Projets novateurs réalisés

A Multidisciplinary Quantum-Based Clinical Decision Support System to Advance Medical Diagnostics and Treatment

Complex diseases like neurological disorders, rare pediatric conditions, chronic kidney diseases, sepsis, and complications from maxillofacial surgery are putting pressure on the global healthcare system. As the volume of medical data grows, ranging from imaging and physiological signals to electronic health records, there is an increasing need for more precise and personalized approaches to diagnosis and treatment. Traditional methods often fall short in handling this complexity, but quantum computing offers a promising solution. With its ability to perform large-scale, parallel computations using principles like superposition and entanglement, it opens new possibilities for tackling these medical challenges.

This project aims to revolutionize clinical decision support systems by leveraging advanced quantum techniques. We will integrate quantum machine learning (QML) methods, including quantum decision fusion, fuzzy clustering, reinforcement learning, and Siamese neural networks, to improve diagnostic accuracy, optimize treatments, and ultimately enhance patient outcomes. Our focus spans four critical medical areas: pediatrics, nephrology, neurology-sepsis, and maxillofacial surgery.

By addressing these pressing clinical challenges, our work not only pushes the limits of medical AI but also brings quantum technologies closer to real-world healthcare applications.

Welfare Governance: Regulating the Rise of Private Credit in Social Welfare Services

Around the world, private equity funds and other investors have acquired social welfare service providers such as hospitals, physician groups, colleges, and childcare centres. While private equity funds bring significant financing to these sectors, private equity ownership is associated with reduced service quality, higher costs, and deteriorating working conditions for service providers—especially where private equity has a substantial share of a local market. This project examines the legal and regulatory reforms in social policy and financial regulation that have permitted and incentivized the expansion of investor-backed childcare services. Drawing on the primary legal regimes regulating social services, it analyzes the interrelationships between welfare, labour, and competition laws and aims to propose a legal framework to regulate private financing in social services.

Focusing on childcare as a key welfare institution, the project compares the legal frameworks in Canada, France, and the United States. In the U.S., childcare financing and delivery is largely market-based, while France’s traditionally public-supported childcare sector has seen the recent extensive expansion of for-profit private service providers. The differing welfare market structures arise from the contrasting welfare financing and regulation. Both countries offer lessons for Canada, where the roll-out of increased government financing for childcare services is underway.

A Satisficing Approach to Generative AI-Driven Design of Nanoparticle-Infused Structural Materials: Integrating Mixture-of-Experts for Efficient Optimization

This project aims to revolutionize the design of nanoparticle-infused structural materials by combining Generative AI with a ‘satisficing’ approach—prioritizing practical, manufacturable solutions over purely mathematical optimization. Instead of searching for a single perfect design, our method will generate a variety of high-performing, user-acceptable, and manufacturable structures using AI-driven models. By integrating a Mixture-of-Experts (MoE) framework, which leverages specialized sub-models for different performance criteria, the project will enhance design efficiency while reducing computational costs. The collaboration between Canadian and international researchers will strengthen expertise in AI-driven materials engineering, benefiting both institutions through knowledge exchange, student training, and advancements in next-generation manufacturing technologies.

Caractérisation des bactéries impliquées dans les parodontites des femmes gestantes et son influence sur la survenue de la prématurité

La prématurité constitue un réel problème de santé publique mondiale car approximativement 13,4 millions de nouveau-nés par an naissent dans cet état dans le monde, déterminant ainsi un taux de prématurité estimé à 11%. Cependant, la grande part de ces naissances revient aux pays en voie de développement, avec plus de 43% des cas. Bien que les suivis et les traitements de complications chez les femmes soient grandement améliorés, plus de 25% de cas de prématurité demeure inconnu.
L’état de la santé buccale maternelle peur être un facteur de risque de prématurité. Dans cette étude, nous tentons d’établir si un lien d’association existe entre la santé buccale maternelle et le risque d’accoucher prématurément en explorant la flore bactérienne chez les femmes en gestation.

Development of Multi-Frequency Ultrasound Localization Microscopy (ULM) Techniques on the Vevo F2 System and VADA Platform

In this project the interns will work with a leading ultrasound imaging company, FUJIFILM VisualSonics Inc, developing advanced ultrasound beamforming techniques (the process by which images are formed) using specialized ultrasound instrumentation (the F2 system using the VADA platform) that will produce high resolution images of blood vessels in tissues. These advanced beamforming techniques (based on a new method called ultrasound localization microscopy) will potentially be incorporated in subsequent versions of their device, further establishing the company as world leaders at the cutting edge of technology development.

Characterizing the relationship between infrared thermography of bony prominences occluded by lower limb orthopedic casts and local skin integrity in hospitalized children with disabilities

This project aims to improve the early detection of pressure injuries (PIs) in children with disabilities who wear casts for long periods. PIs occur when continuous pressure over bony areas damages the skin, leading to pain, infections, and longer hospital stays. Currently, it is difficult to monitor the skin under a cast because it cannot be seen or touched. This study will use thermal imaging to measure temperature changes through the cast material, which may indicate early signs of skin damage. By analyzing these thermal patterns and developing machine learning models, the project seeks to improve how hospital staff monitor and protect the skin health of casted children. This approach could enhance patient care and reduce complications, benefiting both children and the healthcare system.

