L2M-Augmented Reality-Based Training System using Multimodal Language Model for Context-Aware Guidance and Activity Recognition in Complex Machine Operations

Many industrial companies still rely on traditional training methods and struggle to keep up with evolving skill requirements. These conventional approaches, such as manuals, videos, and classroom instruction, are ineffective in delivering the hands-on skills required to operate complex machinery. Our project introduces an Augmented Reality (AR) based training platform powered by Multi-Large Language Models […]

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L2M – SmartRail Hotspot Analytics Using Fiber Sensors

The proposed project will use existing telecom fiber installed alongside railways to monitor the physical condition of Canada’s aging rail network in real time. By attaching small Fiber Bragg Grating (FBG) sensors at key stress points—such as bridges, track curves, and transitions—the system will continuously measure strain, temperature, and wheel impacts without adding new cabling. […]

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L2M-Designing a Stable CD19 Protein Mimic for CAR T-cell Therapy

CAR T-cell therapy is a type of immunotherapy that displays remarkable potential to treat B-cell cancers. In this treatment, a protein on the surface of B-cells called CD19 is targeted, allowing for the specific killing of B-cells in patients. However, CD19 is a “difficult to express” protein, characterized by high levels of aggregated protein and […]

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L2M – Smart Concrete for Structural Health Monitoring (SCSHM)

This project explores the development and application of smart concrete an innovative construction material enhanced with advanced sensing and self-monitoring capabilities. Unlike conventional concrete, smart concrete integrates conductive or functional additives that enable it to detect stress, strain, cracks, and environmental changes in real time. This technology addresses critical global challenges by improving infrastructure durability, […]

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L2M – Integrated Data Science Platform for Complex Spatiotemporally Resolved Biomedical Applications

Reliable annotations set critical ground truths for modern data science initiatives. In life sciences, however, large volumes of physiologic data streams produce computational bottlenecks that hinder this workflow. A researcher’s only viable alternative is to adopt a DIY approach, exporting data to separate coding environments. This fragments the analysis from the visual context and corrodes […]

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L2M – Phase-noise reduction technique for microwave oscillator

The proposed project will explore how our new low-noise microwave oscillator technology can meet real needs in radar and communication systems. We will interview industry experts to understand what performance, environmental reliability, and cost requirements are most important for practical use. At the same time, we will work with manufacturers to see whether our design […]

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L2M-Body-Safe Wearable Antenna Technology for Reliable Health Monitoring Devices

This project focuses on validating the real-world potential of a new wearable wireless sensing technology designed for safer and more reliable on-body communication. Many current wearable devices struggle with performance instability and safety issues due to strong interaction with the human body. This project explores an alternative design approach that minimizes unwanted radiation into the […]

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Studying formation and destabilization mechanisms of pickering emulsions encapsulated with bioactive compounds via confocal/STED microscopy

Bioactive compounds are naturally occurring food components that can promote human health, but they often lose their effectiveness because of problems such as low stability, low solubility, and poor absorption in the body. Encapsulation in emulsions is one promising way to protect these compounds and help them reach their target tissues, but the main limitation […]

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Reinforcement Learning Approach for Improving the Dynamic Response of Frequency in Low-Inertia Islanded Active Grids

The structure of power grid is changing due to the integration of distributed energy resources, especially the renewables and energy storage. These resources with power electronic converters provide additional controllability to grid operators and provide the capability of operating the interconnected gird as several active decentralized systems for enhancing system reliability and maintaining system resiliency. […]

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TRLUP – ML Insights and Metrics

More than 90% of pharmaceuticals fail to impact fail to pass regulatory approval due to toxicity or lack of effectiveness. 50% of those failures have the potential to impact patient lives and existing therapeutics can be repurposed to expand therapeutic options if they can be delivered in smaller dosages to where they are needed most. […]

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TRLUP – Intelligent Automation of Phased Array Ultrasonic Testing for Quantitative Defect Characterization and Evaluation

This project develops an intelligent automation system to revolutionize how we inspect safety-critical components in industries like aerospace, energy, and manufacturing. It focuses on Phased Array Ultrasonic Testing (PAUT), a powerful but skill-dependent method for finding hidden flaws in materials. Currently, interpreting PAUT data demands highly trained technicians to analyze complex signal patterns and images. […]

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