Innovative Projects Realized

Grenadier Pond Turtle Population Survey

Grenadier Pond in High Park, Toronto, is home to several turtle species, some of which are at risk due to habitat degradation, pollution and human interference. However, there is a lack of data on the pond’s turtle population, including species diversity, population size and nesting habits. We will conduct a population survey to establish baseline data that will guide conservation efforts, improve habitat management and support the protection of these highly endangered species.

Novel Vector Potentiators for AAV-mediated Surfactant B Deficiency correction

Surfactant Protein B (SPB) deficiency is a rare genetic disease where surfactant B is not produced in the lung, proper breathing fails and lungs collapse. The disease usually presents early in life, and unless lung transplantation is performed, no other approaches have provided long-term cure. Yet, lung transplantation is not an ideal approach either, as matching donors are limited, and the procedure is extremely invasive for a baby.
Gene therapy can be an alternative as it has been very successful in animal models. The approach consists of delivering the correct SPB gene into lung cells using an adeno-associated viral vector. This virus has shown to be very efficient at infecting lung cells without causing secondary effects. However, it requires to be dosed in high quantities, which could still have risks. In this project, we are aiming to use small molecules (termed VEPOs) developed by Virano Therapeutics that help the virus infect cells more easily, hence reducing the dose and making the therapy safer.
This project will help Virano Therapeutics advance its gene therapy program, exploring how VEPOs can overcome the challenges of this gene therapy, and potentially more. This will also help establish future partnerships, and pave ways to commercialization.

Le marché de la défense dans la région de Sherbrooke

Ce projet vise à mieux comprendre comment la région de Sherbrooke peut profiter de l’augmentation substantielle des dépenses militaires prévues au Canada. Concrètement, la stagiaire analysera les entreprises et les technologies déjà présentes à Sherbrooke pour voir si et comment elles peuvent participer au marché en pleine effervescence de la défense, par exemple dans les domaines de la cybersécurité, des matériaux avancés ou des équipements spécialisés. En rencontrant des entrepreneurs, des organismes de développement économique et des experts, elle dressera un portrait clair des forces et du potentiel de la région. Ce travail permettra à la Ville de Sherbrooke d’identifier des occasions concrètes de développement économique, de favoriser la création d’emplois de qualité et d’aider les entreprises locales à accéder à de nouveaux marchés. À terme, le projet contribuera à positionner Sherbrooke comme un pôle d’innovation dans un secteur stratégique et porteur pour l’avenir.

Mapping Cumulative Effects and Landscape Change in the Crowsnest Watershed

This research project will identify and quantify the cumulative impacts of human development and land use in Alberta’s Crowsnest Watershed using satellite imagery collected over time and geospatial change detection techniques. By analyzing how the landscape has changed over time as a result of human use, and incorporating relevant local and community-sourced data, the study will help to highlight areas of concern and to inform regional land use planning. Conducted in partnership with the Canadian Parks and Wilderness Society (CPAWS) Southern Alberta Chapter, the project addresses CPAWS’ need for accessible, spatially-informed assessments of cumulative effects in the region. The project outcomes will include report(s) to enable replication of the project in other areas, as well as public-facing maps and communication tools designed to support CPAWS’s outreach, policy advocacy, and conservation work across the eastern slopes region.

Perimeter QuInterships – Symmetric Ansatz for the Kagome HAF

Haiqu Inc. focuses on building a quantum software stack enabling more efficient development and execution of quantum applications on near-term and early fault tolerant quantum computers. Simulations of quantum chemistry and condensed matter models are one of the primary early uses cases for quantum processors (QPUs), with benefits for chemistry and materials science. Important open questions in this domain concern the physics of magnetic systems on geometrically frustrated lattices. A particular example is the Heisenberg antiferromagnet (HAF) on the Kagome lattice. The primary challenge is the difficulty in classical simulations using e.g. exact diagonalization or DMRG methods, when applied to larger systems. The key objective of the project is to demonstrate the utility of quantum computers in simulating such systems, overcoming classical limitations. The intern will work with to study in detail, implement and simulate on simulated noiseless and noisy quantum devices the ground state properties of the HAF model using symmetric quantum machine learning (QML). Haiqu has been developing SU(2) symmetric QML ansaetze and studying their applications to quantum condensed matter problems. Through this project we aim to validate the use of such equivariant QML approaches and chart the path to their applications in materials science.