A Novel Application of Plastination Technique for Transforming PMMA waste and Cotton Textile Waste into Functionality-enhanced Fabric Composites

Lululemon is a global leader in athletic apparel industry, focusing on high-quality, functional, and sustainable textiles. With a commitment to environmental responsibility, the partner is targeting 75% sustainable materials by 2025 and aims to source e.g. all cotton from sustainable sources. This joint project aligns with their sustainability mission by addressing two critical challenges: the excessive use of virgin fibers and the environmental impact of textile waste. Specifically, in this MITACS research, we aim to re-purpose a post-production PMMA waste along with recycled cotton waste into a novel high-performance composite, using a custom plastination technique. Once optimized, this innovative approach is expected to create durable, eco-friendly textiles with enhanced mechanical properties potentially suitable for multiple re-purposed applications such as apparel (e.g. outerwear) and accessories (e.g. bags). The anticipated social and economic benefits include reduced dependence on virgin fibres, minimized textile waste, and a scalable solution for using recycled materials in both textile (cotton) and plastic (PMMA) industries. By extending products life cycles and creating a circular economy model, this project offers a new pathway for Lululemon to integrate sustainable material innovation that meets high-performance standards, aligning with globally increasing consumer demands for environmentally responsible products.

Testing and validation of two-stage, high temperature, air-to-water heat pumps for the Nova Scotia environment

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Étude et mise en place d’un modèle prédictif permettant d’améliorer la rentabilité des contrats engagés

Ce projet de recherche est mené en partenariat avec Les Commissionnaires du Québec, une OSBL oeuvrant dans le domaine de la sécurité au Québec, et des chercheurs de Polytechnique Montréal. L’objectif du projet est de concevoir un prototype de système de recommandation pour supporter le processus d’appel d’offres, et à terme, d’améliorer la rentabilité des contrats engagés. Les modèles qui seront intégrés à ce prototype utiliseront diverses méthodes combinant des techniques d’optimisation et l’intelligence artificielle (IA) afin de permettre à l’organisation de maximiser les chances d’emporter des appels d’offres tout tout en garantissant la faisabilité et la rentabilité de leurs propositions.

Développement et validation d’un prototype d’application visant à soutenir la gestion de plaies de pression et de la posture chez des utilisateurs de fauteuil roulant motorisé

Amylior Inc., une entreprise spécialisée dans les fauteuils roulants motorisés, travaille sur un projet innovant visant à améliorer la vie des utilisateurs de ces fauteuils. L’objectif est de créer un fauteuil intelligent capable de s’adapter aux besoins spécifiques de chaque personne, en surveillant des paramètres comme la pression et la posture. Cela permettrait de prévenir des problèmes tels que les plaies de pression, l’inconfort ou la perte de mobilité.
Le projet se décompose en plusieurs étapes : identifier les paramètres cliniques et mécaniques nécessaires pour le suivi de la pression et de la posture, intégrer ces données dans l’application, utiliser l’intelligence artificielle pour optimiser le système, et enfin, tester l’application avec les utilisateurs pour s’assurer qu’elle est facile à utiliser et efficace.
Pour y parvenir, Amylior Inc. collabore avec des experts, des chercheurs et les utilisateurs eux-mêmes. Des méthodes comme la consultation d’experts (méthode Delphi), des sondages et des tests en laboratoire sont utilisées pour garantir que le fauteuil réponde aux besoins réels.
Ce projet montre l’engagement d’Amylior Inc. à innover dans le domaine de la mobilité, en créant des solutions technologiques qui améliorent le confort et la qualité de vie des utilisateurs de fauteuils roulants motorisés.

Novel product and prototype development for soft tissue regeneration

Gingival recession affects ~50% of the population and results in the exposure of tooth root surfaces, which leads to an increased risk of dental caries. The gold standard treatment is autologous grafts involving tissue being harvested from the roof of a patient’s mouth, leading to pain and bleeding, the inability to eat, risk of infection, and the tissue that can be harvested can be insufficient, leading to the need for follow-up procedures. Materials on the market have inconsistent clinical outcomes, likely due to the lack of cells. As a result, autologous grafts remain the gold standard, leaving patients and clinicians in search of alternatives. In the proposed study, we will evaluate a tissue-engineered solution as a potential alternative, using a novel biomaterial and stem cells derived from fat tissue. The material will be characterized and subsequently seeded with adipose-derived cells. The resulting capillary/vessel networks will be characterized in vitro. To enable an intra-operative procedure the material will be functionalized, binding the relevant cell types from processed fat. Lastly, the functionalized material with captured fat-derived stem cells will be evaluated in a clinically relevant animal model and compared to the current clinical material standard. With an estimated 5.7M annual gingival graft surgeries in the US alone, this project will take a significant step towards helping the partner organization address clinical and patient demand, by moving closer to commercially viable manufacturing, material safety, and proof-of-concept in a clinically relevant gingival animal model.

CO2 conversion via a zeolite LTA dehydration membrane reactor

Carbon Exel’s mission is to defossilize the hard-to-decarbonize sectors by generating a low-carbon electro-diesel or e-diesel fuel. E-diesel is derived by transforming carbon dioxide (CO2) and green hydrogen (H2) into e-diesel powered by renewable electricity (hydro, wind, etc.). E-diesel releases 80% less CO2 emissions than traditional diesel, making it a viable option to reduce and neutralize emissions to reach net-zero by 2050. This project aims to develop a catalytic membrane reactor composed of Linde Type-A (LTA) zeolite deposited on a porous Al2O3 substrate that will be employed in Carbon Exel’s modular reactor. The LTA membrane will be validated by characterization and reaction stability tests. The LTA membrane will increase the catalytic conversion and product yield by at least 20%.