TRLUP – Construction Tracker (Dylan Haussecker)

This project focuses on developing a durable, low-power tracking device for small construction equipment, enabling contractors to automatically monitor machine usage, idle time, and location. This technology reduces theft, cuts down on fuel waste, and eliminates manual tracking, helping improve productivity across underserved construction SMEs across Canada. Over four months, the intern will enhance the […]

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TRLUP Ergonomic Shovel

The proposed project is an ergonomic manual shovel that aims to decrease stress and injury. The project aims to improve manual transfer of materials for farmers, construction workers, landscapers, and homeowners. The goal of this project is to improve the technological readiness of an initial prototype to bring it closer to commercialization.

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TRLUP – Real-Time Electromagnetic Sensing for Water Cut Monitoring

This project aims to develop a sensor that uses electromagnetic waves to monitor the water content (water cut) in oil production systems in real time. The sensor has already been tested in a lab environment and shows promising results in detecting changes in water levels in oil–water mixtures. Through this project, I will work with […]

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TRLUP – SolarEvo Shingles

This project focuses on developing solar shingles that act as both a roofing material and a clean energy generator. The goal of this project is to refine the product design, build a go-to-market plan, and create a path to commercialization. These shingles are made from recycled materials and designed to be durable, weather-resistant, and visually […]

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TRLUP – Biomass-Derived Carbon-Negative Solvent and Biochar: Product Development Roadmap and TRL Advancement

This project focuses on advancing a carbon-negative biomass conversion technology that produces two high-impact products: a bio-based solvent for industrial and energy applications, and hydrochar for use as a regenerative soil amendment. Over four months, the intern will support the development of application-specific product formulations, engage with potential customers and offtakers to validate product-market fit, […]

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TRLUP – Advanced Microfluidic System for On-Site Milk Testing

We are developing a novel, low-cost microfluidic detection chip for rapid bacterial detection in milk, addressing critical needs in both maternal health and the dairy industry. Bacterial contamination in milk poses significant health and economic risks, from mastitis in breastfeeding mothers to large-scale spoilage in dairy production. Current diagnostic methods, such as culture-based assays, are […]

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TRLUP – From Sparse Data to Actionable Insights: A Transit Ridership Platform

Public transit agencies in Canada often struggle to accurately measure and predict ridership patterns due to limited and incomplete data. Traditional methods typically rely on a single data source, which makes it hard to get a clear view of how people move across the transit network. Without this information, agencies find it challenging to match […]

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TRLUP – Advanced UAV System for Indoor and Confined-Space Navigation

We are developing a compact, autonomous unmanned aerial vehicle (UAV) platform engineered specifically for operation in GPS-denied, confined, and hazardous environments. Designed for use in search and rescue (SAR), industrial inspection, infrastructure monitoring, etc., the platform addresses key limitations of conventional drones and ground robots, which often struggle with maneuverability, stability, and situational awareness in […]

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Automating Web Application Security Testing for Enhanced Efficiency and Coverage

Forward Security is a cybersecurity firm focused on helping clients identify and mitigate application-level vulnerabilities. One of their current innovation priorities is improving the efficiency and accuracy of manual security testing practices by leveraging automation, particularly in alignment with the OWASP Application Security Verification Standard (ASVS), a globally recognized framework for secure software development and […]

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Augmenting NVD-based Attack Path Generation with New Factors for Cloud Environments

To quantitatively assess the security level of a cloud environment, a common method is to construct an attack graph which tracks a potentail attacker’s moves through interconnected computing systems by exploiting vulnerabilities of each system, one after another. The state-of-the-art automatic attack graph generation suffers from two limitations: 1) low quality or inconsistency of vulnerability […]

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