Innovative Projects Realized

Tinder for talent: Bridging the gap between coach intuition and standardised testing batteries in talent detection

This project will investigate how coaches make selection decisions in sport, combining youth athlete testing results with the intuition and experience coaches bring to their decisions. We will use retrospective testing data from athletes whose career outcomes are already known, allowing us to evaluate how accurately coaches predict future success and which factors, e.g., speed, height, inform their decisions. By collaborating with the University of Toronto, this research will strengthen evidence-based approaches to talent identification, providing insights that can improve selection processes and support the development of athletes. Participating institutions will benefit from shared expertise, access to new data and methodologies, and the opportunity to enhance international collaboration in sport science research.

L2M – Your Academic Choice

This project focuses on strengthening the business model and growth strategy of Your Academic Choice (YAC), a mentorship platform that supports Grade 12 students (18+), gap year students, and university students making academic decisions. Over four months, I will validate target customer segments, refine the go-to-market strategy, develop a pricing framework, and improve operational processes to ensure the platform can scale efficiently. The expected benefit to the partner organization is a clearer understanding of its highest-value customer segments, a data-driven marketing and pricing strategy, and improved operational systems that support sustainable growth and long-term impact.

Use of bioinformatics tools to assess Abundance and Sequence Variation of HIV-1 LTR U3 Transcription Factor Binding Sites and their Association with HIV-1 LVR Reactivation

HIV-1 persists in people on antiretroviral therapy (ART) because the virus can hide in long-lived immune cells, forming a latent reservoir. These hidden viruses can reactivate if treatment stops, making HIV difficult to cure. Efforts to reverse latency aim to “wake up” these silent viruses so the immune system or drugs can eliminate them, but only a fraction of proviruses respond to stimulation. The reasons for this variability are not fully understood, particularly for the main HIV subtypes circulating in Uganda (A1, D, and their recombinants).

This project investigates how the abundance and sequence variation of key transcription factor binding sites in the U3 region of the HIV genome influence viral transcription and reactivation. Using advanced sequencing and bioinformatics, the research will analyze proviral sequences from the Rakai HIV Reservoir Cohort to identify patterns associated with stronger or weaker reactivation. By linking viral DNA features to measures of latent virus activity, the study aims to explain why some proviruses resist reactivation, providing insights that could guide future HIV cure strategies.

Data-efficient Robot Learning from Human Demonstrations via Interaction Graph

The proposed research project aims to solve a critical challenge in robotics, the need of large amounts of training data, which is often costly and time-consuming to collect. Interaction graphs have shown impressive generalization capability by retargeting human motions to robots from just a single demonstration. However, the behaviors exhibited from existing frameworks leveraging interaction graphs are mostly unimodal. Leveraging Diffusion Policy’s expressiveness in modelling multimodal behaviors, we propose a unified framework that combines interaction graph and diffusion policy to learn diverse manipulation strategies from just a handful of human demonstrations. This collaboration benefits both institutions by advancing the research of both labs. This project expands Prof. Allen’s prior work on interaction graphs as a robust abstraction tool to model human-object and robot-object interactions, while simultaneously supporting Prof. Coros’ focus on efficient robotic skill learning by demonstrating how structured representations such as interaction graphs can dramatically improve the sample efficiency of learning real-world tasks.

Proposition pour un jumeaux numérique

Les solutions logicielles que Famic développe (Automation Studio™ et Andon Studio™) sont à la fine pointe de la technologie. Elles s’insèrent parfaitement dans les nouveaux paradigmes de l’industrie 4.0. Et c’est, le principal défi auquel l’entreprise fait face; l’utilisation de tels outils avancés nécessite une formation spécialisée et pointue. Bien que la formation des principes physiques de bases (hydraulique, pneumatique, électrique, etc.) soit déjà une activité bien ancrée et maitrisée, le saut vers une approche de modélisation – simulation orientée objet via un jumeau numérique, semble encore loin d’être acquise et déployée. Une approche pédagogique innovante (via études de cas, application du jumeau numérique, approche de transfert hybride, modélisation de systèmes multiphysiques, etc.) est plus que jamais pertinente et nécessaire. C’est une question importante pour soutenir sa croissance, continuer aux développements du talent sur des secteurs d’activités stratégiques pour le Canada et renforcer son avantage concurrentiel en lui permettant d’appuyer sa présence sur la scène mondiale. Pour l’ÉTS, il s’agit de renforcer une collaboration, déjà existante avec un leader dans son domaine, et de bénéficier des retombées du projet pour consolider l’apprentissage.

L2M – Modular Hybrid Air Purification System

This project will help move Pure Air Nova from a validated idea into a clear, pilot-ready product plan and a practical path to market. Based on nearly 100 customer interviews, we will focus on one priority user group, distill their needs into a simple set of product requirements, and develop a prototyping strategy that outlines what to build first and how to test performance in real-world settings. We will also develop a basic cost and pricing model and a pilot plan with clear success measures. The partner organization benefits from receiving a well-structured, high-quality project outcome that demonstrates how Lab2Market Launch turns real customer insights into a focused product direction, a lower-risk development plan, and stronger readiness for early adoption and commercialization.

Echoes of the Andes: Community Health and Climate Resilience in Ecuadorian Páramo Communities.

