L2M – Clinical Trial Recommendation System Using Large Language Model

We are developing a conversational AI system that helps hospitals and cancer centers find the right patients for clinical trials much faster and easier. Currently, research staff spend weeks manually reading through hundreds of pages of patient medical records to see if patients qualify for specific cancer treatment studies, which means many patients who could […]

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L2M – Vira

This research-based project aims to make developing virtual reality (VR) applications faster and easier by using generative AI tools. By streamlining the development process, the project can help both companies and individual developers save time and resources. This is especially valuable for Calgary’s growing community of VR businesses and research labs. Overall, the project supports […]

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L2M – EnerCast

I intend to commercialize a foundation model for forecasting energy production and consumption time series, addressing challenges like renewable integration, storage optimization, and demand-supply balancing. Resources such as HVACs, EVs, ESSs, and solar roofs introduce uncertainty due to temperature sensitivity, price response, and weather variability, making grid management and the transition to smart grids more […]

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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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Adaly.AI Generative AI & Data Science Proposal (OTU)

This project focuses on researching and developing an advanced coordination mechanism between our API layers and LLM infrastructure. The goal is to efficiently access and reason across both structured and unstructured data sources to improve customer’s decision-making processes. Success will be measured by the speed in which that data source can be identified, sourced, and […]

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L2M – Link Between Worlds

Link Between Worlds is a project that combines play therapy techniques and teaching creative expression to Indigenous peoples and communities that typically are not given a voice. The objective of Link Between Worlds, through an intensive/retreat format, is to teach and provide a safe space for indigenous people to grow and learn skills in storytelling/filmmaking, […]

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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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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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L2M – Patient Repositioning Device

Healthcare workers face increasing challenges in protecting themselves from injuries caused by physically demanding tasks. One of the most injury-prone activities is repositioning patients in bed, such as sliding them up or down the mattress or turning them onto their side for sling placement and backside care. These tasks often require significant manual effort and […]

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