Building a Multimodal AI/ML Insights Engine for Data-Driven VLT Game Optimization

This project aims to help International Game Technology (IGT), a global leader in gaming, better understand what makes their Video Lottery Terminal (VLT) games successful. Currently, IGT finds it hard to link specific game features (like bonus rounds or themes) to how well a game performs or how long players stay engaged. This project will solve this by using advanced Artificial Intelligence (AI) and Machine Learning (ML) to analyze both player feedback (from focus groups) and game performance data. By combining these different types of information, IGT will get a powerful “AI/ML Insights Engine”. This new tool will allow them to make more informed decisions about designing games, allocating resources, and improving player engagement, moving beyond guesswork to a data-driven approach.

L2M Launch / Qc Fall 2025 / Advanced MicroTesting

Le projet a pour objectif de commercialiser LOTUS-X1, un banc de test universel pour puces électroniques alliant haute performance et coût réduit. Actuellement, les chercheurs en microélectronique doivent concevoir et programmer un banc de test spécifique pour chaque puce, ce qui mobilise un temps considérable et complique la reproductibilité. LOTUS-X1 centralise tous les outils, génération et mesure de signaux analogiques, numériques et de puissance, dans une plateforme modulable, offrant ainsi aux laboratoires un dispositif réutilisable et facilement adaptable aux différents protocoles expérimentaux.

Pour réussir la transition du prototype vers le marché, deux phases clés sont prévues. La première vise à consolider un modèle d’affaires robuste : recueillir des retours clients pour affiner la proposition de valeur, élaborer des gabarits d’emails pour optimiser la relation client, définir une stratégie d’acquisition marketing et établir une structure de coûts et de revenus pertinente. La seconde phase porte sur le déploiement opérationnel : rédiger un plan produit détaillé, lancer un portail client pour recueillir suggestions et signaler les anomalies, implémenter un CRM (ex. : HubSpot) pour automatiser le suivi et élaborer une grille tarifaire cohérente.

Le succès du projet sera évalué à travers la livraison d’un Business Model Canvas complet, d’un plan produit, d’un portail fonctionnel, d’un CRM configuré et d’une tarification documentée. Le programme L2M fournira un accompagnement d’experts pour garantir la pérennité et l’efficacité de la commercialisation.

Integration of multi-omics data for predictive modelling of drug efficacy in cerebral organoids

To date, using only electrophysiological data, Epiloid has achieved a classification accuracy in the low-90% in classifying drugs on their predicted ability to modulate hyperexcitability (as seen in epilepsy). This project seeks to enhance this accuracy by incorporating multi-omic datasets into Epiloid’s machine learning pipeline, which stands to dramatically assist in collecting a holistic picture of how new therapeutics affect neural circuitry of brain organoids. This provides a useful translational tool towards personalized medicine.
Epiloid Biotechnology is pioneering the integration of human-derived 3D cerebral organoids with machine learning (ML) to enhance preclinical drug discovery for neurological diseases. This project aims to bridge the gap between complex transcriptomic readouts and ML-driven drug efficacy predictions, leveraging human-relevant in vitro models. In collaboration with the Stem Cell Network, this project will support the ongoing R&D efforts funded through Epiloid’s Ontario Genomics BioCreate grant, which focuses on
integrating multi-omics data into predictive models for neurological drug development. The project includes the development of human iPSC cultures, cerebral organoid generation, and optimization of of SOPs for transcriptomic data preprocessing for ML model integration, and validation of these models using publicly available datasets.
The project will deliver several critical outcomes, including optimized SOPs for transcriptomic data generation, high-quality organoid datasets, and enhanced ML models that integrate electrophysiological and transcriptomic data. These advancements will position Epiloid as a leader in human-relevant preclinical testing, directly supporting its long-term goal of becoming a key partner in precision drug discovery.Furthermore, this partnership aligns closely with SCN’s national mandate to accelerate the development of
regenerative medicine and cellular therapies through collaborative research.
Anticipated benefits include the improved prediction of drug efficacy and safety, reducing costly late-stage failures; accelerated drug discovery timelines through better preclinical models; and enhancing Epiloid’s competitive advantage through proprietary organoid and machine learning data pipelines.

