L2M – Augmented Reality-Enhanced Precision Robotic Manipulator Simulation and Training System

The global manufacturing sector is shifting towards high-mix, low-volume (HMLV) production. While large corporations can invest in advanced automation, Canada’s small and medium-sized enterprises (SMEs) face a significant “adoption chasm.” This gap is driven by prohibitive upfront capital costs for robotic systems, a critical lack of in-house programming and maintenance expertise, and the financial risk […]

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A novel scaffold for tympanic membrane repair

The ability to hear, and the quality of our hearing, depends on the health of the eardrum. Eardrum perforations due to diseases and accidents can be treated using grafts, such as autologous grafts, allografts and xenografts. These replacements suffer from various limitations such as donor site morbidity, long operation time and healing time, and risk […]

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L2M – Artificial Intelligence Enabled LED Lighting

Cities and lighting companies currently spend weeks and tens of thousands of dollars to create new plastic lenses every time a different streetlight beam is needed or when light pollution must be reduced. Our design is a simple film that sticks to the front of an LED and updates the light patterns quickly—no new lens […]

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L2M – AR-CAD: An Augmented Reality-based Computed Aided Design Tool

This project will advance the development of AR-CAD, an innovative augmented reality (AR) design tool that allows engineers to create and manipulate 3D models in real-world scale using a headset. Unlike traditional CAD tools that rely on 2D screens and complex interfaces, AR-CAD enables intuitive, hands-on design, helping users visualize and validate parts more quickly. […]

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L2M – Healthcare Systems Performance Optimization using Reinforcement Learning-Enhanced Functional Resonance Analysis Method

Healthcare systems operate as complex socio-technical environments, involving unpredictable interactions among patients, clinicians, technologies, administrators, and institutional policies. These systems are often under significant pressure to improve performance, reduce costs, and enhance patient safety—yet they frequently lack the tools to simulate the consequences of operational decisions before implementation. Traditional approaches like retrospective analysis or static […]

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L2M – Artificial Intelligence Integrated Medical Media Suite

The Artificial Intelligence Integrated Medical Media Suite (AIIMMS) is a smart, AI-powered crash cart designed to support emergency response teams during coding events. By integrating live video, audio, patient biometrics, and patient electronic health record data into a centralized interface, AIIMMS can help reduce the cognitive load and enhance clinical decision-making in real time. The […]

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L2M- AI Lab Assistant

This project initially targets drug discovery labs, with long-term plans to expand into broader biomedical research. As AI becomes integral to scientific work, we aim to build a custom AI assistant that goes beyond basic chat support, capable of running code, executing ML/DL pipelines, and assisting with lab-specific tasks.

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L2M – Neuro-integrated carbene coatings

Brain-Computer Interfaces (BCIs) are a revolutionary technology with the potential to significantly improve the lives of individuals with neurological disorders, but their long-term use is severely limited because the implants often fail within a short period. This project, a collaboration with Queen’s University, aims to solve this critical problem by developing and commercializing “Neuro-Integrated Carbene […]

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TRLUP – Stretcher Aid

Our Stretcher Aid is a new approach to increasing ergonomics and overall care for both caregiver and patient. Our product is designed to create more usable working space for Nurses and Caregivers, allowing for more ergonomic choices during emergency situations. With the support of New Ventures BC, we will be able to utilize the resources […]

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L2M – OmniPave

OmniPave is a research-based concept from the University of Alberta that tackles this by fusing satellite radar, AI-analyzed bus-camera footage, targeted drones, and citizen reports into a real-time map that spots micro-cracks within days, before they expand into potholes. This proactive approach can shift cities toward low-cost crack sealing instead of expensive patching. However, major […]

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L2M – Developing Machine Learning Models to Accelerate our In-Vivo Creatinine and Potassium Biosensor Development

Many people with heart failure are not prescribed the full set of guideline-directed medical therapies (GDMT), which can shorten their lifespan and reduce quality of life. One major reason is the difficulty and inconvenience of regularly checking potassium and creatinine levels, which are needed to safely adjust these medications. To address this, we are developing […]

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