Innovative Projects Realized

ESROP – Permanence and Periodicity: An Analysis of Structural and Cyclical Changes in Macroeconomic Aggregates

With the rise of protectionist policies in the United States, rapid integration of artificial intelligence in business, and demographic pressures from an aging population, Canada finds itself at the intersection of several powerful economic forces. These dynamics blur the distinction between long-run structural change and short-run cyclical fluctuations in macroeconomic data, increasing the risk of misinterpretation and policy miscalibration.

This project seeks to develop modernized analytical models that more effectively disentangle structural and cyclical components in macroeconomic data by leveraging time-series unsupervised learning models and graph neural networks. Existing economic models rely heavily on traditional statistical decomposition methods and the adoption of machine learning remains limited and transitional. This research addresses that gap by integrating advanced time-series machine learning with established macroeconomic theory.

Building on the combined expertise of researchers at KMUTT and the University of Toronto, the project employs a multi-phase methodology that pairs machine-learning model development with social-science case studies. The result is an advanced model designed to improve macroeconomic analysis while fostering research collaboration between Canada and Thailand.

Ultimately, this research aims to strengthen the analytical tools available to central banks, supporting sound monetary policy decisions, economic resilience, and confident navigation of an increasingly complex global economy.

Stage de recherche sur la rétroaction des noyaux actifs de galaxies (AGN) et la dynamique du milieu intra-amas de galaxies

Le projet de recherche proposé vise à comprendre comment un trou noir supermassif influence son environnement et la formation des étoiles dans la galaxie centrale NGC 4696, au cœur de l’amas du Centaure, en utilisant des données inédites du télescope spatial James Webb. Le stagiaire participera à l’analyse de ces observations afin de séparer, à l’aide de méthodes avancées d’intelligence artificielle, la lumière émise par le gaz chaud et froid de celle des étoiles, et d’étudier des signatures stellaires surprenantes qui pourraient indiquer un mode de formation stellaire inhabituel. Ce travail permettra de mieux relier le refroidissement du gaz, l’alimentation du trou noir et son impact sur la galaxie, un problème central en astrophysique moderne. Les avantages escomptés sont doubles : sur le plan scientifique, le projet pourrait apporter des résultats majeurs sur la formation des étoiles et la rétroaction des trous noirs, et sur le plan de la formation, le stage offrira une expérience de pointe en analyse de données JWST, en astrophysique observationnelle et en intelligence artificielle, au sein d’une équipe de recherche internationale de premier plan.

ESROP – Unobtrusive Visual/Walking Guidance in Mixed Reality

Mixed reality (MR) based visual guidance enables intuitive interaction between the user and the environment and has various applications (e.g., picking tasks, navigation, and surgical support). These applications require highlighting physical objects, and many existing techniques utilize obvious virtual elements such as outlines and arrows. While effective, they significantly increase visual clutter when conveying a large amount of information, thereby detracting from the actual scene. Therefore, we aim to control the “saliency” of the scene, the distinctiveness of certain elements in a visual scene that naturally attract human attention, using methods that are less perceivable to users, such as blur, without introducing additional virtual objects. We explore the potential for naturally guiding users’ walking behavior by manipulating “saliency” to direct their gaze. This project will contribute to the advancement of MR technologies by exploring subliminal visual guidance techniques that can enhance user experience and interaction in MR environments. The findings from this research can inform the development of more intuitive and user-friendly MR applications, which can have significant implications for various industries, including healthcare, manufacturing, and education.

Strategic development and implementation of B2B growth frameworks for enterprise resource management software

This project involves a student intern working with QReserve, a Canadian technology company that provides sophisticated resource management and scheduling software. The intern will focus on a “Growth and Marketing” initiative designed to translate QReserve’s complex technical features into clear, professional, and human-centric content for the B2B market. By developing strategic communication frameworks—including technical writing, multimedia assets, and data-driven outreach—the intern will help build professional trust within the community. This project will directly benefit QReserve by enhancing its brand presence, refining its client acquisition strategies through data analysis, and ultimately expanding its user base in the competitive enterprise software sector.

Platform Optimization and Clinical Readiness Development for the WithinStride® Smart Insole System

PROVA Innovations Ltd. is developing WithinStride®, a Canadian-designed smart insole system that supports gait rehabilitation using wearable technology and connected digital health tools. The system is intended to help individuals with mobility challenges improve their walking patterns and support recovery in both home and clinical environments.

This project will focus on strengthening the overall performance, reliability, and usability of the WithinStride® platform as it advances toward broader clinical adoption and commercialization. Activities will include enhancing system functionality, improving how data is collected and presented, and refining the user experience for patients and clinicians.

By optimizing both the physical device and its supporting digital components, the project aims to ensure the technology is effective, accessible, and ready for real-world use. The internship will support the continued development of a Canadian medical innovation that promotes mobility, healthier aging, and scalable rehabilitation solutions.

Les patrimoines des couples de fait : patrimoine d’union parentale et patrimoine indivis

Aujourd’hui, de plus en plus de couples choisissent de vivre ensemble sans se marier. Ils achètent des biens, fondent parfois une famille et organisent leur vie commune… sans toujours mesurer les conséquences juridiques de ces choix. En cas de séparation ou de décès, le partage des biens peut devenir source d’importantes difficultés, particulièrement entre les conjoints de fait.

Depuis 2025, le droit québécois prévoit un mécanisme inédit au bénéfice des conjoints de fait ayant un enfant commun : l’union parentale, qui crée un patrimoine commun destiné à assurer protection économique et égalité entre les partenaires. En revanche, les conjoints de fait sans enfant relèvent principalement de l’indivision, forme de propriété commune moins protectrice et souvent mal comprise.

