Projets novateurs réalisés

Organic gunshot residue as forensic evidence

Organic gunshot residue (OGSR) is a trace residue released during firearm discharge. It includes unburned, partially burned, and pyrolyzed components of the propellant (smokeless powder) and other organic substances (stabilizers, plasticizers, flame suppressants). Recently, the forensic community has shown interest in complementing standard SEM-EDS methods for the detection of inorganic gunshot residue (IGSR), with analytical methods that can detect the organic constituents. Unlike IGSR, which consists mainly of microscopic particles released from the primer (i.e., Pb, Ba, Sb), OGSR offers direct evidence related to the propellant formulation. The main components yielding OGSR are the stabilizers, like diphenylamine (DPA), ethyl centralite (EC), and akardite (AKII)), and the energetic explosives, like nitroglycerin (NG)) and nitrocellulose (NC) used in the smokeless powder (SP). In this study, we hypothesize that partially burnt and neat smokeless powders will exhibit different stability and degradation products. Monitoring these products using mass spectrometry methods can expand the scope of current analytical OGSR detection and provide insights into the stability of these residues recovered from forensic substrates (skin, clothing, etc.).

Mining and Modeling Review-Priority Labels in Gerrit for Predictive Review Analytics

Code review is a critical step in modern software development, ensuring quality, preventing defects, and coordinating collaborative work. Large ecosystems such as OpenStack, which is hosted on Gerrit, receive a high volume of code changes every day, making it challenging for reviewers to decide which contributions should be handled first.

In response to this, OpenStack developers use a special review-priority label to indicate which changes are urgent or should be reviewed ahead of others. However, little is known about how consistently this label is applied, how it influences reviewer behavior, or whether it actually helps reduce review delays.

This project aims to study how developers use the review-priority label, understand the patterns behind its application, and explore how AI techniques can support and improve its effectiveness. We will mine OpenStack’s Gerrit data, extract features related to priority signals and review outcomes, and build predictive models that help teams identify when a change should be prioritized. The goal is to provide insights and AI-assisted recommendations that make priority-driven code review more consistent, reliable, and useful in large software ecosystems.

Smart Dream Home – Enhancing Housing Accessibility Through User-Centered App Innovation

Smart Dream Home is a forward-thinking startup developing an innovative mobile application designed to guide newcomers and homebuyers in Canada through every stage of the housing journey—from research and budgeting to purchase and settlement. The organization’s main activities center around designing an intuitive, data-driven digital platform that simplifies the often-overwhelming process of finding, financing, and settling into a new home. However, as a new product targeting a highly diverse and complex user base, Smart Dream Home faces a key innovation challenge: transforming raw ideas about user needs into a validated, user-friendly, and emotionally engaging experience. Traditional market research and product testing are not sufficient to capture the real challenges faced by newcomers and first-time buyers, who vary widely in digital literacy, cultural expectations, and housing priorities. This project aims to address that gap by introducing a structured user testing and customer experience research framework that integrates qualitative and quantitative insights directly into the product development cycle. The innovation lies in developing a continuous feedback and co-creation model where real users are not just test subjects but active collaborators in shaping product usability and emotional resonance. This approach goes beyond typical app development cycles, embedding empathy-driven design and behavioral insights into Smart Dream Home’s technology roadmap. To achieve this, expertise is required in marketing research, UX/UI testing methodologies, data analysis, and human-centered design, alongside strong communication skills to interpret complex feedback and translate it into actionable improvements. By developing this research-driven innovation process, Smart Dream Home will be able to refine its product with precision, increase user adoption, and position itself as a trusted digital companion for homebuyers across Canada.

Westland Insurance – Innovating from Within: A Multi-Disciplinary Approach to Change & Learning

Westland Insurance is a rapidly growing insurance organization committed to modernizing how learning is delivered, supported, and scaled across a national workforce. As the company expands, maintaining consistent, engaging, and accessible learning experiences has become an innovation priority. Existing learning plans, tools, and LMS workflows were originally designed for smaller teams and now struggle to keep pace with new products, roles, and regulatory requirements. The challenge is not simply updating content; Westland needs a more intelligent, efficient, and future-ready learning ecosystem that reduces administrative burden, improves learner engagement, and supports real-time capability development across the organization. This project goes far beyond routine L&D tasks by focusing on designing new learning automation methods, data-informed content mapping models, and next-generation microlearning assets that increase accessibility and scalability. Solving this challenge requires expertise in instructional design, learning analytics, digital content development, workflow optimization, and creative media tools. Through this internship, the intern will support the development of innovative learning assets, redesigned LMS structures, and modernized support tools that will strengthen Westland’s ability to efficiently train and upskill teams as the organization continues to grow.

