Innovative Projects Realized

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 body while maintaining accurate sensing and communication capabilities.

Over a four-month period, the project will involve customer discovery, market research, and business model development to understand where this technology can create the most impact — particularly in healthcare monitoring, rehabilitation, and smart wearable applications. The goal is to bridge the gap between academic research and real-world application by assessing user needs, industry interest, and commercialization pathways.

This work supports the development of safer, more efficient wearable technologies and contributes to Canada’s innovation ecosystem by advancing research translation into practical solutions.

L2M – AI-powered Vision-based Robotic System for Autonomous Waste Sorting and Recycling

Waste sorting today is inefficient and relatively expensive since current systems can’t achieve full autonomy. Our project introduces a practical solution that combines AI-powered vision-based object detection with low-cost robotic manipulators to automatically detect and sort waste streams in real time. This innovation reduces hardware and maintenance costs, minimizes the labor reliance, and greatly enhances the overall efficiency. By embedding robotics and AI into waste processing, we deliver a reliable and economically accessible recycling approach that promotes the circular economy and reduce landfill dependency.

L2M – Molecularly imprinted polymers optimized by Hansen solubility parameters for the extraction of phenolic compounds from water samples and water safety monitoring by LC-MS

Monitoring water quality is essential for protecting public health and the environment, yet many harmful pollutants remain difficult and expensive to detect. Among them, phenolic compounds commonly released from industrial activities are persistent, toxic, and often found in Canadian water systems at levels that require advanced laboratory testing. Unfortunately, current sample-preparation methods used to extract these pollutants from water are slow, costly, and not selective enough to reliably detect them at trace levels. These limitations create challenges for environmental labs, municipalities, and industries that are responsible for water safety monitoring.

This project aims to address these challenges by developing a new, more efficient extraction technology using Molecularly Imprinted Polymers (MIPs). These are synthetic materials designed with highly specific “binding sites” that recognize and capture phenolic pollutants, functioning like a lock-and-key system. Unlike conventional approaches, MIPs can provide stronger selectivity, better sensitivity, and lower cost over time because they require less solvent and preparation.

A key innovation in this project is the use of Hansen Solubility Parameters (HSPs), a scientific framework that predicts how polymers and solvents interact. By applying HSPs, we can design MIPs in a more accurate and data-driven way that are better suited for real-world water testing.

L2M – GutSight

This project will help develop GutSight, a new test to monitor inflammation in people with inflammatory bowel disease (IBD) without relying only on colonoscopies. Over four months, I will improve the way we measure gut biomarkers, strengthen the computer model that predicts disease activity using data from 400 patients, and do basic research on how this test could fit into real hospital and lab routines. The partner organization will benefit by getting a clearer picture of whether this test is practical, useful for doctors and patients, and worth developing further as a future product.

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 can be produced using standard industrial materials and assembly methods. Our project aligns with the strategic value of North Forge as it supports advanced hardware startups from prototype to production.

Microbubble-enhanced cold plasma activation for treatment of wastewater from food processing

To address the challenge of treating wastewater from food processing industries, researchers at the University of Alberta have developed an innovative, chemical-free technology using plasma-activated microbubbles. To improve this system for large-scale use, a postdoctoral researcher will join a world-leading fluid dynamics group at the University of Twente in the Netherlands. This international collaboration will use the Dutch team’s advanced diagnostic tools to reveal exactly how bubble behavior and water flow affect the purification process. This partnership is a key step for optimizing a sustainable Canadian technology, allowing the Dutch team to apply its fundamental expertise to a critical environmental problem, and ultimately strengthening Canada’s innovation capacity.

Santevia Water Systems Inc. – Designing Performance-Driven Digital Content to Enhance Marketing Innovation

Santevia Water Systems Inc. is a Delta-based organization that designs and manufactures mineralized alkaline water filtration systems that promote wellness and sustainability. As a growing Canadian brand competing in the global wellness and home water filtration market, Santevia continuously strives to connect with health-conscious consumers through engaging, educational, and visually appealing digital content. However, the organization faces a key innovation challenge in transforming its creative production process into a data-informed, performance-driven system that not only reflects brand storytelling but also maximizes measurable marketing outcomes across platforms such as Meta and other digital channels. The current creative process, while effective in producing high-quality assets, relies heavily on traditional design and brand alignment practices without fully integrating real-time performance analytics or iterative design experimentation into content development.