The project ‘Echoes of the Andes: Community Health and Climate Resilience in Ecuadorian Páramo Communities’ aims to produce actionable, community level evidence to strengthen climate resilience and wellbeing in Ecuador’s páramo regions, ecosystems vital for water regulation, biodiversity, and Indigenous livelihoods but threatened by climate change and severe data scarcity. In partnership with the University of Saskatchewan and ESPOCH, the research integrates socioeconomic information with satellite derived environmental indicators to address the lack of reliable, fine scale data needed for effective local planning. The project focuses on four methodological objectives: assembling a harmonized socio environmental dataset; creating accessible maps that illustrate community conditions and climate risks; developing a context specific Healthy Communities Indicator combining social, environmental, and climate dimensions; and applying econometric modeling to identify key drivers of community wellbeing. These components together aim to inform targeted, evidence-based interventions. Expected outcomes include a documented dataset, community friendly maps, a validated indicator, and an analytical report, along with a draft academic manuscript. While this phase does not yet involve Indigenous engagement, it establishes foundational tools and methods for deeper collaboration in future stages. Ultimately, the project strengthens international research partnerships and produces scalable approaches applicable to other remote, climate vulnerable regions.

Synthesis and Characterization of Nanostructured Materials for Advanced Engineering Applications

Ce projet de recherche vise à créer des matériaux légers et flexibles capables de protéger les appareils électroniques contre les interférences électromagnétiques (EMI), en combinant des nanocouches de MoS2 (un matériau 2D conducteur) avec des cadres organiques covalents poreux (COF) inspirés de la structure de la nacre. Pendant 13 semaines au laboratoire NPNL de l’Université de la Colombie-Britannique sous la supervision du Professeur Mohammad Arjmand, je synthétiserai ces hybrides, les intégrerai dans des polymères souples, et testerai leurs performances en blindage EMI (efficacité >30 dB), conductivité électrique, et résistance à la flexion et à l’humidité. Les avantages attendus incluent des matériaux plus légers et durables pour les smartphones pliables, 5G et drones, avec une meilleure absorption des ondes (réduction des réflexions parasites), une durée de vie prolongée des appareils (moins de déchets électroniques), et des données précieuses pour guider la conception future de protections EMI au Canada.

The Socialization of First-Generation International Doctoral Students in Canada and the U.S.

International doctoral students play a significant role in host countries by supporting research, innovation, and economic growth. While the journey through doctoral education is often described as transformative, the path to completing a doctoral degree is rarely straightforward. Beyond completing coursework and writing a dissertation, it requires learning unspoken academic rules, building relationships with faculty and peers, and understanding what is valued in a given field. For students who are both international and the first in their families to pursue higher education, this process can be especially complex. They often encounter unfamiliar academic cultures, language barriers, and fewer family-based resources to help interpret expectations. Despite their importance, this student population has received limited research attention. Using a comparative approach, this study examines how first-generation international doctoral students in Canada and the U.S. experience doctoral socialization and respond to opportunities and barriers through different forms of agency. The findings will benefit participating institutions by providing evidence-based insights into how they can better support diverse doctoral student populations. Improved understanding can lead to more effective mentoring, clearer communication of expectations, stronger professional development opportunities, and more inclusive institutional cultures, ultimately enhancing doctoral program completion, research productivity, and career readiness.

Space-Based Observation and Estimation Framework for Non-Cooperative Space Objects

This project develops a framework to identify and track inactive space objects, using observations from space-based sensors. As space becomes increasingly crowded, knowing the location, orientation, and physical properties of these uncontrolled objects is essential for avoiding collisions and ensuring safe space operations. The research combines sensor data with advanced mathematical techniques to estimate key characteristics like mass, size, and reflectivity of space debris, and to detect unexpected movements that could indicate breakups or collisions. This work will strengthen collaboration between Istanbul Technical University in Turkey and the University of Calgary in Canada, bringing together expertise in estimation algorithms and space surveillance. The outcomes will contribute to international efforts in space while providing the intern with specialized training in an increasingly critical field for the future of space activities.

Swift analysis method to support the development of mines of critical minerals

This project focuses on the development of a method for the direct analysis of solid samples by laser ablation, which is greatly advantageous over methods requiring sample dissolution. It involves minimal sample preparation and eliminates acids and other reagents required for dissolution, thereby making it a greener method of analysis. However, because ablated solid materials are directly analyzed, analytes are not physically separated from the surrounding matrix and matrix-induced interferences complicate or even prevent quantitative analysis. The proposed approach involves the controlled addition of nitrogen or hydrogen to increase the robustness of the technique used to measure analytes in the dry aerosol produced by laser ablation, thereby reducing or eliminating interferences. The approach will be applied to both depth profiling and surface mapping of geological samples, to determine the in-depth composition and spatial distribution of elements in the sample, respectively. The outcome will be robust analysis methods that address real world challenges and can easily be implemented by commercial laboratories servicing the mining industry. These developments are directly relevant to mine exploration, mine development, and environmental monitoring in Canada where reliable and sensitive analytical methods are essential for direct solid analysis.

L2M Launch Atlantic Cohort / Development of an Intelligent Scribe for Medical Pre-Consultation

Family doctors in Canada are currently overwhelmed by administrative tasks, spending nearly half of their time on paperwork rather than patient care. This project focuses on the commercialization of Mavia, an AI-powered pre-consultation platform designed to reduce this burden. Mavia interacts with patients before their appointment to gather their medical history and symptoms, automatically generating a structured clinical note for the physician. By automating data entry, this technology allows doctors to focus on the patient, reduces burnout, and improves access to primary care. This internship will validate the system in real clinics while ensuring strict adherence to Quebec’s patient privacy laws.