compétitivité des entreprises québécoises et canadiennes dans un contexte technologique en évolution rapide.

Droit international de l’investissement et développement durable

Le projet s’inscrit dans la thématique “Durabilité et environnement”. Il analyse les interactions entre le droit international de l’investissement et les impératifs de développement durable. Dans un contexte marqué de plus en plus par l’urgence climatique et environnementale, force est de constater que l’ensemble des Etats, y compris le Canada sont confrontés à des défis écologiques majeurs. Pour préserver ces intérêts sociaux et environnementaux, les Etats prennent des mesures, parfois susceptibles de porter atteinte aux intérêts privés des investisseurs. Ces derniers ne tardent pas à traduire les Etats qui s’engagent dans la durabilité, devant les tribunaux arbitraux, en usant des standards de protection des investissements solides prévus par les traités d’investissements, à l’instar du Traitement juste et équitable. Concrètement, le projet vise à analyser de manière critique les mutations du droit international à la lumière des impératifs du développement durable. Pour ce faire, il identifie les solutions innovantes permettant d’intégrer des obligations substantielles à la charge des investisseurs, qui sont jusque-là exemptés. La doctrine contemporaine dénonce cette asymétrie du droit international de l’investissement et le projet vise à enrichir cette réflexion dans le but de contribuer à cette transformation du droit international de l’investissement.

Microwave-Assisted Degradation of Organic Contaminants and Regeneration of Granular Activated Carbon in Water Treatment

This project explores microwave-assisted thermal treatment as a sustainable method to both degrade organic contaminants and regenerate granular activated carbon (GAC) used in water treatment. The goal is to determine whether high-power microwaves can desorb and break down pollutants from spent GAC while preserving its structure and extending its adsorptive life.

A range of micropollutants including pharmaceuticals, phenols, dyes, and pesticides, will be tested on coal, coconut, and wood-based GAC under controlled 2.45 GHz microwave exposure. By promoting desorption and thermal transformation, this approach could reduce reliance on chemical regeneration or full mineralization while enabling multiple reuse cycles of GAC.

AGP Dynamic Solutions Inc., a Canadian leader in industrial microwave systems, is the industry partner. With expertise in high-power microwave technology, AGP is evaluating how its systems can support on-site GAC regeneration, cutting operational costs and carbon waste for water utilities and industries.

Led by an intern with advanced research training in water filtration, the project will use advanced analytical tools to assess regeneration efficiency. The outcomes could drive scalable, innovative solutions that lower waste, support cleaner water, and align with circular economy and public health goals.

Adaptive Digital Twin for Optimizing Repositioning, Routing, and Matching in Private Floating Fleets

Private charter fleets are valuable mobile assets that, when efficiently managed, can generate substantial revenue for operators and owners. A key factor in maximizing profitability is achieving a high asset utilization rate. We propose the development of a large-scale adaptive digital twin for supporting private floating fleet repositioning, routing and matching decisions. The digital twin is designed to connect thousands of charter aircraft and passengers in real time in a virtual private air travel network. Metaheuristic repositioning/routing/matching algorithms will be designed to optimize floating fleet assignments. These algorithms will account for various operational constraints and costs, including regulatory compliance, insurance, fuel surcharges, crew fees, and airport charges.
The digital twin will employ a microservice-enabled multi-agent system architecture to model key components—operators, passengers, aircraft, airports, and more. This back-end infrastructure will enable the industrial partner to monitor dynamic supply and demand, optimize routing and repositioning decisions, evaluate and validate a wide range of strategic, operational, and pricing scenarios. It will also be designed to be integrated with the industrial partner’s existing software systems. Additionally, the proposed platform can support the development of advanced market mechanisms such as empty-leg auctions, group bidding, and revenue-sharing models among collaborating charter operators.

Attitude Determination using Dual-Purpose SSA Payload

Wide Field of View (WFOV) cameras can be deployed in the space environment to allow for opportunistic observation of Resident Space Objects (RSOs) for Space Situational Awareness (SSA). This project aims to deploy a WFOV camera in a cubesat, which will increase the observation window compared to the previous near-space and stratospheric missions.

Studying formation and destabilization mechanisms of pickering emulsions encapsulated with bioactive compounds via confocal/STED microscopy

Bioactive compounds are naturally occurring food components that can promote human health, but they often lose their effectiveness because of problems such as low stability, low solubility, and poor absorption in the body. Encapsulation in emulsions is one promising way to protect these compounds and help them reach their target tissues, but the main limitation is that emulsions are not always stable and can separate over time. Pickering emulsions, which are stabilized by solid particles rather than traditional surfactants, have been shown to offer better stability and lower toxicity, making them highly attractive for food and nutraceutical applications. However, there is limited understanding of the exact mechanisms by which they become unstable, particularly when bioactive compounds are encapsulated inside them. To address this knowledge gap, the project will use advanced imaging methods, such as confocal and STED microscopy, to capture high-resolution images of emulsions at different stages of formation and destabilization. The images will be analyzed using quantitative tools to provide information on droplet size, shape, distribution, and the arrangement of encapsulated compounds. By combining this information, the project will build new understanding of how emulsion stability is related to its microstructure and the role of protein nanoparticles as stabilizers.