Development of Low-Loss, High-Finesse Nanofiber Optical Resonators for Distributed Quantum Computing

There is a significant global effort to develop fault-tolerant quantum computers, with a leading strategy being the creation of modular, distributed quantum networks. This approach requires high-fidelity “quantum interconnects” to link individual quantum processors. This project proposes to fabricate and optimize the fundamental component for these interconnects: ultra-low-loss, high-finesse nanofiber optical resonators. This will be achieved by using the specialized heat-and-pull fabrication process pioneered at Waseda University. These high-quality resonators are essential hardware for future scalable quantum computers and networks. Both Concordia University and Waseda University will benefit from the project. Concordia will gain direct access to Waseda’s world-class facilities and the critical know-how of this fabrication technique, which is currently unavailable at the home institution. Waseda University will benefit from the intern’s direct contributions to their ongoing research in nanofiber optimization, which is part of a national-level JST Moonshot program. This project will establish a new, foundational collaboration, paving the way for future joint publications and international projects.

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 scientific impact due to a lack of standardization and reproducibility.

To address this, we offer an interactive analysis platform specializing in large physiologic data streams. The software utilizes multi-resolution charting to enable instant visualization of massive datasets and features a dedicated annotation management system to ensure rigorous, standardized labeling. Uniquely, it integrates directly with user-configured IDEs to merge visualization with real-time code experimentation.

This project is positioned to capture a widening market gap. While the post-ChatGPT AI boom created vast tooling ecosystems for enterprise data science, academic and independent researchers remain underserved by rigid, incumbent tools. Through this internship, the intern will validate product-market fit to capture this high-value research market. Supported by North Forge, this project aims to accelerate the commercialization of Canadian intellectual property, fostering economic development by delivering a solution that restores precision and scalability to physiological research.

Metis Family Services – Digital Transformation of HR File Systems: Designing and Implementing a Compliant HRIS

Métis Family Services is a delegated child and family services agency that provides culturally grounded safety, support, and community services to Métis children, youth, and families across Surrey and the Greater Vancouver region. As the organization expands its programming and workforce, it faces a critical innovation challenge: the transition from a paper-based human resources file system to a fully digital, compliant, and configurable Human Resource Information System (HRIS). The current physical HR file structure limits operational efficiency, data accuracy, and timely access to information across departments, creating barriers to evidence-based decision-making, workforce planning, and organizational growth. Because this transformation requires a comprehensive review of existing processes, analysis of gaps, configuration of a customized HRIS, and development of a structured transition plan, the work goes far beyond routine administrative duties. Instead, the project requires applied research, system evaluation, and the design of new digital workflows that will fundamentally improve how the agency manages employee information. This innovation initiative demands expertise in HRIS systems, data management, change management, business process mapping, compliance requirements, and the ability to translate technical system configurations into practical, user-friendly tools for staff. By conducting a detailed review of current HR file practices, identifying pain points, redesigning digital file structures, and configuring a customized HRIS solution, the intern will help Métis Family Services modernize its HR infrastructure in a way that enhances data integrity, supports organizational accountability, and strengthens long-term service delivery capacity.

Évaluation des impacts de la déconnexion numérique

Le “digital free tourism” (tourisme déconnecté ou déconnexion numérique en milieu touristique) désigne une forme de tourisme où les personnes voyageuses peuvent se déconnecter des technologies numériques (téléphones intelligents, médias sociaux, etc.) pendant leur séjour. Certains travaux récents questionnent cependant les limites du tourisme déconnecté, en soulignant par exemple le stress vécu à la suite d’une déconnexion imposée ou encore les tensions/ambivalences qui naissent entre le besoin de se déconnecter et celui de rester connecté pour des raisons pratiques ou sociales. Dans ce contexte, l’Association Hôtellerie du Québec (AHQ) et le Manoir d’Youville font appel à la Chaire de recherche sur les dépendances comportementales et la réduction des méfaits du Centre de recherche médicale de l’Université de Sherbrooke pour étudier l’état de la déconnexion numérique ainsi que les impacts associés. Qu’est-ce que la littérature dit sur le sujet? Est-ce une pratique efficace? Quelles sont les stratégies mises en place, à ce jour, par les acteurs du milieu touristique au Québec, au Canada et ailleurs?

Understanding and improving compositional generalization in vision-language models

Compositionality — the ability to understand new combinations of familiar parts — is a core aspect of human cognition and reasoning, but current vision-language models such as CLIP still struggle with it. These limitations reduce the reliability of systems that must correctly interpret objects, attributes, and relations in real-world scenarios. Although many methods have been proposed to strengthen CLIP’s compositional abilities, it remains unclear which parts of the model they affect or why certain approaches lead to better results. This project will develop a standardized diagnostic framework to identify where compositional behaviour improves within the models and what factors drive those improvements. The resulting insights and tools will help guide the development of more reliable multimodal AI systems. This project will benefit both participating institutions by supporting their shared interests in advancing reliable, scalable AI methods, fostering a new research collaboration between the groups, and creating reusable resources that will support future research and student training.