Projets novateurs réalisés

Impact assessment for Women’s Centres Connect

Women Centre’s Connect (WCC) is launching a province-wide Impact Assessment Initiative that will rigorously measure—and transparently communicate—the economic and social returns generated by its programs, with the explicit goal of unlocking sustained government funding. This project will build a robust evidence framework that traces how WCC’s services move women from economic inactivity or precarious circumstances into stable employment, quantifying outcomes such as incremental tax revenues, public-service cost savings (e.g., reduced shelter use and crisis interventions), and downstream community benefits. Drawing on best-practice methodologies used in labour-market and social-finance evaluations, the assessment will consolidate fragmented data sources, introduce new outcome metrics, and apply a defensible return-on-investment (ROI) model that aligns with the province’s economic-development agenda. By producing an independently validated report and an easy-to-update dashboard, the initiative will equip policy makers with hard numbers—rather than moral appeals—demonstrating that every dollar invested in WCC yields multiple dollars in fiscal and productivity gains. Securing funding for this assessment is therefore pivotal: without empirical proof of impact, WCC risks losing the resources and legitimacy required to expand its work, whereas a credible ROI case will position the organization to secure a permanent, government-funded role in driving Nova Scotia’s economic growth.

A Multi-Agent System (MAS) platform for AI-Assisted Patient Assessment and Prognosis in Obesity

This project will develop a multi agent-based personalized healthcare platform that helps healthcare providers better understand and support people living with obesity. The tool will use artificial intelligence, large-language models to ask questions about a patient’s mental health, lifestyle, and quality of life, then use that information to suggest more tailored treatment options, such as drug responsiveness. By working on this project, the partner organization will gain a new, innovative way to support doctors and patients—going beyond basic tools to deliver smarter, more compassionate care.

Development of a software platform to connect brands with vetted vendors

The proposed project involves the intern supporting the development of NOUN, a software platform that connects beauty brands with trusted manufacturers. The intern will help improve how data is organized and shared between brands and vendors, making it faster and easier to manage product development. This work will help the partner organization, EC Studios, launch the NOUN platform more efficiently, saving time and reducing errors for both internal teams and external clients.

Optimized DAP Placement and WiMAX Planning for Smart Grid

Smart grid aims at improving the power grid performance, security and reliability through monitoring, controlling and protecting the grid dynamically. As communication infrastructure and technologies provide two-way data communication between grid endpoints, they are the key enablers for smart grid realization. WiMAX and 802.15.4g is among the dominant considered communication technologies for smart grid implementation. During this PhD internship, we intend to enhance and optimize these communication technologies and also provide a cost-efficient architecture towards the requirements of smart grid applications. New methods and algorithms are devised in order to adapt the communication technology with the smart grid system profile specifications. Powertech Labs Inc. is a BC Hydro subsidiary which provides clean energy and engineering consultation towards optimizing power systems and providing smart grid solutions. This project provides the partner with guidelines on optimized network planning based on the above-mentioned communication technologies. Our analysis and simulations help Powertech Labs Inc. to have a better understanding of the network before the actual implementation. It also enables Powertech Labs Inc. to introduce new services to customers and to facilitate new demand-side management and energy efficiency programs involving a higher degree of customer participation.

TRLUP – Triboelectric Measurement Devices

This project focuses on developing a novel triboelectric sensor to improve the efficiency and reliability of industrial processes specifically in gas-phase polyethylene production. In these reactors, plastic particles often accumulate electrostatic charge during operation, leading to dangerous buildups that can cause the formation of solid “sheets,” resulting in costly unplanned shutdowns.

The goal of this project is to design and prototype a next-generation electrostatic sensing system capable of monitoring the overall charge of particles in real-time instead of relying on very local measurements. By combining this new hardware with advanced signal analysis, we aim to give operators early warnings when static levels rise, allowing timely interventions to prevent problems in advance. Ultimately, the project brings together science, engineering, and innovation to solve a long-standing industrial challenge and support cleaner, smarter, and more efficient industrial operation.

Modélisation technico-économique multi-énergie pancanadienne

Le stage s’inscrit dans un projet R&D qui s’étend sur trois ans, porté par le consortium international “Hydrogen and Climate Partnership – A new hydrogen network between Canada and Germany as a key component of a climate-neutral energy system”. Ce projet a pour objectif d’analyser les relations et les effets de la restructuration des chaînes de valeur industrielle afin d’explorer la coopération entre le Canada et l’Allemagne basée sur l’hydrogène au regard des critères d’économie, d’écologie et de sécurité d’approvisionnement.
Les stratégies nationales de décarbonisation dans le monde entier intègrent l’hydrogène comme la meilleure solution pour atteindre les objectifs communs de réduction des gaz à effet de serre. Il est nécessaire pour les décideurs de mieux comprendre ses avantages et ses limites dans les futurs systèmes énergétiques. À ce titre, l’objectif du projet consiste à fournir une suite d’outils de modélisation pour évaluer l’impact de l’hydrogène et des stratégies de décarbonation au Canada. Le but est de s’adresser à la fois aux décideurs publics pour les aider dans le déploiement de leur stratégie hydrogène, et aux industries privées qui ont besoin de visibilité pour investir efficacement dans toute la chaîne de valeur en maîtrisant leurs risques.
Notre plateforme de modélisation Artelys Crystal intègre des modèles fins pour tous les actifs composant les systèmes et réseaux électriques et de gaz naturel. Un modèle de la région du Nord-Est de l’Amérique du Nord est déjà développé dans Artelys Crystal. Avec ce projet, nous visons à intégrer au modèle électrique tous les modèles liés à la chaîne de valeur H2, à savoir une représentation fine et des paramètres technico-économiques des différents types d’électrolyseurs, des réseaux H2 pour la transmission et la distribution incluant le stockage et la consommation. Il sera ainsi possible d’effectuer des analyses prospectives sur les comportements possibles des systèmes électrique dans une économie où l’hydrogène a une place prépondérante.

