Projets novateurs réalisés

Plasma Proteomic Profiling of Severe Traumatic Brain Injury In Pediatric Patients

Severe traumatic brain injury (sTBI) is a leading cause of mortality and disability in pediatric populations. Surviving patients often face long-lasting neurological deficits exacerbated by primary and secondary injury, necessitating further advancements in prognosis and understanding of sTBI mechanisms. Our project aims to address this issue by identifying differentially expressed proteins present in pediatric sTBI patient plasma samples. In combination with bioinformatics and machine learning techniques, we seek to correlate findings with clinical variables to improve prognosis, as well as to identify enriched cellular pathways contributing to sTBI pathophysiology. Through cooperation with the Children’s Health Research Institute, this project will help to improve productivity of our partner organization by addressing this knowledge gap.

Decoding the Developmental Gene Regulatory Mechanisms of Schizophrenia and Bipolar Disorder Using Genetics and Single-Cell Epigenomics Data

This research project will explore how certain genetic differences may increase the risk of developing mental health conditions like schizophrenia and bipolar disorder. These conditions often begin in the teenage years or early adulthood, but researchers believe that early brain development, before and after birth, plays a key role. The intern will use powerful computer tools to study large public datasets that show how genes are turned on and off in different types of brain cells during early development. The goal is to find out how specific genetic changes might affect brain function in ways that lead to mental illness. The project is based at the Children’s Health Research Institute (CHRI), which focuses on improving child and youth health. This work will support CHRI’s mission by helping scientists better understand the early causes of psychiatric disorders, which could lead to earlier diagnosis, better treatment, and improved mental health outcomes for young people.

Laboratory-Based Transmission Electron Microscopy Technique to Study Electrochemical CO2 Conversion under Operating Conditions

The growing urgency to combat climate change has driven major interest in technologies that can capture and convert carbon dioxide (CO2) into useful fuels and chemicals. Electrochemical CO2 conversion is a focus area in carbon capture and utilization storage (CCUS) as a potential disruptive technology for a circular carbon economy, including decarbonization of chemical manufacturing, valorization of carbon emissions, and storage of renewable energy in chemicals/fuels. Widespread deployment of CO2 conversion technologies is hindered by poor energy conversion efficiencies and operational lifetimes—performance capabilities that are ultimately dictated by the utilized materials, including the catalysts, electrodes, and polymer electrolyte membranes. Methods are needed to visualize the dynamic CO2 conversion processes. This project is leveraging new, state-of-the-art in situ/operando electrochemical transmission electron microscopy (TEM) techniques, which enable nanometer-scale imaging of the morphology of catalysts/ electrodes under electrochemical CO2 conversion conditions in real-time. This will provide insights into catalytically relevant structures and properties that will inform the development of next-generation CO2 conversion materials to address performance and stability challenges. The outcome will be made-in-Canada clean energy materials and technologies that will contribute towards achieving Canada’s ambitious pledge to be net-zero carbon emissions by 2050, strengthening its competitiveness in the critical clean energy sector.

Robitaille Équipement : Intégration de l’intelligence artificielle dans le processus de prix de vente

Robitaille Équipement : Intégration de l’intelligence artificielle dans le processus de prix de vente
Principales activités du partenaire :
Robitaille Équipement inc. fournit à ses clients, à travers la province de Québec et les maritimes, des pièces d’usure pour la machinerie lourde et des pièces et équipements pour le déneigement.
Qu’il s’agisse de pièces ou encore d’équipements spécialisés pour les petits et grands véhicules lourds, Robitaille s’assure d’offrir ce dont les clients ont besoin grâce à son inventaire exhaustif et son réseau de fournisseurs de première qualité.
La tâche principale de Robitaille Équipement, considérant la mission de l’entreprise, est de fournir des équipements et des produits avec des prix adaptés à différents types de clientèles.
Problématique et avantages escomptés du projet :
L’entreprise Robitaille Équipement souhaite moderniser le processus d’estimation du prix de vente en intégrant l’intelligence artificielle (IA) afin d’optimiser et de standardiser la gestion des prix. Actuellement, l’entreprise s’appuie sur un système de tarification flexible, tenant compte de multiples facteurs :
? La taille et le statut du client (revendeur, fabricant ou utilisateur final).
? La concurrence sectorielle.
? Les spécificités locales du marché.
De plus, les prix sont déterminés selon les critères suivants :
? Des listes tarifaires structurées par niveaux de marge.
? Un calcul global définissant un tarif de base.
? L’expertise des vendeurs qui ajustent les prix en fonction de chaque situation.
Ce modèle, développé au fil des ans, n’est pas sans failles. En effet, il soulève parfois des enjeux stratégiques, corporatifs et de formation du personnel de vente :
? Une courbe d’apprentissage complexe et rapide pour nos nouveaux vendeurs, qui doivent assimiler une logique tarifaire parfois implicite.
? Des écarts de prix non négligeables entre les succursales, qui peuvent générer de l’incompréhension et de la frustration chez les clients, et ternir l’image professionnelle de l’entreprise.
La politique commerciale de Robitaille Équipement l’entreprise doit être cohérente et transparente, pour l’entreprise comme pour ses clients. La solution proposée dans ce projet devra renforcer la fiabilité, l’équité et la performance de l’entreprise sur l’ensemble du réseau de distribution.

