L2M – Development of a Rapid Molecularly Imprinted Polymer (MIP)-Based Diagnostic Device for Differentiating Bacterial and Viral Infections via Dual Biomarker Detection

We are developing a rapid, low-cost diagnostic device that helps healthcare providers quickly determine whether an infection is bacterial or viral, leading to better treatment decisions and reduced antibiotic misuse. This project will explore real-world demand for the device, evaluate its competitive edge, and refine its market strategy. Through the Lab2Market Validate program, Edmonton Unlimited […]

Read More
L2M – TraffiCore

During the course of this project, the main focus will be on the market research aspect of TraffiCore, a traffic monitoring and control automation startup which aims to provide traffic managers and controllers with a useful tool that can automatically perform the repetitive and mundane tasks that are usually perfomed manually and suboptimally. The intern […]

Read More
L2M – Digital Twin for Real-Time Cardiac Arrest Risk Monitoring

This project has developed a real-time digital monitoring system that identifies people at risk of sudden cardiac arrest by analyzing their heart signals (ECGs). By combining a machine learning model with cloud-based technology, the system automatically updates each patient’s status and sends alerts if a risk is detected. This enables the partner organization to provide […]

Read More
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 […]

Read More
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 […]

Read More
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 […]

Read More
A wireless headset for power-aware EEG/non-EEG signals processing and seizure warning

Epilepsy is a debilitating neurological disorder affecting approximately 50 million people worldwide (World Health Organization). This project proposes to develop a SMART (Seizure Monitoring At the Right Time) Headset for these patients to monitor their brain signal and track their movements, heart rates and breathing patterns. This headset will have new types of sensors suitable […]

Read More
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 […]

Read More
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, […]

Read More
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 […]

Read More