L2M – BioThera Solutions

We are developing a promising new technology based on extracellular vesicles (EVs, often referred to as exosomes), which are natural delivery vehicles produced by cells. These tiny particles have the potential to transform how we treat diseases by delivering therapeutic ingredients directly to where they’re needed in the body. To bring this technology to market efficiently, we’re starting with a skincare product that uses EVs to deliver anti-aging ingredients deep into the skin, offering real, science-backed results. This approach enables us to demonstrate the effectiveness of our platform, generate early revenue, create trust in this technology, and establish a solid foundation for future medical applications (i.e., infrastructure, team, etc.). The partner organization will benefit by supporting a project with immediate commercial potential and long-term impact in advanced therapeutics.

comparison of heart rate variability and brain activation during emotional regulation in athletic groups

Stress has been implicated as a significant contributor to both mental and physical illness, and has been shown to compromise psychological well-being. Emotional regulation is the process of monitoring and adjusting emotional responses to environmental stress. Heart rate variability (HRV) and functional magnetic resonance imaging (fMRI) have been used as biomarkers for emotional regulation. Currently, there is a knowledge gap on the long-term effects of athletic training on changes in these biomarkers of emotional regulation. The UBC Brain Behavior Lab (BBL) and Lululemon Athletica’s Whitespace™ Innovation Team, aimed to determine if persons who practice yoga differ in HRV and brain activation (measured using fMRI), in response to emotion-evoking environmental stimuli compared to recreational athletes and varsity hockey players with no yoga background. The practice of yoga may help reduce levels of stress as individuals learn to mindfully experience emotions as they acquire the ability to separate ones’ emotions from the emotions of others and the situation at hand.

Modélisation de la recharge et de la vulnérabilité des eaux souterraines sous changement climatique à l’aide de l’intelligence artificielle

Ce projet répond à l’enjeu mondial urgent de la durabilité des eaux souterraines face aux changements climatiques, en développant un cadre de modélisation robuste, alimenté par l’intelligence artificielle, pour évaluer et comparer la recharge et la vulnérabilité des nappes phréatiques dans deux régions aux climats contrastés : la plaine semi-aride de Berrechid au Maroc et le sud du Québec au Canada, caractérisé par un climat humide. En intégrant des variables environnementales issues de données satellitaires (par exemple la végétation, la température et les précipitations), des scénarios climatiques (RCP 4.5 et 8.5), ainsi que des algorithmes avancés d’apprentissage automatique à des modèles hydrologiques conventionnels comme DRASTIC, AHP et SWAT, le projet produira des outils d’aide à la décision à haute résolution et transférables — tels que des cartes de vulnérabilité, des simulations de recharge et des tableaux de bord interactifs. Ces outils soutiendront une gestion de l’eau fondée sur la science et résiliente face au climat.

Understanding how Dolutegravir-based antiretroviral therapy modifies the HIV-1 latent reservoir and implications for an HIV cure

Global funding for life-sustaining therapy to treat HIV-1 has become unstable in recent years, particularly in sub-Saharan Africa, where 70% of the 37.9 million people with HIV (PWH) reside. Lifelong adherence to therapy is required as HIV integrates into the DNA of long-lived host immune cells, persisting quietly for decades with the potential to reactivate and produce HIV at any time. Prior cure strategies aimed at eliminating this reservoir have failed due to a gap in our understanding of the molecular mechanisms behind HIV persistence and decay. Previously, our group examined reservoir changes over time in Ugandan PWH and found that their reservoir significantly increased shortly after participants initiated a new therapy drug, dolutegravir (DTG). However, the assay used to measure these changes relies on cellular reactivation, unable to distinguish whether DTG increases the number of HIV-containing cells or enhances their reactivation. This project will utilize our adaptation of a molecular-based assay for the HIV subtypes in Uganda to distinguish between these possibilities. Understanding how DTG modulates reactivation potential and reservoir stability will help define molecular targets for HIV eradication strategies. This project will improve our fundamental understanding of the HIV reservoir and enhance representation of African and female PWH.

Recurrence analysis of neuronal behaviors and networks

The goal of this project is to bridge the fields of neuroscience and nonlinear dynamics by leveraging advanced machine learning algorithms to analyze recurrence patterns in neural wave data. Specifically, the project focuses on studying traveling cortical waves – a fundamental phenomenon in brain activity – using recurrence quantification analysis enhanced by machine learning techniques. By combining these approaches, we aim to uncover novel physical relationships and dynamical properties underlying neural processes, providing deeper insights into how the brain organizes and propagates information.

TRLUP – Building an AI-Driven Compliance Intelligence Prototype: Clause Classification, Regulation Mapping, and Policy Impact Detection

This project will develop a working prototype of an intelligent compliance assistant that leverages machine learning to detect regulatory risks in business contracts, map clauses to frameworks such as GDPR and PIPEDA, and generate plain-language summaries. The system will also track evolving regulations and intelligently suggest policy updates. By simplifying legal review, it enables Canadian SMEs in highly regulated industries to avoid fines, reduce operational delays, and stay confidently aligned with changing laws. Ultimately, the solution empowers small businesses to treat compliance as a strategic growth enabler rather than a legal burden.