Structurer le changement : vers un cadre d’implantation de la plateforme FLOW

Ce projet vise à soutenir l’implantation d’une technologie d’intelligence artificielle développée par Flow Factor, utilisée dans le domaine de la santé mentale pour automatiser certaines tâches administratives et cliniques. Dans un contexte aussi sensible que celui de la relation d’aide, l’introduction de nouvelles technologies peut susciter des préoccupations ou des résistances. Le projet consistera donc […]

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Enhancing TMJ Disorder Diagnosis via AI-Assisted Segmentation

Temporomandibular Joint Disorder (TMD) is an umbrella term for diseases that affect the jaw. It is a common but often underdiagnosed condition that can cause significant jaw pain, limited movement, and long-term oral health issues. Accurate diagnosis relies heavily on the precise identification of tiny jaw structures in medical imaging, a task that remains challenging […]

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Development of multimodality imaging and advanced AI/ML algorithms for point-of-care and drug discovery applications

The proposed international research collaboration project aims to develop accurate and efficient image processing algorithms for advanced imaging instrumentation technologies. The overarching goal of the project is towards fully automated microscopy technologies with many strategically important applications for both DGIST (Korea) and McMaster (Canada) such as point-of-care diagnosis in remote communities and drug discovery. The […]

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Smarter Imaging for Everyone: Adapting AI-Based Diffusion MRI Analysis to Low-Field Scanners

This project tackles a major challenge in modern brain imaging: advanced techniques like diffusion MRI and tractography are powerful tools for studying conditions such as multiple sclerosis, dementia, and brain cancer, but they rely on expensive, high-resolution scanners that are often unavailable in routine clinical settings—especially in underserved or rural communities. These methods also struggle […]

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Adaptive Human–LLM Teaming for Scalable Cybersecurity at eSentire

This project will explore how AI can best complement human expertise in cybersecurity operations. The intern will collaborate with industry professionals at eSentire to study how tasks are currently performed, develop lightweight AI-based tools to support key workflows, and design a method to assess the impact of these tools in real-world conditions. The goal is […]

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Generative AI in Corporate: Do Male and Female Leaders Respond Differently?

This project will study how male and female executives differ in the adoption of artificial intelligence (AI) technologies. I use the launch of ChatGPT as the big technological event to understand how executives communicate and discuss the adoption to generative AI. I then analyze how these differences affect how investors react in the stock market. […]

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L2M Validation / Qc Automne 2025 / AsbabAI is a novel platform that evaluates the causality of deep learning models to improve their explainability and robustness using causal inference,a key requirement in regulated sectors such as healthcare and finance

Artificial intelligence (AI) is increasingly used to make high-stakes decisions in fields like finance, insurance, and healthcare. However, most of AI systems function as “black boxes,” producing results without clear explanations. This lack of transparency can lead to serious consequences, such as denying loans to creditworthy individuals or making unfair risk assessments. The AsbabAI aims […]

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Scalable Quantum-Enhanced Generative Models for Drug Discovery: Extending QCBM with NQS and CUDA Quantum for Multi-target Inhibitor Design

This project proposes a scalable quantum-enhanced generative model for drug discovery, targeting the design of KRAS inhibitors through the integration of Neural Quantum States (NQS), Quantum Circuit Born Machines (QCBMs), and CUDA Quantum acceleration. By replacing traditional quantum circuits with adaptive NQS representations and extending QCBM capacity to 32 qubits, the framework enables more expressive […]

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IA Conversationelle pour l’apprentissage du français

Francoflex offre une IA conversationelle qui aide à l’apprentissage du français au travail. Elle aide à l’intégration des travailleurs dont la première langue n’est pas le français. Pour assurer de l’efficacité du modèle de reconnaissance audio et un bon apprentissage, il faut entraîner un modèle capable de reconnaître des accents forts dans différentes langues natives […]

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Reliable, Continuous, and Safe Updates of Digital Twin Services

The intern Mr. Andersen will travel from Aarhus University, Denmark to Polytechnique Montréal, Canada, to research the engineering of Digital Twins (DTs). DTs are virtual representations of physical systems, like the concrete mixing machine which is the focus of this project. Mr. Andersen will work with Prof. Bentley Oakes on the research problem of ensuring […]

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Adoption of Frictionless Retail Technologies: Key Factors and Impact

This project will study consumer experience and reaction to shopping in a frictionless or autonomous store environment. Fricitonless stores offer a no-cashier shopping experience using advanced technologies such as computer vision , weight sensors and light sensors. The adoption of some or all aspects of this technology has significant potential benefits for retailers in terms […]

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L2M Validation / Qc Automne 2025 / NodusAI

Les gouvernements, hôpitaux et banques détiennent d’immenses volumes de données précieuses, mais les lois strictes sur la confidentialité et les risques de sécurité rendent toute collaboration presque impossible, freinant l’innovation et limitant la performance des modèles d’IA. De ce fait, les hôpitaux ne peuvent pas bénéficier de modèles de diagnostic partagés et entrainés par plusieurs […]

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