À travers l’analyse de situations concrètes et de la pratique juridique, le projet vise à mettre en lumière les forces, limites et zones d’ombre tant du patrimoine d’union parentale que du patrimoine indivis. Par ailleurs, cette étude poursuit un objectif de comparaison entre le droit français et le droit québécois pour évaluer les modèles d’organisation patrimoniale des couples de fait et contribuer à une meilleure compréhension des règles applicables, tant pour les professionnels du droit que pour les citoyens.

Electric and Hybrid Electric Aircraft Design: Partnership between the University of Stuttgart and the University of Toronto

The global shift to sustainable energy and climate consciousness as lead to the innovation and development of unique technologies that challenge societal norms. One such technology is electric and hybrid electric aircraft. With the advancement of this transportation type comes the advent of new challenges in energy storage and thermal management. Once such problem is the creation of unusable heat in the fuselage that must be dissipated to the external atmosphere. This project focuses on the development of a composite fibre fold Skin Heat Exchanger (SHX) that can, in theory, effectively dissipates heat without creating an excessive amount of cooling drag and aerodynamic inefficiency. This project focuses on the development, design, and integration of an SHX onto an experimental electric aircraft, known as the e-Genius. A proposed collaboration between the University of Stuttgart and the University of Toronto, the advancement of electric aircraft technologies can shape the future of sustainable design, and make combustion-based aircraft a thing of the past.

Modeling Brain Responses to Natural Conversation via LLM-Derived Informational and Relational Metrics

The project uses large language models (LLMs) and information-theory measures to quantify how people think in real conversations. The goal is to create a pipeline that quantifies informational content (the purpose of the utterance is to provide/inquire information) and relational content (the purpose is to build a stronger relational bond with the other speaker) in conversation utterances. Then, we will test whether these conversation features can predict which parts of the brain become active while people talk and listen in natural, everyday conversations. This work will help Princeton and the University of Toronto develop better, more realistic models of human communication and brain function, and will produce tools and analyses that can support future research in neuroscience and AI.

Enseigner à NEOJIBA

Ce projet de recherche vise à mieux comprendre comment la musique peut contribuer au développement et au bien-être des jeunes, en particulier ceux issus de milieux défavorisés. Pour ce faire, le chercheur effectuera une immersion de trois mois au Brésil au sein de NEOJIBA, un programme d’éducation musicale reconnu internationalement et inspiré d’El Sistema, qui permet à des milliers de jeunes d’apprendre la musique en orchestre. En participant directement aux activités du programme comme enseignant et observateur, il cherchera à comprendre comment NEOJIBA adapte la musique à son contexte social et culturel, tout en répondant aux critiques adressées à El Sistema. L’objectif est ensuite de comparer cette expérience avec la réalité québécoise afin d’identifier des pratiques inspirantes et réalistes pouvant améliorer l’accessibilité et l’équité des programmes de musique au Québec. À terme, ce projet souhaite contribuer à documenter les possibilités d’adaptation de programmes inspirés d’El Sistema au Québec.

Diagnostic médical assisté par l’IA via l’intégration de l’imagerie médicale et des modèles linguistiques et visuo-linguistiques

L’intelligence artificielle joue un rôle de plus en plus important dans le domaine de la santé, notamment grâce aux grands modèles de langage capables d’analyser de vastes volumes d’information médicale. Toutefois, ces systèmes demeurent souvent difficiles à interpréter, ce qui limite leur utilisation dans des contextes sensibles.

Ce projet vise à développer des outils d’intelligence artificielle plus transparents et fiables afin de soutenir la prise de décision clinique. En combinant apprentissage automatique avancé et mécanismes explicatifs, l’objectif est d’améliorer la compréhension des recommandations générées par l’IA et de renforcer la confiance des utilisateurs.

Mené dans le cadre d’une collaboration entre le Canada et la Tunisie, le projet offrira à une stagiaire l’occasion de travailler dans un environnement de recherche stimulant à l’Université du Québec à Rimouski (campus de Lévis). Cette expérience favorisera le transfert de connaissances et le développement de compétences spécialisées en intelligence artificielle appliquée.

À terme, les résultats contribueront à l’évolution de technologies intelligentes responsables et au rayonnement de la recherche canadienne.

Vehicle Mounted Remora Edge Sensor Platform Building the Urban Nervous System

Livesens is building the Urban Nervous System: a vehicle-mounted sensing layer that turns everyday fleet movement into real-time street visibility. As vehicles drive their normal routes, we capture basic mobility signals (where movement slows, where stops cluster, how travel time changes by time of day) and convert them into clear corridor outputs like travel time reliability, delay hotspots, and recurring congestion patterns.

ESI Imaging Novel Breast Cancer Screening Data Driven Research Study

ESI’s current focus is product research and development (R&D), and commercialization activities. The R&D pipeline furthers the technology (hardware, software), systems, and collects/analyzes the data required to ensure device operations and regulatory compliance. Device R&D will refine and miniaturize the metasurface, enhance antennae, and complete software integration (signal and image processing, hardware integration, AI-driven decision-making). Data collection, testing, analysis are key to hardware and software enhancements by providing evidence, comparative testing, AI/ML training, and pre-regulatory data. Ongoing, regular, structured data collection is critical to development and certification; with a small team, data collection activities are key, but leadership and engineering teams lack the resources for sustained collection. A key data collection milestone is First-in-Human (FIH) testing scheduled for Q2-Q3 2026.
The intern will primarily be involved in data-driven activities related to FIH with an enriched population; that is, high-risk female patients at an Ontario Breast Screening Program (OSBP) / breast oncology facility. (ESI is currently in discussion with Juravinski Hospital/CIBC OSBP site.) The intern will be involved in the FIH design, collection, and analysis of the data needed to feed further R&D and regulatory planning