Innovative Projects Realized

Environmental Impact Assessment in Edmonton’s North Saskatchewan River Valley

Edmonton’s North Saskatchewan River Valley and Ravine System (“the River Valley”) is a core component of the city’s open space network. In accordance with the City of Edmonton’s North Saskatchewan River Valley Area Redevelopment Plan, an environmental impact assessment is required for proposed development, such as utility infrastructure or parks amenities, in the River Valley. An update to the detailed technical guidelines for completing these assessments is required to better reflect current best practices in municipal environmental impact assessment, with a focus on addressing system-wide, cumulative impacts of multiple stressors on ecosystem functions in the River Valley. Through this project, the Sustainability Scholar will contribute towards environmental protection of the River Valley, a key biodiversity core area and regional biodiversity corridor, by helping to ensure that the potential environmental impacts of proposed development are assessed appropriately and communicated effectively to decision makers.

Emotion Vocabularies Used in Therapy: Investigating How Emotion Language Supports Adolescents’ Emotion Regulation and Mental Health

The proposed project examines how the words adolescents use to describe their emotions change over the course of psychotherapy and whether having a broader vocabulary for both positive and negative emotions is linked to better mental health outcomes. To address these questions, the study will analyze text- and video-based conversations from approximately 1,500 adolescent–therapist pairs delivered through the Talkspace online psychotherapy platform. This research project will benefit both participating institutions by strengthening collaboration between research teams at Princeton University and the University of Guelph, advancing shared expertise in emotion-language and adolescent mental health research, and generating high-quality research outputs including a peer-reviewed academic manuscript, a conference presentation and doctoral student’s dissertation.

Multi-Sensor Validation and Scaling of Machine Learning Models for Contrail Detection and Flight Attribution using Integrated Ground-Based and Satellite Observations

This proposed research project aims to tackle the significant climate impact of aviation contrails by creating a high-quality “ground truth” dataset to improve how we detect and predict them. By extending Western University’s extensive Global Meteor Network of ground cameras to European ground-based camera systems and improving current machine learning models, the project will help solve the “flight matching” problem – accurately identifying which specific flights create warming contrails. This collaboration offers a powerful synergy: Western University benefits by transforming its astronomical camera network into a world-leading tool for climate monitoring, while TU Delft gains the essential ground-based machine learning algorithms to extend the use of their current cameras. Ultimately, this partnership equips researchers with the specialized skills and validated models necessary to lead global initiatives in reducing aviation’s contribution to climate change.

Investigation of Commotio Cordis using patient specific Finite Element Models

The proposed project would like to investigate Commotio cordis, which is a rare event that can cause cardiac arrest due to sudden impacts to the chest. Specifically, this project aims to research strain patterns on patient specific finite element models. The expected benefit to the participating institutions will be developing of a new approach to research Commotio cordis, development of new FEA techniques, and new skills to share with home institutions. By working together, the institutions will develop new approaches to understand Commotio cordis and improve safety for athletes.

Dynamics of Live Streaming Commerce in Supply Chain Management

This project studies how live streaming commerce, a fast-growing way of selling products through real-time online video is changing supply chain management. Unlike traditional e-commerce, live streaming creates sudden spikes in customer demand that existing supply chains often struggle to handle efficiently. The research aims to understand how these new sales models affect inventory management, logistics, product quality, and revenue sharing, particularly in the Canadian context where distances are large and logistics costs are high. By comparing live streaming–based supply chains with traditional e-commerce systems, the project will identify practical hybrid strategies that combine the speed of live streaming with the reliability of existing infrastructure. The expected benefit for participating institutions includes actionable insights to improve supply chain responsiveness, reduce operational risks, and support data-driven decision-making for digital commerce strategies, helping organizations remain competitive in rapidly evolving global markets.

Validation clinique d’un système de rétroaction musicale et visuelle pour la correction de la marche chez les enfants atteints de paralysie cérébrale

Le projet de recherche proposé vise à participer à la validation clinique de MusiGAIT, un système de biofeedback musical et visuel conçu pour aider des enfants vivant avec une paralysie cérébrale à améliorer leur marche. Ce système transforme certains mouvements, notamment la flexion excessive du genou lors de la phase d’appui, en signaux sonores et visuels afin de rendre la rééducation plus compréhensible, motivante et engageante. Dans le cadre de ce stage, la stagiaire participera à l’organisation et au déroulement de séances expérimentales en milieu clinique et contribuera à la collecte de données de marche, incluant la cinématique, l’activité musculaire, la perception de l’effort et la douleur. Elle prendra également part à l’évaluation de l’efficacité des différentes modalités de biofeedback proposées ainsi qu’à l’analyse de l’utilisabilité du système et de la satisfaction des enfants et des cliniciens à l’aide de questionnaires et d’entrevues. Les avantages attendus de ce projet sont une meilleure compréhension de l’effet du biofeedback sur la correction de la marche, la validation scientifique du système MusiGAIT et une contribution directe à l’amélioration des outils de réadaptation pédiatrique, tout en permettant à la stagiaire de développer des compétences en recherche clinique et en analyse du mouvement.

Joint Communication and Sensing Using Intelligent Retro-reflective Surfaces

This project explores a new approach to indoor localization using retroreflective Reconfigurable Intelligent Surfaces (RIS). Unlike conventional RIS that actively steer signals, retroreflective RIS naturally send radio waves back toward their source while still allowing programmable control. This creates stable and energy-efficient signal paths that can significantly improve positioning accuracy in cluttered or dynamic environments.
The project develops models and algorithms to understand how these surfaces can be used for remote localization and angle of incidence estimation. The goal is to enable low-cost, scalable, and reliable localization solutions for future wireless networks.

