Projets novateurs réalisés

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.

Psychophysiological dynamic networks for co-regulation in parent-child dyads: A novel approach toward personalized intervention

This project explores how conflict between parents impacts how children and caregivers manage their emotions in real time. In collaboration with East China Normal University, we will observe emotion regulation patterns in parent-child pairs during structured play tasks designed to simulate both everyday and high-conflict situations. Unresolved parental conflict is a known gateway to intimate partner violence, child maltreatment, and chronic mental health issues across the lifespan. By using physiological measures to track emotional responses, this study will help identify when and how children’s emotional development is most disrupted—and how parents’ reactions may either buffer or worsen these effects. The results will inform family-based interventions that prevent long-term psychological challenges and support healthy child development. In addition, the project will provide advanced statistical training that the lead researcher (KA) will bring back to Canada to enhance local research capacity and apply to ongoing child health and development studies.

High-Fidelity 3D Simulation of Soft Tissue Cutting via Adaptive Cohesive Zone Modeling: Toward Digital Surgery

This project aims to improve surgical simulations by developing advanced computer models to simulate how soft tissues behave during surgeries. It will focus on modeling tissue fracture and how surgical tools interact with tissue, considering factors such as tissue anisotropy, residual stresses, and complex tool geometries. Current finite element (FE) models developed at UBC assume material isotropy and rely on a pre-defined path for tissue cracks, limiting their ability to simulate puncture mechanics with complex tool geometries like those found in real surgical procedures. To overcome these limitations, this project will implement an adaptive cohesive zone model (CZM), which allows the crack path to be determined in real-time based on tissue behavior. In collaboration with experts from TU Graz, the project will refine and validate these models using their specialized expertise and advanced testing equipment, which are unavailable at UBC. This collaboration will benefit both UBC and TU Graz by connecting complementary expertise and fostering long-term partnerships, leading to student exchanges and future research funding opportunities. The outcomes of this project will be transformative for digital surgery, positioning Canada as a global leader in digital and medical technologies.

TRLUP – Scaling the ROAR Tool: A Data-Driven Climate Resilience Platform for Canada’s Built Environment

The project advances the commercialization and scalability of the Resiliency Opportunity Assessment and Response (ROAR) Tool—a data-driven decision-support platform for assessing and mitigating physical climate risks in the built environment. The ROAR Tool is positioned to serve building owners, property managers, and ESG-driven institutions by providing actionable insights aligned with the Canadian Sustainability Disclosure Standards (CSDS). With over 8 million vulnerable occupants in residential and commercial buildings, the ROAR Tool empowers property owners and public-sector organizations to make informed, low-cost, and low-carbon adaptation decisions.

TRLUP – Smart Integrated System for Air Disinfection

Airborne viruses spread most readily in closed rooms where people share the same air. The usual defence is to crank up the ventilation system, so more outdoor air dilutes the germs. Unfortunately, higher airflow drives up energy bills and works against carbon-reduction targets. Installing Far-UVC lamps (222 nm) is another promising option because this light can kill viruses in real time without chemicals. We propose an integrated control platform that turns Far-UVC into a smart, energy-aware clean-air layer. Ceiling-mounted krypton-chloride lamps are paired with inexpensive sensors that track UV intensity, room-temperature, and CO2 and, Ozone concentrations. A reinforcement-learning algorithm continuously reads those sensors, simulates how air and light operate the room, and adjusts lamp brightness and airflow in real time. The goal is simple: deliver the germ-killing dose only where and when it is needed, never exceed safe exposure limits, and dial back ventilation whenever the lamps can shoulder more of the disinfection load. Making this work draws on four skill sets—UV physics to model light, indoor fluid mechanics to map airflow, hands-on electronics to prototype sensor networks, and machine-learning control to teach the system how to balance health protection with energy savings automatically.

TRLUP – Rootsy Marketplace: Advancing Local E-Commerce in Canada

Rootsy Marketplace is building a scalable, tech-enabled local e-commerce platform to connect Canadian small businesses with local buyers. The project focuses on optimizing platform logistics, digital operations, and market reach using third-party delivery partners.

La fabrication de la catégorie fille-s aux Nations Unies : une autre histoire des droits de l’enfant (1989-aujourd’hui)

Le projet de recherche proposé s’inscrit dans le cadre d’une thèse doctorale intitulée « La fabrication de la catégorie fille-s aux Nations Unies : une autre histoire des droits de l’enfant (1989 – aujourd’hui) ». Il vise à analyser la construction de la catégorie « fille-s » dans le champ onusien des droits de l’enfant, en mobilisant une approche croisée en sociologie des organisations internationales, études de genre et droits humains.

Partant du constat que les filles, situées à l’intersection des catégories « femmes » et « enfants », sont souvent invisibilisées dans les cadres juridiques internationaux, ce projet cherche à comprendre les dynamiques discursives, normatives et institutionnelles qui ont conduit à leur reconnaissance en tant que sujet spécifique au sein du système onusien, et plus particulièrement dans le champ des droits de l’enfant. L’analyse repose sur un corpus qualitatif de documents produits par les Nations Unies (rapports, archives).

Le stage permettra de finaliser un chapitre central de la thèse, qui pourrait également donner lieu à une publication scientifique. Ce chapitre mobilise le concept de « champ » pour analyser les acteurs et les pratiques à l’égard de la catégorie filles dans le « champ des droits de l’enfant ».