Making Medical AI Smarter, Adapting Language Models for Real-World Healthcare

This international project brings together researchers from Canada and Japan to improve the accuracy and reliability of artificial intelligence (AI) in healthcare. The goal is to enhance how large language models (LLMs)—the technology behind tools like ChatGPT—respond to medical questions by grounding them in verified facts. At the National Institute of Informatics (NII) in Tokyo, […]

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Common Risk Factors in the Stablecoin Market

This project focuses on understanding what makes the prices of stablecoins (a type of cryptocurrency designed to stay stable) go up or down. Traditional financial models don’t fully explain how these digital assets behave, especially during market changes or when new regulations are introduced. By studying both general market trends and specific factors like liquidity, […]

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Lexical Development in Multilingual Immigrant Children: Cognitive and Sociocultural Influences on English Vocabulary Acquisition

This project explores how multilingual immigrant children aged 8–13 in Canadian ESL support programs acquire English vocabulary during their early years of settlement. Vocabulary development is crucial for academic success, yet many newcomer children face barriers that go beyond language exposure alone. The research investigates how cognitive factors, such as working memory and phonological processing, […]

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Development of non- or minimally toxic marine coating with black Titania

The proposed project will benefit the participating institutions by establishing a new international partnership focused on developing sustainable, non-toxic coatings to combat marine biofouling, an issue with significant economic and environmental implications for industries like shipping and aquaculture. By combining expertise in photoactive materials and microbial-material interface analysis, the collaboration will enhance research capacity at […]

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Multiscale Simulation of Cortical and Hippocampal Dynamics Using Region-Specific Brain Network Models

Recent advances in computational neuroscience underscore the value of biologically accurate models integrating multimodal neuroimaging to simulate brain activity realistically. Deep brain areas like the hippocampus, crucial for memory and cognition, pose challenges for non-invasive study due to their complex dynamics. The Region-Specific Brain Network Model (RSBNM) addresses this by combining Neural Mass Models, high-resolution […]

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Rewiring Time in Brain Models: Anatomically-Grounded Delay Distributions for Multiscale Neural Mass Modeling

This international project brings together top neuroscience teams from McGill University (Canada) and Aix-Marseille University (France) to develop the next generation of realistic brain models. The goal is to improve how computer simulations represent the timing of signals traveling through the brain, which depends on factors like axon length, thickness, and myelination. Current models often […]

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Resonateur à ondes acoustiques de surface transversal (SH-SAW) sans réflecteurs pour la caractérisation biologiques

La technologie de biodétection est essentielle pour les diagnostics médicaux, la surveillance de l’environnement et la recherche biologique fondamentale. Alors que la résonance plasmonique de surface (SPR) offre une détection sans étiquette sensible aux changements d’indice de réfraction et que les capteurs à ondes acoustiques de surface (SAW) excellent dans les milieux liquides et sondent […]

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L2M – BIM-Enabled Multi-Criteria Decision-Making: Towards Efficient Building Element Selection

The project focuses on creating a new software tool that combines multi-criteria decision-making (MCDM) methods with BIM, a 3D digital modeling system used in construction. This tool will assist architects, engineers, and builders in selecting materials and elements by evaluating multiple criteria, such as cost, durability, and their environmental impact. By addressing challenges like too […]

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Automated Ichnofabric Analysis with Deep Learning for Marine Core Research

This project proposes a completely novel workflow to automate the detection and quantification of bioturbation (i.e., biological sediment mixing by infaunal organisms) in deep-ocean sediment cores using the proven capabilities of neural networks in complex image interpretation. The new technique will enable precise, objective, and efficient quantification and identification of bioturbation types caused by infaunal […]

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L2M – BioinformHER

Bioinformatics is fundamental to modern medicine, driving breakthroughs in cancer, pandemics, and disease understanding, however, while demand for this field continues to grow, its workforce still does not reflect the people it serves. Fewer than 20% of bioinformaticians are women, and less than 5.7% are Black [1]. This homogeneity reflects and perpetuates systemic biases across […]

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L2M – NutraMate

The NutraMate project aims to revolutionize prescription management in pharmacies by implementing an AI-driven automation system that replaces traditional manual processes. Our cutting-edge technology will significantly reduce the documentation and data entry time while also having high accuracy and improving patient safety through advanced verification processes. Our product is seamlessly integrated into existing pharmacy workflows […]

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L2M –SynapPlay

This project aims to help older adults and people with neurological conditions such as stroke or Parkinson’s disease stay independent longer by developing a tablet-based digital therapeutic tool called SynapPlay. The platform combines physical and cognitive tasks with real-time feedback to improve balance, thinking skills, and motor control, all from the comfort of home. Through […]

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