Projets novateurs réalisés

Modeling cardiac fibrosis in a dish with human iPSC-derived fibroblasts

Cardiovascular disease remains a leading cause of death in Canada and is a progressive disease characterized by impaired heart function that can ultimately lead to heart failure, with a rising incidence and a 5-year survival rate of only 50%. Advanced cases of heart failure caused by dilated cardiomyopathy (DCM) are referred for mechanical circulatory support and/or heart transplantation. We are trying to generate a “Heart-in-a-Dish”, allowing us to model disease and test treatments in patients with diagnosed cardiovascular disease. This will provide an opportunity to develop new treatments for a range of clinically important cardiovascular diseases. Our primary aims are to develop a “bedside to bench to bedside” path for cardiovascular disease modelling and to generate tools to evaluate pharmacologic and functional profiles in physiologically relevant systems in the context of heart disease. From blood samples, we can 1) generate and validate induced pluripotent stem cells (iPSCs) generate relevant cell types in the heart and 2) characterize functional properties of cardiac fibroblasts which become activated in the disease and drive disease progression. We want to develop new medications to impact this disease progression.

L2M-Oculum-Ontario

Oculum is developing a new imaging system to improve how eye surgeons see delicate, transparent tissues during surgery—without the need for chemical dyes, which are often risky and not approved for many procedures. This project will help Oculum move from early research to real-world use by building the business and operational tools needed to bring the technology to market. Over four months, the intern will help create a solid business model, prepare materials to attract early investors, and design a roadmap for developing and selling the product. This will strengthen Oculum’s ability to raise funding, grow the team, and bring safer, faster, and more reliable tools to eye surgeons and their patients.

L2M – AIDA: Avatar-Integrated Dating App

Online dating platforms struggle to balance emotional intimacy with user privacy. Most rely on static profiles and text-based chats, which lack the non-verbal cues—like gaze, facial expressions, and body language—that are essential for building trust. While video calls attempt to fill this gap, they introduce two critical issues: First, fixed camera angles in conventional video platforms disrupt natural eye contact behavior, weakening interpersonal connection. Second, video reveals users’ real identities prematurely, often before trust has been established.

At York University’s BioMotion Lab, we have been investigating how subtle social signals—especially gaze direction—shape virtual communication. Our research led to the development of AIDA (Avatar-Integrated Dating App), a new platform that uses real-time 3D avatars, computer vision, and MPDepth, a patented rendering technique, to simulate face-to-face conversations with true dynamic eye contact—while preserving user anonymity.

The current MVP supports facial expression mirroring and gaze tracking through floating-head avatars. The next step is to transition this research prototype into a scalable, commercial-ready product. To do so, this project will focus on (1) replacing face-only avatars with full-body avatars, (2) building a platform-independent architecture, (3) ensuring secure, privacy-compliant backend systems, and (4) packaging the technology into an API that can be easily licensed and integrated by dating companies.

This initiative represents a crucial step in moving academic innovation into the marketplace. It will refine the technical infrastructure, validate usability and trust-building benefits, and prepare the technology for commercialization—advancing Canada’s leadership in privacy-respecting, human-centered virtual communication.

Stratonovich solution for hyperbolic Anderson model with space-time homogeneous Gaussian noise

Stochastic partial differential equations (SPDEs) are mathematical models that describe random phenomena evolving over space and time. SPDEs underpin modern approaches to modeling phenomena in fields such as climate science, neuroscience, financial mathematics, engineering and quantum physics. The aim of the project is to construct a new solution to a particular SPDE and investigate the properties and representations of the solution. These developments, which would be new to the scientific community, are relevant to both the physical applications when modeling such equations and the theoretical applications when investigating other SPDEs. Hence, a successful project would form a basis for publication between the intern and supervisors, thereby bolstering the portfolios of both research teams and fostering future collaboration between the institutions.

L2M Validation / QC Automne 2025 / Next-Generation Paper Diagnostics: Point-of-Care Smart Detection of Infection

This project focuses on creating a low-cost, paper-based sensor that can quickly detect and archive Pseudomonas aeruginosa, a harmful bacterium found in both medical and environmental settings. This includes infections in hospitals and contamination in water systems—two areas where fast, accurate detection is essential for protecting public health. The sensor leverages smart electrochemical technology to specifically detect a signature molecule produced by the target bacteria, enabling rapid and accessible testing without the need for complex laboratory equipment or specialized training. In addition to real-time detection, the paper-based format allows the device to physically retain the sample, providing an integrated means of archiving for potential confirmatory testing or future analysis.

Beyond medical and water testing, the sensor also shows promise for use in biosecurity. With minimal adjustments, it could be adapted to detect other hazardous biological agents, making it valuable for emergency response, border screening, and public safety applications. Made of paper, the device is lightweight, inexpensive, and easy to dispose of safely through simple incineration, an important feature when handling biohazardous waste in remote or resource-limited settings. This makes it especially suitable for deployment in northern Quebec and Indigenous communities, where laboratory access and waste management options are often limited.

