Projets novateurs réalisés

Development of a modular aircraft propulsion simulation model

In this project a modular propulsion simulation tool will be developed, which is able to be integrated in an already existing framework for preliminary aircraft design. The developed tool shall then be used for analyzing different propulsion system configurations of conceptual aircraft, to compare these against each other regarding different metrics, such as efficiency and system weight.

Advancing Diamond-Based Quantum Magnetometers through Innovative Bonding Techniques

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Doctoral research collaboration: Professor Hannah Heilmann, Royal Danish Academy of Fine Arts

Research Internship with interdisciplinary artist and Associate Professor Hannah Heilmann at the Royal Danish Academy of Fine Arts, Copenhagen. The work will seek to build the intern’s capacity to create public-facing artistic research with Heilmann, an established expert, on concepts related to feminist embodiment, ecology, affect, and performance.

Apprentissage automatique quantique (QML) en oncologie : application au cancer du sein et au cancer du poumon

Le cancer représente un défi majeur pour la santé mondiale avec des millions de nouveaux cas chaque année. L’intelligence artificielle (IA), notamment l’apprentissage profond, a amélioré la détection des tumeurs, mais transformer les grandes quantités de données médicales en informations cliniquement exploitables reste difficile. L’informatique quantique émerge comme une technologie prometteuse, notamment via l’apprentissage automatique quantique (QML), qui propose des algorithmes avancés pour améliorer l’apprentissage automatique. Ces algorithmes sont explorés dans des domaines biomédicaux pour des tâches comme la réduction de la dimensionnalité et la classification. Les modèles hybrides quantiques-classiques montrent un potentiel pour la découverte de biomarqueurs et la prédiction de la survie des patients, notamment en pathologie numérique. Malgré des avancées, des recherches supplémentaires sont nécessaires pour valider ces techniques en oncologie. L’apprentissage automatique et profond reste crucial pour la détection précoce du cancer, particulièrement efficace pour analyser les images médicales complexes et faciliter des diagnostics rapides. Ce projet vise à évaluer le potentiel du QML dans la prédiction du cancer du sein et du poumon, en utilisant les bases de données CBIS-DDSM et LUNA16.

New quantum materials and new quantum sensors using ultra-cold atoms

The aim of this research internship is to contribute to our group’s research program using laser­ cooled gases to
explore fundamental phenomena of quantum materials and to use them to realize new quantum sensors. This research program has two main objectives – the use of ultra-cold atomic and molecular gases to (1) realize new quantum sensors with scientific, industrial and/or commercial applications and to (2) investigate fundamental questions concerning few and many-body quantum phenomena relevant for quantum materials development and research. Both objectives have both short and long term goals (that extend beyond this grant). The short term goal for the quantum sensor research theme is to establish cold atoms as the international, primary pressure standard for UHV. The long term goal is to investigate the applications of this new sensor to flux measurements relevant for semi- conductor fabrication processes. The short term goal for the quantum materials research theme is to observe many- body fermi-fermi and bose-fermi pairing phenomenon in ultra-cold atomic gases relevant to quantum materials and related to electron-electron pairing in superconductors. The plan is to study the modification of pairing due to impurities, mass imbalances, and the effects of quantum statistics.

Analyse structurale de la mine du mont Wright, Fermont, Québec

La mine du mont Wright, située à Fermont au Québec, est le plus important producteur de minerai de fer du Canada. Le gisement se trouve dans des roches ayant été plissée plusieurs fois et possiblement disséquées par des failles tardives. Le projet de maîtrise-recherche proposé, en partenariat entre la compagnie ArcelorMittal et Polytechnique Montréal, vise à réaliser la première analyse structurale du site. Les retombées les plus importantes pour la compagnie seront l’amélioration du pouvoir de prédiction de la présence de plis secondaires qui causent parfois de couteux dynamitage de roches stériles, et une amélioration des calculs de stabilité de pente par une meilleures compréhension de la géométrie des failles. Outre les retombées économiques, ce projet permettra de mieux comprendre l’évolution tectonique de la Province de Grenville : une ancienne chaine de montagne qui avait l’envergure de l’Himalaya il y a un milliard d’années.