Optimisation des processus de l’entreprise par la mise en place d’un ERP

Dans le cadre de ce stage, le stagiaire participera activement à un projet stratégique visant à implanter un système ERP (Enterprise Resource Planning). Ce logiciel est essentiel à la transformation numérique de l’entreprise, car il centralise la gestion des processus opérationnels au sein d’un système intégré unique. Le stagiaire jouera un rôle clé en contribuant à l’analyse des besoins, en développant des solutions d’intégration, et en optimisant les processus ainsi que les outils de suivi de la performance. La mise en place de l’ERP permettra à l’entreprise de centraliser et d’harmoniser ses processus opérationnels, d’améliorer l’efficacité et la coordination entre les services, et d’optimiser le suivi de la performance. Ce projet stratégique favorisera la transformation numérique et apportera une meilleure réactivité et prise de décision grâce à des données fiables et partagées en temps réel.

Performance de l’ADN environnemental pour l’identification des sites de fraie de l’éperlan arc-en-ciel et du gaspareau sur la côte du Nouveau Brunswick

Ce projet vise à évaluer la performance de l’ADN environnemental comme technique de détection des sites de fraie de l’éperlan arc-en-ciel et de gaspareau dans les rivières côtières du Nouveau-Brunswick à partir d’un large échantillonnage réalisé par notre partenaire (Vision H2O) dans les dernières années. Ces informations représentant une information critique dans la gestion de ces espèces de poissons exploitées par la pêche commerciale et récréative. Les données de présence des espèces seront utilisées afin de paramétrer un modèle de niche numérique prédisant l’utilisation potentielle des rivières non échantillonnées. Ces modèles permettront aussi d’établir les facteurs les plus importants dans la détermination de la présence des espèces dans les rivières côtières de la province.

Transforming Vacant and Derelict Infill Properties into Affordable Housing Opportunities

This project addresses the growing challenge of vacant and derelict properties in Winnipeg’s Spence Neighbourhood by exploring practical strategies to convert them into affordable and sustainable housing. The research will examine the main barriers to housing redevelopment, including high construction costs, complex zoning regulations, limited financing, and low incentives for property owners to invest in improvements. By analyzing demographic and housing data, the study will identify the needs of vulnerable groups, particularly youth and newcomers at risk of homelessness. Additionally, a housing stock assessment will evaluate the quantity and condition of vacant properties and explore how crime rates, declining property values, and socioeconomic factors contribute to property abandonment. Furthermore, the project will investigate the failure of market solutions to drive property redevelopment, despite the potential financial returns. The findings will equip SNA with practical insights to strengthen the community reduce homelessness, improve housing conditions, and make the neighbourhood safer and more welcoming for current and future residents.

TRLUP – Magnetic Pickering Nanoemulsions as a Diagnostic Tool for Fracture Characterization in Unconventional Reservoirs

This project focuses on exploring how a new diagnostic technology—magnetic Pickering nanoemulsions—can help improve the way we understand fluid flow in underground rock formations, such as those found in oil and gas reservoirs. These nanoemulsions are tiny droplets that are stable under harsh conditions and can be tracked using magnetic tools, making them useful for mapping fractures in rocks. During this four-month project, we will study how ready this technology is for the market by researching potential customers, competitors, and industry needs. The expected benefit to the partner organization is a clear roadmap that shows how this lab-developed innovation can be developed into a commercial product, helping them stay competitive with advanced, field-ready tools.