Innovative Projects Realized

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.

TRLUP – Advanced Self-Driven Microfluidic Platform for Concentrating Therapeutic Vesicles

We are developing a novel microfluidic platform designed to enable efficient concentration of extracellular vesicles (EVs) from biological fluids such as plasma, serum, etc. This system reduces sample volumes from 1–10?ml down to less than 100?µl without the need for bulky instrumentation or centrifugation, offering a scalable and user-friendly alternative to conventional methods. By leveraging precisely engineered channel geometries and self-driven flow, the platform enhances both yield and purity of EV recovery. This concentrated output is ideal for downstream applications in biomarker discovery, liquid biopsy diagnostics, regenerative medicine, and EV-based therapeutics. The technology builds on our previously validated EV isolation device and incorporates improvements in throughput and handling capacity for integration into clinical and lab workflows. Ultimately, this advancement aims to streamline sample preparation, minimize EV loss, and accelerate translation of EV-based tools into practical healthcare and research settings.

BioSport

This project aims to help BioAro Inc., a Calgary-based biotech startup, promote its two new health products—PanOmiQ and BioSport—by improving how they reach and connect with customers. The project will help BioAro to research the market, identify who the ideal customers are, and create engaging content and strategies to raise awareness. The project will aim to make sure the company’s website and digital platforms offer a smooth and consistent experience for users. This support will help BioAro grow its customer base and successfully bring its new products to market.

Validation of a novel markerless motion tracking system for telerehabilitation

Physical therapy is a major modality in the treatment of patients with chronic musculoskeletal and neurological pain; however, current virtual reality (VR)-based solutions are unable to precisely capture full body motion leading to motion sickness and VR game design challenges. In this proposal, we aim to validate the accuracy of the AReve Health motion capture software, powered by the LightBuzz SDK, during (1) upper-body (shoulder abduction) and (2) lower-body (squat) exercises using the cameras of an iPad Pro against a gold-standard optical motion capture system. We hypothesize that the range of motion and joint angle values between the two systems will be similar. The project is expected to contribute to earlier detection of health and injury risks, promote preventive care strategies, and support individualized rehabilitation, thereby improving overall quality of life and reducing long-term healthcare costs. Also, the project will strengthen the partner organization’s competitive position within the expanding wearable health technology market. Collectively, the outcomes of this project will drive technological innovation, foster public health advancements, and support sustainable economic development for the partner organizations.

Optimizing modeling processes though building a AI Digital Twins

Toronto Pearson Airport (operated under the Greater Toronto Airport Authority – GTAA) is Canada’s largest airport in terms of total passenger traffic and North America’s second largest in terms of international traffic. With daily non-stop flights to many of the world’s economies, we move people and goods across the country, the continent and around the globe. Our goal is to create the airport of the future, and we are well positioned to make this a reality (Our Story, n.d.).
The research objectives within this project aims to optimize the modeling process for furniture and interior elements, and establish a standardized catalog of dimensions. Such a catalog would allow GTAA to implement a coding system similar to that used in EdgeWise (an as-built modeling platform that uses advanced algorithms to automate tedious scan-to-BIM workflows), where predefined element dimensions facilitate the automated detection of components within point-cloud data. This automation significantly reduces manual input and errors ultimately streamlining the modeling process and improving overall efficiency.
Beyond modeling, a standardized catalog can also enhance the organization and management of digital twin data. For instance, GTAA already plans to embed parameters into family models for elements like signage, improving both the accuracy and usability of the digital twin. However, the effectiveness of this approach relies on the standardization of geometry and the predictability and repeatability of these elements.
This project will provide research opportunities for the interns to model Architectural BIM elements. The research will involve 3D modeling of the Terminal 1 and Terminal 3 of Toronto Pearson Airport Modelling will include tenant kiosks, canopies, restaurants, sitting areas, and serving equipment, as well as signage, wayfinding and advertisements.

An Intelligent Digital Twin for an Automated Warehouse

A manufacturing company that produces Aluminum profiles uses extrusion, cutting, straightening, heat treatment, and coatings processes. The warehouse of the company uses an automated warehouse with a loading/ unloading stacker (crane) and an AGV fleet.
The goals of this project which are summarized below are to develop an intelligent digital twin for the warehouse, which the company will then use to test and simulate various scenarios in the production and market demand and its effect on warehouse operation.
Designing, implementing, and evaluating an I-IoT system for the shelves of the warehouse to measure the accurate content of inventory at each cell of the warehouse
Designing, implementing, and evaluating the digital twin of the automated warehouse and its AGV fleet
Designing, implementing, and evaluating optimization algorithms to enhance the path planning operation of the loader/unloader stackers and AGVs
The proposed project will be carried out by a team of researchers led by Dr. Farshid Najafi at Simon Fraser University with unique laboratories in Digital Twin, Industrial Internet of Things, and Smart Manufacturing which will support the research project. The supporting organization, Longboard Architectural Products, manufactures aluminum products that are used for architectural cladding, siding, soffits, and ceilings.