Strategic Development and Commercialization Pathway for UV-Light Poultry Barn Air-Disinfection Technology under the CNI–UQMS–Pillars Framework

This project will develop and implement a comprehensive business and governance plan to commercialize a new UV-Lite air-disinfection system for poultry barns, incorporating public health, animal welfare, and agrifood sustainability outcomes. The intern will work under the joint supervision of Dr. Ruben Burga (University of Guelph – Lang School of Business) and Novometrix Research Inc., a social enterprise research firm pioneering the Community Network Integration (CNI) and Universal Quality Management System (UQMS) frameworks for cross-sector governance. The intern’s main deliverable will be a comprehensive commercialization and business plan,

including operational workflows, stakeholder integration models, funding strategies, and data- governance templates aligned with the Four Pillars of Outbreak Response (Leadership, Data & Analysis, Interventions, Communications).

Chemiluminescence-Resonance Energy Transfer Strategies for Next Generation Photodynamic Therapy

This research project aims to develop new molecular systems that can produce light directly inside biological tissues, allowing diseases such as cancer to be detected and treated without the need for an external light source. Conventional light-based therapies are limited because light does not penetrate deeply into the body, reducing their effectiveness for internal or hard-to-reach tumors. To overcome this limitation, the project focuses on chemiluminescent reactions, which are chemical processes that generate light through reactions triggered by biological conditions found in cancer cells.

The goal is to design integrated systems capable of chemiluminescence resonance energy transfer (CRET) by chemically engineering chemiluminescent reagents and BTI photosensitizers so that they are fully compatible. Rather than simply mixing components, the project aims to ensure efficient energy transfer between them, allowing the internally generated light to activate BTI photosensitizers. Once activated, these molecules can produce reactive species that destroy diseased cells through photodynamic therapy while minimizing damage to healthy tissues.

By combining chemistry, light-based science, and biomedical applications, this work seeks to overcome key limitations of current light-based treatments and could contribute to safer and more effective therapeutic strategies in cancer medicine.

Implementation of Multi-view learning to a Dynamic Convolutional Neural Network for Object Detection

In the context of developing an academic activity as part of the intern’s postgraduate studies and building a new international research collaboration, the University of Alberta and the Tecnológico de Monterrey propose this research stay project, promoting a strategic initiative of artificial intelligence (AI) and the establishment of Industry 5.0 in fields such as agriculture and biomedicine. The project involves implementing and validating Multi-view learning in a Dynamic Convolutional Neural Network (MVDCNN) for object detection, utilizing different feature fusion strategies to enhance the performance of single-view detector models in terms of mean average precision (mAP). This collaboration aims to generate open-access knowledge that might encourage the development of technological solutions to face current national challenges, such as food security and health care access, addressed by government programs such as Food Sovereignty, Health and Data Science (México), Science and innovation in agriculture, and Health Science and Research (Canada). The awaited outcome of the research resides in the design, implementation, and validation of a multi-view detection model that improves detection rates by applying feature fusion techniques, contributing to further projects, including the intern’s thesis project, and delivering a manuscript for submission to a prestigious conference or journal.

Developing Thermally Stable Lipid Nanoparticles (LNPs) with Long-Term Stability for mRNA Therapeutics

The success of the COVID-19 vaccines demonstrated how powerful new technologies based on lipid nanoparticles (LNPs) and messenger ribonucleic acid (mRNA) can be for protecting public health. As more RNA-based medicines are being developed, it is increasingly important that these LNPs are stable and easy to distribute, especially to support global accessibility and improve preparedness for future health crises. Currently, most LNP formulations must be stored at –20 °C or even –80 °C to remain effective, which makes manufacturing and distribution costly and limits access in regions without reliable cold-chain infrastructure. This project will explore novel synthetic lipids and stabilizing materials (e.g. polymers) to develop LNP formulations that stay functional for longer and under less demanding storage conditions. The research will be carried out through a collaboration between two leading centers of LNP innovation: the University of British Columbia and the Eindhoven University of Technology. Together, these institutions aim to advance next-generation LNP technologies and strengthen international scientific cooperation.

Environmental correlates influencing roost selection of the King Vulture (Sarcoramphus papa) in the Calakmul region, Mexico

The project consists of an internship at the Centro de Investigación Científica de Yucatán (CICY) in Mexico under the supervision of Dr. José Luis Hernández-Stefanoni. The goal of this project is to acquire the necessary skills, resources and data that will contribute to a master thesis in biology, at Sherbrooke University, Canada. The subject of the thesis is the selection of communal roosts by king vulture (Sarcoramphus papa) in the region of Calakmul, Mexico. This species uses specific habitats in the neotropical forests as their roosts, where they rest, clean, drink, and socialize. These sites are therefore likely key to the conservation of the species in the region. To study roost selection, data on landscape characteristics will be acquired by remote sensing, particularly LiDAR. This radar technology will be useful to acquire variables that are not available using multispectral imagery to characterize roosts in an integrated manner, accounting for vertical and horizontal vegetation heterogeneity. This project will lead to a new collaboration between the home and host supervisors which will allow them to benefit from new expertise and recognition in their field of research. The student will also acquire new skills on a novel tool in wildlife ecology.