Pratiques et conditions favorables d’un accompagnement par des professionnels des services éducatifs de Centres de services scolaires lors de la réintégration d’un élève ou lors de son arrivée/sa présence en classe spéciale

Ce projet de recherche vise à mieux comprendre comment les professionnels (p. ex., des conseillers
pédagogiques ou des psychologues) qui accompagnent des équipes-écoles (p. ex., des directions d’école ou des
personnes enseignantes) peuvent les aider à adopter de nouvelles façons de répondre aux besoins des élèves
ayant un handicap ou des difficultés d’adaptation ou d’apprentissage (EHDAA). En évaluant une démarche de
recherche-action déjà en cours, le projet permettra d’identifier ce qui facilite ou freine les changements de
pratiques, afin de soutenir les équipes-écoles dans leurs interventions auprès de ces élèves. Ce projet sera
bénéfique pour le partenaire, en améliorant la qualité de l’accompagnement offert et en aidant l’organisme à mieux
déployer ses ressources dans d’autres régions du Québec. Il contribuera aussi à former une stagiaire aux enjeux
importants du système scolaire, comme l’inclusion et la réussite éducative, tout en renforçant les liens entre les
milieux de recherche et les milieux de pratique.

Fault-Seal Analysis at Aquistore

Faulting might be affecting the flow of injected CO2 into the subsurface at the Aquistore Carbon Capture and Storage facility in southeastern Saskatchewan. 3D seismic data indicate that faulting affects the Deadwood Sandstone injection target approximately 100 m to the west of the injection well. The seismic data cannot however image all the structural complexity that is likely to be associated with the faulting. As such, predicting how or if that faulting affects the movement of CO2 is problematic; the fault could act as a conduit or a barrier.

This project supports a masters student in Earth Sciences at Western University. The student will adapt a seismic- and outcrop-based workflow, known as fault-seal analysis, that is used in the petroleum industry predict the effects of faults on the movement of gases and fluids. The product will be a 3D model of the stratigraphy and structure near the injector well. The model can be employed by reservoir engineers to simulate the movement of CO2, thereby allowing PTRC and its associates to make improved management decisions.

Modelling pathways of dredged sediment placed on Sturgeon Bank

Sturgeon Bank is a Wildlife Management Area within the unceded traditional territories of the Coast Salish peoples, and west of the City of Richmond, British Columbia. Sturgeon Bank is primarily comprised of intertidal marsh, mud flats and open water, and provides several ecological and coastal risk mitigation benefits. However, monitoring indicates that Sturgeon Bank’s salt marsh areas have receded by more than 30% since 1986. The Sturgeon Bank Sediment Enhancement Pilot Project (SBSEPP) is a field level pilot project designed in part by the Mitacs partner organization to address the observed marsh recession. The SBSEPP involves the placement of sediments on the mudflats, with the premise that the sediments will be transported onshore by waves and tidal circulation, supporting marsh restoration. Beginning in 2021, three sediment deposits have been completed at Sturgeon Bank, and large quantities of data have been collected to monitor the site’s progression. The Mitacs intern will explore the collected data using data analysis and numerical modelling software to provide the Mitacs partner organization with insight into the sediment transport processes observed in the SBSEPP. Such insight is crucial in potential upscaling of project components for marsh restoration throughout the Fraser Delta and throughout Canada at large.