OHME! Foods Inc. – Retail Operations Innovation and Process Optimization Project

OHME! Foods is a rapidly expanding Vancouver-based snack company specializing in freeze-dried fruits and yogurt crunches produced locally in British Columbia. As the company continues to scale its retail presence across Canada, it faces the challenge of managing and optimizing the complex process of retail onboarding, launch execution, and post-launch support across multiple grocery partners. Currently, retail activities are handled reactively, relying on manual coordination and ad-hoc processes that create inefficiencies, communication gaps, and inconsistencies between store launches. To sustain growth and ensure operational excellence, OHME! requires an innovative, data-driven approach to systematize and streamline its retail launch process. This project aims to design and implement a structured framework complete with standardized templates, workflows, and tracking tools that will enable OHME! to replicate successful retail launches efficiently and at scale. The initiative goes beyond day-to-day sales coordination by introducing process mapping, performance analytics, and technology-supported retail support models to drive continuous improvement. Solving this challenge requires expertise in business process design, sales operations, and retail analytics, combined with creative marketing and communication skills to bridge sales performance insights with consumer engagement strategies.

Big Sisters of BC Lower Mainland – Designing and Implementing Data-Driven Process Improvements to Strengthen Fundraising and Operations

Big Sisters of BC Lower Mainland is a non-profit organization dedicated to enabling life-changing mentoring relationships that ignite the power and potential of young people. Through its inclusive programs, the organization empowers female, female-identifying, non-binary, gender fluid, transgender, and Two Spirit youth to build confidence, resilience, and leadership skills. To sustain and expand these vital community programs, Big Sisters relies on dynamic fundraising strategies, donor engagement, and operational excellence that allow the organization to maximize resources and impact.
As the non-profit sector continues to evolve, Big Sisters has recognized the need to modernize and innovate its internal systems to keep pace with increasing data demands, donor expectations, and digital fundraising trends. Current administrative and fundraising workflows rely on traditional, manual processes that limit efficiency and scalability. The organization faces the challenge of transforming these processes into a more data-driven, technology-enabled, and strategically integrated model that strengthens operational performance and enhances community reach.
This project introduces an innovation-driven opportunity to research, design, and pilot new methods of operational improvement and donor management that extend beyond daily administrative tasks. The intern will analyze the existing workflows across fundraising and operations to identify inefficiencies, explore digital solutions such as automated tracking systems, and design frameworks that support data accuracy, faster reporting, and improved decision-making. By developing new processes and tools for cross-departmental collaboration and donor engagement, the project will help Big Sisters build an adaptable and sustainable infrastructure that supports long-term organizational innovation.

Understanding Green Bilayer Dielectrics through Advanced Characterization: A Canada–Finland Collaboration

This project focuses on developing environmentally friendly electronic materials by combining biodegradable polymers with semiconducting materials to develop degradable, flexible, and high-performance organic electronic devices. The work aims to improve device stability and sustainability, contributing to the advancement of green electronics. Through collaboration between participating institutions, the project will promote knowledge exchange in materials design, processing, and device fabrication, while providing students and researchers hands-on experience in sustainable technology development.

Finning – Digital Transformation of Onboarding and Sales Training Systems

Finning Canada is the world’s largest Caterpillar dealer, serving mission-critical industries such as mining, construction, energy, and forestry. As the company continues to modernize and scale its operations, Finning is undergoing two major transformation initiatives: the Finning Foundations Project, which is redesigning the employee onboarding experience, and the Sales Training Transformation Project, which is re-engineering how sales enablement programs are delivered across a distributed and hybrid workforce. The challenge Finning faces is that its legacy onboarding and sales training processes rely heavily on manual coordination, siloed tools, and inconsistent learning pathways, which creates delays, duplicated efforts, and variable employee experiences. With the company supporting thousands of employees across multiple provinces and business units, there is an urgent need for an integrated, digitally enabled onboarding and sales training ecosystem that improves internal efficiency, accelerates time-to-competency, and supports the consistency required for a large, geographically dispersed organization.

Double diplôme de doctorat : Comportement alimentaire et besoins énergétiques lors d’épisodes d’inactivité physique prolongés

L’activité physique joue un rôle essentiel dans l’équilibre entre l’énergie que nous mangeons et celle que nous dépensons. Pourtant, lorsqu’on devient inactif (blessure, hospitalisation ou simplement un mode de vie sédentaire), cet équilibre se dérègle. Nos besoins énergétiques diminuent, mais notre appétit ne s’ajuste pas toujours : nous continuons souvent à manger comme si nous étions encore actifs. Ce désalignement favorise alors une accumulation de masse grasse et augmente le risque d’obésité et de troubles métaboliques.

