Projets novateurs réalisés

Development of multimodality imaging and advanced AI/ML algorithms for point-of-care and drug discovery applications

The proposed international research collaboration project aims to develop accurate and efficient image processing algorithms for advanced imaging instrumentation technologies. The overarching goal of the project is towards fully automated microscopy technologies with many strategically important applications for both DGIST (Korea) and McMaster (Canada) such as point-of-care diagnosis in remote communities and drug discovery. The internship will allow two Canadian graduate students to develop core skills in image processing algorithms development as well as establishing their own professional networks.

An economic evaluation of sulfonylurea medication, hypoglycemic episodes and falls in older adults with type 2 diabetes

Drug use in older persons is a major public health concern. Even though therapeutic drugs are beneficial for patients’ health in terms of survival or quality of life, patients aged >65 years have a greater risk of developing drug-related complications. Such complications may be fatal because of the high frequency of both multiple pathologies and polypharmacy in these patients, who consume a major proportion of healthcare resources. The present work aims to evaluate the impact of treatment with a widely used antidiabetic drug (sulfonylureas) in older diabetic patients on avoidable hospitalizations for hypoglycemia, falls, and fractures. This economic study will be
conducted using data from the diabetes-specific Quebec Integrated Chronic Disease Surveillance System database. For Merck Canada Inc, the present work will play a key role in helping evolve research in the area of pharmacogeriatrics related to diabetes in Canada.

Renfrew Paramedics Minimum Data Set

In collaboration with the Provincial Community Paramedicine Program at Ontario Health, Renfrew County Paramedics is leading the development of a Minimum Data Set (MDS) in an effort to improve CP integration with Ontario Health Teams. This project will focus on the development of a robust data governance framework that includes the development of core data domains, data definitions, and integrated care classification schemes informed by benchmarking against CP reporting standards and assessments. The outcome of this project will be the development of a draft data dictionary (definition, coding standard, data type, essential/optional, meta-data) that will be communicated to CP programs across the programs through dedicated MDS workshops.

PatchUp Summer Education Student BSI

PatchUp is a web-based resource that offers a smarter, more scalable way to support classrooms by addressing behavioural needs through technology and innovation. Designed to assist students during moments of dysregulation, PatchUp provides interactive emotion regulation activities that can be used independently or alongside support staff, making it a flexible solution across a variety of contexts. In addition to directly supporting students, each interaction with PatchUp provides schools with insights into behavioural patterns and classroom disruptions that often go undocumented. These insights enable more strategic decision-making, enhanced student support, and help guide incoming class complexity teachers, ensuring this new resource is used where it’s needed most.
Our current priority is to deepen our understanding of the complex challenges students and classrooms face, along with the diverse strategies educators use to manage them. This knowledge directly informs both the overall product strategy and the finer details of design and implementation. Gathering meaningful insights requires collaboration with an experienced educator—particularly someone who has managed real classroom disruptions, ensuring the product remains grounded in real-world needs and is truly effective in practice. Therefore, addressing this problem requires someone with direct classroom experience and who understands the realities of teaching.

Light collection optimization with semiconductor photodetectors – Year two

Better light collection by photodetectors would automatically improve signal to noise ratio and photodetector performance. For example, for the positron emission tomography application, it would result in a better image quality for a lower dose. The main cause of the light loss is too much reflection of light that is trying to travel from the light source into the semiconductor light sensor. Several options are possible to overcome this difficulty and will be investigated, such as anti-reflective coatings, the use of an optical coupling compound with a higher refractive index to
bound the medium and the photodetector, or micro and nano structures on both the medium and the photodetector. The research will be aimed at finding the best compromise between light collection optimization and feasibility, to improve performance of photodetectors designed and manufactured by Excelitas Canada.

Light collection optimization with semiconductor photodetectors

Better light collection by photodetectors would automatically improve signal to noise ratio and photodetector performance. For example, for the positron emission tomography application, it would result in a better image quality for a lower dose. The main cause of the light loss is too much reflection of light that is trying to travel from the light source into the semiconductor light sensor. Several options are possible to overcome this difficulty and will be investigated, such as anti-reflective coatings, the use of an optical coupling compound with a higher refractive index to
bound the medium and the photodetector, or micro and nano structures on both the medium and the photodetector. The research will be aimed at finding the best compromise between light collection optimization and feasibility, to improve performance of photodetectors designed and manufactured by Excelitas Canada.

Optimization of Super Heavy Lift Drone Design utilizing Computational Fluid Dynamics and a Design of Experiments approach

Heavy-lift drones offer promising solutions for challenges in wildfire response, construction, and logistics, thanks to their rapid deployment and lower environmental impact. As Pulshn focuses on developing drones capable of transporting heavy payloads, this research aims to support the optimization of drone design for enhanced performance and reliability. Specifically, the study will explore the aerodynamic behavior of ducted fan configurations to improve mass flow rate and thrust efficiency. Computational Fluid Dynamics (CFD) will be used to evaluate aerodynamic performance, while a Design of Experiments (DOE) approach will assess how key design parameters influence outcomes. The findings will guide the development of a next-generation heavy-lift drone capable of carrying up to 1,000 kilograms. This advancement aligns with Pulshn’s goals and could significantly expand commercial applications in emergency response, infrastructure development, and cargo transport.