During this project, feedback from potential users and stakeholders (healthcare professionals, NGOs, and public health officials) will be gathered through structured interviews and fieldwork. This input will be used to validate the sensor’s design, usability, and relevance in real-world scenarios such as infection control, water quality monitoring, and crisis response. Insights will inform key aspects of commercialization, including pricing strategy, distribution models, and potential partnerships. These efforts will help the start-up refine its product and accelerate the development of a user-informed, field-ready diagnostic tool.

L2M – Additive Manufacturing of Advanced Ceramics for Patient-Specific Components in Dentistry

This project aims to develop next-generation dental implants using Yttria (Y2O3)–Zirconia (ZrO2) composites through advanced ceramic additive manufacturing. The work will begin with a pre-prototyping validation survey to assess market needs, clinical requirements, and user preferences. Based on the survey findings, material and process optimization will be carried out to produce clinically viable prototypes. The project will benefit the partner organization by providing validated product concepts, early market insights, and a foundation for future commercialization in the dental implant sector.

L2M Validation / Qc Fall 2025 / DeepScript

This project will support the development of DeepScript, a software platform that helps researchers find promising small molecules for drug discovery without needing to run large and expensive screening campaigns. Instead of testing hundreds of thousands of compounds, DeepScript uses biological data and artificial intelligence to predict which existing compounds are most likely to work in a given experiment. This will make drug discovery faster, cheaper, and more accessible, especially for smaller biotech companies and academic labs. The work will help DeepScript refine its value proposition, explore product–market fit, and validate the platform’s potential with real users.

L2M Next-Gen Pellet Extrusion 3D printer: Eliminating Barriers to Performance and Precision

This project focuses on solving key problems in large-scale pellet-fed 3D printing, a technology that holds great promise for cost-effective, sustainable manufacturing. Unlike traditional 3D printers that use expensive filaments, pellet-fed printers use raw plastic pellets directly, making them more affordable and flexible for industries like construction, automotive, and tooling. However, the current systems have three big issues which are weak bonding between printed layers, material stringing or oozing during pauses, and poor blending of recycled or composite materials. These problems lead to print defects, extra waste, and unreliable performance, making it harder for companies to adopt this technology for real-world use.
To address these issues, the intern will help refine and validate a new hardware system that includes a square-profile nozzle (for stronger bonding), a mechanical anti-oozing valve (for cleaner prints), and a built-in polymer mixer (for blending different materials in real time). The intern will also study the Canadian market, assess the system’s performance under local manufacturing conditions, and build a commercialization strategy based on stakeholder interviews, standards research, and business modeling.
As a partner organization, will benefit by being closely involved in the early-stage development of a scalable, Canadian-made 3D printing innovation. This aligns with the mission of supporting high-growth startups and manufacturing solutions. The project will generate a validated prototype and commercial insights, making it easier for partner organization and its network to evaluate and support the launch of the technology. Additionally, this collaboration will help position it as a key enabler in bringing advanced, sustainable manufacturing technologies to market, expanding opportunities for job creation, clean tech leadership, and business growth in Canada.

L2M – Scalable Additive Manufacturing of Compact Lattice Heat Exchangers for High-Performance Thermal Management in Space-Constrained Applications

This project focuses on the commercialization of a compact, high-efficiency heat exchanger developed using advanced lattice geometries and additive manufacturing technologies. Designed to meet the thermal management needs of space-constrained systems, the innovation offers significant advantages in size, weight, and performance over traditional heat exchangers. The intern, Sanjoy Dam, will conduct market research, customer discovery, and business model development to validate the commercial potential of this Canadian-made solution. Applications include electric vehicles, aerospace, HVAC, and satellite systems—industries where efficient thermal control is essential. The outcome will be a go-to-market strategy supporting the launch of a scalable and locally manufactured thermal product.

L2M – WearNovAiN: A Wearable Biomedical Platform for Self-Screening of Breast Cancer via Sweat Biomarkers

This project develops WearNovAIN, a wearable sweat-based diagnostic patch for early-stage breast cancer detection. Combining colorimetric sensing and AI analysis, it aims to provide a low-cost, non-invasive solution for underserved communities.

L2M – Health Validate – A Rapid and Portable DNAzyme-Based Biosensor for Early Colorectal Cancer Detection

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in Canada, with over 24,000 new cases and 9,300 deaths reported in 2023. Early detection significantly improves survival rates, yet current screening methods, such as stool-based tests and colonoscopies, have major limitations. Fecal tests often produce false positives, leading to unnecessary and invasive colonoscopies, while some cases of early-stage CRC go undetected. There is a clear need for a simple, accurate, and affordable screening tool that can help identify CRC at an early stage when treatment is most effective. This project aims to conduct a customer discovery to gather customer pain points of colorectal cancer screening and will highlight opportunities for a suitable alternative test for early detetection of CRC.

L2M-FiberTrap

FiberTrap is a new filter designed to stop microplastics from washing machines before they reach our water systems. Every time we do laundry, tiny plastic fibers come off synthetic clothes and go down the drain. These fibers are too small for regular water treatment plants to catch, and they often end up in rivers, lakes, and oceans. FiberTrap is a reusable device that connects to washing machines and captures these fibers using smart design and safe materials. This project will help improve the filter’s design, test how well it works, and prepare it for use in homes and businesses.