Advancing Mass Timber Durability through Hygrothermal Field Measurements and Predictive Modelling

This project aims to make mass timber buildings, a sustainable alternative to concrete and steel, even more reliable. While mass timber is great for the environment, we don’t fully understand how it handles moisture over time, which can affect its durability. Our project will tackle this by using advanced sensors to monitor a new mass timber building under construction in Toronto, collecting real-world data on how the wood reacts to moisture during construction and one people occupy the building. This will help our partner, Synergy Partners Consulting Ltd., a leading building science company, to better predict and manage moisture risks. The outcome will be more durable and sustainable mass timber buildings, strengthening Canada’s leadership in green construction and ensuring healthier environments for everyone.

Conceptual design and dynamics modelling of tethered solar shield

The objective of the proposed project is the development of a tethered solar shield to reduce the amount of solar radiation to Earth, thereby opening up the possibility to combat global warming. The intern will work on the following two phases. The intern will begin by carrying out literature review on the designs proposed for solar shields to date, and tethered systems deployed in the solar system. The intern will carry out basic analysis to determine the mass and tether length requirements on the shield and the ballast body. Once the basic system design has been established, the intern will work on formulating the dynamics model of this system. Different modeling options will be considered for the shield, the ballast body and tether, ranging from point mass to flexible-body models. The relevant perturbations that are important for the particular system will be assessed and suitable models for those perturbations will be identified. The formulated model will be implemented in Matlab and dynamics analysis will be carried out to study the response of the system. This work will provide the necessary insights into the requirements for the next phase of the project which is the control of the tethered solar shield.

Adaptive OCR for Structured Data Extraction in Technical PDF Documents

The proposed research project aims to digitize information currently locked in image-only PDF files, which are common in government and engineering sectors but are difficult to search and analyze. These documents, which often include technical drawings, forms, and reports, cause inefficiencies and errors due to the need for manual review. To address this, the project will develop an adaptive system using advanced image recognition (OCR) and vision-language models to accurately extract structured data. This involves creating algorithms for content and layout analysis and building a user-friendly software tool to help people upload, view, and export this extracted information. For the participating institutions, the University of Alberta in Canada and the National Taiwan University of Science and Technology, this project strengthens their ongoing collaboration in digitalizing building processes and advances data-driven design and construction. The project’s outcomes will streamline document workflows, reduce manual effort, and improve data analysis for both academic research and real-world applications in engineering and government.

From Agents to Teams: Optimizing the Creation of LLM-based Multi-Agent Systems

As multi-agent systems become more complex, improving how Large Language Model (LLM)-based agents work together is increasingly important. This research focuses on creating reusable design patterns and adaptive coordination strategies to boost collaboration and system performance. Blend360 is an AI service provider that builds advanced solutions for clients in sectors like finance, healthcare, and consumer goods. The company is exploring the use of multi-agent systems in its AI toolkit. These systems break down client problems into smaller tasks that multiple AI agents can solve together. However, there are key challenges preventing their smooth deployment in real-world applications. First, current systems often use static workflows (such as sequential or hierarchical setups), which limit flexibility in dynamic environments. Second, there is a lack of reusable design patterns to guide how agents interact, making these systems hard to build and maintain. Third, existing evaluation methods focus only on whether a task is completed, ignoring how well agents collaborate, how much each contributes, or how efficient their communication is. This research will help address these issues and directly support the development of smarter, more scalable agentic AI tools for Blend360’s clients.

Cartographier l’écosysème bioalimentaire du Saguenay–Lac-Saint-Jean

Le projet vise à développer un portrait clair et actuel des organismes qui soutiennent le développement du secteur agroalimentaire au Saguenay–Lac-Saint-Jean. Bien que la région soit riche en ressources, en expertises et en initiatives, il est parfois difficile pour les entreprises de savoir à quelle porte frapper pour obtenir du soutien. Plusieurs organismes travaillent fort pour aider les producteurs, transformateurs ou entrepreneurs, mais un manque de coordination rend les démarches parfois complexes ou inefficaces. Ce projet vise à cartographier l’écosystème bioalimentaire régional : identifier qui fait quoi, où, avec qui, et dans quels domaines. En dressant ce portrait détaillé des organisations et de leurs liens, on pourra repérer les doublons, les manques, mais aussi les occasions de collaboration. Cela permettra aux organismes de mieux orienter les entrepreneur·e·s, de renforcer la complémentarité entre les services offerts et d’augmenter l’impact des actions menées dans la région. À long terme, ce projet aidera à bâtir un système alimentaire plus cohérent, plus inclusif et plus durable pour toute la population du Saguenay–Lac-Saint-Jean.