Policy Analysis for Inclusive Cooperative Growth: Strengthening Expertise Hub Cooperative’s Capacity to Support Immigrant Communities

Expertise Hub Cooperative (EHC) seeks to engage a policy analyst to strengthen its ability to navigate evolving policies and support its immigrant-focused mission. This initiative will provide actionable insights, policy recommendations, and strategies to address systemic barriers, advocate for change, and enhance EHC’s capacity to foster inclusivity and community impact. By aligning with EHC’s cooperative values, this work will empower the organization to adapt to policy changes and better support its members and programs. This will support Expertise Hub Cooperative (EHC) in navigating the evolving policy landscape that impacts the cooperative and its immigrant-focused members. By delivering comprehensive policy analysis, stakeholder insights, and actionable recommendations, this project will empower EHC to address systemic barriers, foster inclusivity, and advance its mission of building a connected and empowered immigrant community.

EHC’s work goes beyond workforce development, fostering connections through workshops, job fairs, and events that empower immigrants to thrive socially, culturally, and economically. This initiative will provide EHC with the tools and insights needed to adapt to current policies and trends while strengthening its impact.

Electrifying Bike Sharing Systems: Structural Demand Estimation and Large-scale Optimization

Bikeshare systems around the world are increasingly incorporating electric bikes to expand their coverage and increase ridership. This project aims to apply descriptive and prescriptive analytics to support key operational and strategic decisions in bikeshare electrification. First, we will perform empirical analysis to quantify the spatially heterogeneous impact of electric bike availability on bikeshare ridership. Then, we will develop an optimization model that jointly determines charging infrastructure locations and battery swapping policies—two of the most common charging strategies in e-bike sharing systems—to maximize overall ridership. Together, these efforts will offer a comprehensive, data-driven approach to electrifying bikeshare systems and promote the broader adoption of this sustainable mode of transportation.

Le Music Legacy Project – Bibliothèque des performances musicales du monde en Réalité Virtuelle

Conscient des difficultés auxquelles font face de nombreux musiciens, ingénieurs du son et réalisateurs dans différents pays (et convaincu de l’importance de l’engagement du chercheur auprès des populations étudiées), je souhaite développer à travers mes recherches postdoctorales une structure qui fasse le pont entre recherche ethnomusicologique, création musicale et engagement social. Pour ce faire, il s’agit de réaliser une série d’enregistrements musicaux à travers le monde, à l’aide d’un studio nomade, avant de les travailler en laboratoire (au LARC, à l’Université Laval), pour ensuite les diffuser via des réseaux commerciaux établis par l’entreprise La Hacienda Creative, spécialisée dans la post-production audionumérique. Dans cette perspective, l’objectif principal de ce projet postdoctoral est de créer une plateforme de recherchecréation
visant à décloisonner l’expérience de recherche ethnomusicologique. Cette structure servira de cadre expérimental utile au renforcement des relations de réciprocité entre chercheurs, musiciens et réalisateurs provenant des différents pays visités.

The Biomechanical Differences between the SideStix? Crutch and a Traditional Forearm Crutch

Many people with physical disabilities depend on forearm crutches to help them walk. Although forearm crutches are helpful, many people experience overuse injuries as a result of using the forearm crutch. Injuries to the wrists, elbows and shoulders are commonly experienced with long-term use of the forearm crutch. The research project will examine differences between the traditional forearm crutch and a newly developed SideStix? crutch. The SideStix?crutch has been developed with a spring-like device and rotating footpads. It is hypothesized that the new crutch will effectively change body movement while crutch walking while reducing the impact on the body. SideStix? Ventures Inc. will greatly benefit from this project by understanding how their crutch influences walking and it may reduce overuse injuries.

Improving the Detection of Performance Regressions with Change Point Detection Methods

As software systems evolve, the software performance has to be constantly monitored to ensure that systems are responsive and economically sustainable. Companies like Mozilla have dedicated teams and an automated workflow to detect performance regression. However, due to the nature of performance measurements, the automatic detection of regressions is bound to flag issues falsely, which makes the performance team waste investigation time, and miss actual regressions, which could impact end users.

This research project aims to explore the state-of-the-art methods in change point detection (CPD) to improve the accuracy of Mozilla’s performance detection system. We plan to create a real-world dataset of validated performance alerts, explore the efficacy of multiple CPD methods on Mozilla’s data, and integrate the best techniques in Mozilla’s detection system. A more effective performance regression detection system would improve team productivity, enabling them to focus their efforts on fixing real performance anomalies, ultimately making the company’s products better and more responsive.