Pour comprendre ce phénomène, Philippe St-Martin participe à l’étude BRACE (Bed Rest with Artificial gravity and Cycling Exercise), soutenue par l’agence spatiale européenne. Ce modèle unique d’inactivité physique extrême, reposant sur l’alitement prolongé de volontaires actifs et en bonne santé, simule la microgravité observée chez les astronautes. Pour la première fois, ce protocole combine alitement et alimentation ad libitum mais contrôlée, permettant d’étudier comment l’appétit et la prise alimentaire réagissent à une chute d’activité physique.

Ces travaux visent à mieux comprendre pourquoi l’inactivité dérègle la régulation de l’appétit et de la balance énergétique, et à identifier le rôle protecteur de l’exercice. Les résultats aideront à concevoir des stratégies de prévention contre la prise de poids liée à l’inactivité, sur Terre comme dans l’espace.

Développement d’outils numériques pour la modélisation et la simulation du procédé de précipitation

La précipitation est une opération unitaire clé du Génie des Procédés, utilisée pour séparer, purifier, synthétiser et mettre en forme des produits organiques ou minéraux, notamment en industrie pharmaceutique. Elle consiste à faire apparaître une phase solide à partir d’une solution liquide via une réaction chimique produisant un composé moins soluble. Pour garantir la pureté et les propriétés du produit (granulométrie, morphologie…), le procédé doit être rigoureusement contrôlé. Les conditions opératoires (débit, concentration, température…) et l’hydrodynamique influencent directement la qualité du précipité.
Pour optimiser ou contrôler le procédé, des modèles prédictifs sont développés. L’approche par bilan de population est particulièrement intéressante, car elle permet de prévoir l’évolution de la distribution en taille des particules au cours du temps.
L’objectif de la recherche est de développer des outils numériques génériques et robustes pour résoudre l’équation de bilan de population en tenant compte de la nucléation, de la croissance et de l’agglomération des particules, dans un procédé fermé ou continu. Une méthode de volumes finis sera utilisée et validée par des solutions analytiques simples. Un couplage avec l’hydrodynamique puis une validation expérimentale sur un produit modèle compléteront l’étude.

Smash and Tess Dreamwear Inc. – Advancing Sustainable Fashion Through Data-Driven Digital Marketing

Smash + Tess Dreamwear Inc. is a fast-growing Vancouver-based fashion company known for redefining comfort and style through its signature Romper designs and commitment to ethical, sustainable production. As a leader in the “slow fashion” movement, Smash + Tess has built a powerful community around inclusivity, sustainability, and confidence but like many digitally native brands, it faces the challenge of evolving its digital marketing strategies to stay competitive in an increasingly crowded e-commerce landscape. The innovation challenge lies in developing data-driven, omnichannel digital marketing campaigns that not only drive sales but also deepen emotional engagement with consumers through authentic storytelling, emerging digital platforms, and next-generation tools. This project will focus on enhancing the company’s digital marketing ecosystem through experimentation with innovative tactics such as predictive analytics for consumer targeting, creative A/B testing for content optimization, and integrated campaign tracking across Shopify, Meta, TikTok, and Google Ads. Going beyond daily marketing operations, the internship will support the exploration and implementation of new approaches to digital engagement and community growth helping Smash + Tess remain a trailblazer in ethical, locally made fashion. Solving this challenge requires expertise in digital strategy, data analytics, creative content production, and an understanding of evolving consumer behaviour in the fashion and lifestyle space.

Investigating Cfp1 PHD Domain Iron–Sulfur binding activity in anaerobic conditions through Structural and Biochemical Studies

This project aims to uncover how Cfp1 PHD domain, a chromatin reader domain traditionally known for coordinating zinc might use a special iron–sulfur (Fe–S) cluster to sense and respond to changes in the cell’s environment. By studying this protein under oxygen-free conditions and determining its 3D structure, we hope to reveal how redox chemistry influences gene regulation, a question with broad implications for understanding cell function and disease. The project brings together the University of Ottawa’s expertise in chromatin biology and the Institute of Structural Biology in Grenoble’s world-leading specialization in metalloproteins. This collaboration will advance understanding of redox-linked chromatin regulation while strengthening the partnership between the University of Ottawa and the Institute of Structural Biology through shared infrastructure, training, and joint publications.