Automation, Data Processing, and Validation of Spectral Measurements in Molecular Degradation Research

This project develops automated pipelines for processing Raman and UV-Vis spectral data collected during studies of molecular degradation. The focus is on improving reproducibility, accuracy, and efficiency in monitoring antioxidants such as BHT and PAN derivatives. The workflows will perform spectral baseline correction, peak fitting, smoothing, and feature extraction, enabling rapid interpretation of large experimental datasets. Validation against quantum chemical simulations ensures consistency between experimental observations and theoretical models. Automated routines will allow scalable, high-throughput analysis, reducing manual errors and accelerating discovery. Outcomes include standardized tools for processing spectroscopic measurements, integration with quantum-derived reference spectra, and improved reliability of degradation monitoring in industrial oils and complex matrices. Students will gain experience in coding, algorithm development, and data–experiment integration, strengthening their skills in spectroscopy, automation, and applied sensing technologies.

Computational and Experimental Study of Molecular Transformation Routes in BHT-Quinone, Para-Benzoquinone, PAN, and PAN2

This project focuses on the combined quantum computational and experimental investigation of molecular transformation routes in antioxidant systems, specifically BHT-quinone, para-benzoquinone, PAN, and PAN2. These compounds are critical intermediates in the degradation of antioxidants commonly used in lubricants, polymers, and other organic systems exposed to oxidative stress. The study integrates quantum-chemical modeling, including density functional theory (DFT) and multiconfigurational approaches, with Raman and UV-Vis spectroscopy to establish transformation pathways and spectral fingerprints of the molecules and their degraded forms. The experimental component will provide reference spectra under controlled conditions, while the computational analysis will predict electronic structure changes, vibrational characteristics, and thermodynamic stability of products. By combining both approaches, the project will generate a detailed molecular-level understanding of antioxidant degradation, enabling predictive models for monitoring material stability.

The results have direct industrial relevance for sectors where lubricant lifetime, polymer durability, and oxidative resistance are crucial, such as aerospace, automotive, and energy. The project will also serve as a platform for training students in interdisciplinary physical methods, spanning spectroscopy, computational quantum chemistry, and materials diagnostics. This research contributes to both fundamental science, by clarifying molecular transformation routes and practical applications, by informing the design of sensors and monitoring systems for oxidative degradation.

Applications of Two-Eyed Critical Sensemaking: Reviewing Academic Research Processes and Ethics from a lens of Indigenous Governance

The purpose of this project is to understand the tensions between Indigenous-led research projects and the standard academic processes that are intended to maintain ethical standards. By identifying the tensions, strategies used to navigate them effectively will also be identified. The project will be adopt Two-Eyed Critical Sensemaking as a lens to analyze research ethics processes. The Two-Eyed Critical Sensemaking Approach was designed to provide guidance for Canadian administrators who wish to respond to Commission’s Calls to Action. This research will support extension of the approach and its applicability in other settings. It will also support development of additional procedural guidelines that can adapt to the geographically specific context of Indigenous reconciliation efforts. It will also provide a unique opportunity for cross collaboration and network building for the student and Indigenous-led research efforts in Australia.

Optimisation des simulations haute-fidélité du champ de vent dans un parc éolien par l’apprentissage automatique

Wind energy plays a crucial role in the global transition to clean and sustainable energy. Maximizing wind farm efficiency requires accurate prediction of wind behavior. This project aims to enhance wind field simulations by combining high-fidelity computational fluid dynamics (CFD) models with machine learning techniques. While CFD simulations provide detailed insights into wind-turbine-terrain interactions, they are computationally intensive, limiting their use for real-time decision-making.
The project uses machine learning to learn from CFD data and build surrogate models that predict wind conditions much faster without losing accuracy. This approach enables rapid assessment of wind patterns, supports optimal turbine placement, improves operational strategies, and enhances maintenance planning.

Conducted at École de technologie supérieure (ÉTS) in Montreal, the research involves a collaborative team led by Dr. Reda Snaiki, with access to high-performance computing resources and expert guidance from PhD students. The intern will develop machine learning models and validate them against CFD simulations and, when possible, real wind data.
The expected outcomes include more informed operational decisions, increased energy production efficiency, and reduced costs. This methodology could be applied to various renewable energy systems, advancing sustainable and resilient clean energy technologies worldwide.

Évaluation multidimensionnelle de l’intégration technologique dans l’industrie minière

Cette recherche évalue l’impact des technologies émergentes (telles que l’automatisation, l’intelligence artificielle) sur les opérations minières souterraines, en considérant leurs dimensions environnementales, sociales, techniques et économiques. En développant des outils d’aide à la décision et des modèles analytiques, elle vise à optimiser la sélection des technologies, leur calendrier de déploiement et leur intégration avec les processus existants.

Le projet se concentre sur l’amélioration de l’efficacité énergétique, la gestion des flux de matières et la performance opérationnelle, tout en garantissant la durabilité et la conformité réglementaire. Pour les institutions partenaires—l’École de technologie supérieure (ÉTS, Canada) et l’Université Mohammed VI Polytechnique (UM6P, Maroc), cette collaboration renforce leur expertise dans les technologies minières durables, favorise les échanges transfrontaliers de connaissances et élargit leur impact grâce à des solutions adaptées aux besoins industriels.

À terme, ce projet fournira aux entreprises minières des stratégies fondées sur des données pour accroître leur productivité, réduire leur empreinte environnementale et promouvoir des pratiques plus sûres et plus efficaces. Il positionnera également les deux universités comme des leaders dans l’innovation minière.