Cryptographic Verifiable Computing in Networked Control Systems

In Networked Control Systems (NCS), computation is outsourced to an external party, which we call a controller. This type of service has been gaining popularity in recent years. However, there is the threat of the controller wanting to read the commands passed onto it, thus violating confidentiality. To avoid this, we seek to incorporate cryptographic verifiable computing into NCS, for example by employing Paillier encryption or cryptographic primitives such as the AES in an efficient and feasible manner. Doing so will allow for more secure yet fast communication between the parties. As a result, this internship will bridge the gap between currently available technology and the security concerns raised by both public and private actors of Industry 4.0. Because of this, Concordia University’s standing as a vigilant cybersecurity institution will strengthen. By extension, Canada’s reputation on the international cybersecurity stage will grow too.

An Analytical Model of Thickness and Flatness Estimation for Tailor Rolled Blanks

Rolling is an important process in metal forming. Through the rolling process, metal billets are turned into sheets or strips for use or further processing. Due to worsening global environmental conditions and higher demands for industrial products, lightweight design has become a trend in fields like automotive and aerospace. Traditional rolled metal sheets and strips with uniform thickness are unsuitable for the high demand for complex structural designs. As a result, a new type of sheet with variable thickness has been developed and applied. It’s called Tailor Rolled Blanks (TRB). Research on this new technology is just beginning. This project aims to fill the gap in predicting and analyzing key parameters in the rolling process of TRB. The key parameters will include the thickness and flatness of TRB. The research will advance high-grade sheet manufacturing technology and enhance the levels of industries such as automotive and aerospace in Canada.

Towards a Model-Based Federated Learning Architecture for Intrusion Detection and Mitigation in Small Office and Home Office Networks

This project aims to strengthen RabbitRun Technologies’ (RRT) cybersecurity capabilities in software-defined wide area network (SD-WAN) solutions for small office/home office (SOHO) environments. It addresses the critical need for secure and reliable connectivity in remote and small business settings by integrating federated learning into RRT’s systems. This approach enables RRT routers to collaboratively improve intrusion detection and mitigation while maintaining data privacy and minimizing communication demands.

The key goals of the project are: (1) developing a domain-specific language (DSL) to simplify the mining and specification of security-related network behaviours; (2) advancing state-machine learning techniques to better detect evolving cybersecurity threats; and (3) implementing a federated learning infrastructure for collaborative model refinement across distributed routers.

This initiative bridges academic research and industry innovation, providing the intern with hands-on experience in applied AI, cybersecurity, and model-based software engineering. It also lays the foundation for secure, dynamic networking solutions, benefiting both RRT and the broader Canadian digital economy.

Revolutionizing Asset Management: RFID-Powered Solutions for Asset-Heavy Industries

Scatterlink is a nuanced technology company that delivers advanced inventory and asset management solutions design specifically for asset- heavy industries. Through the use of Radio- Frequency Identification technology (RFID), Scatterlink bridges the gap between physical assets and digital management, providing real-time visibility, tracking, and actionable insights. The asset-heavy industry faces substantial challenges with manual, labor-intensive inventory tracking methods, which result in increased operational costs and productivity setbacks due to asset misplacement and human error. Scatterlink has identified an innovative solution by developing an automated, end-to-end RFID-based inventory and asset management product. The mission of this product is to replace outdated outdated inventory methods with a streamlined digital system that enhances accuracy, reduces operational costs, and optimizes resource allocation. This collaboration with Lambton College seeks to accelerate the development of a minimum viable product (MVP). Lambton College and Scatterlink will develop an integrated mobile and web application using open-source frameworks such as React JavaScript (JS) and Node JS and Express for backend processes tailored to the operational requirements of asset-heavy industries. The successful completion of this project will see the development of a comprehensive digital solution for asset management that will in turn transform the industry. This transformation is essential in mitigating the inefficiencies currently plaguing the industry and fosters a more resilient and competitive economic environment in Canada. This partnership with Lambton College will create approximately 50-75 new high skilled jobs over the next fiver years contributing to workforce development in the technology sector. The anticipated efficiency gains will result in significant cost savings for client companies, positioning Scatterlink to remain competitive in a rapidly evolving global market. Moreover, as this technology offers a proven effectiveness in mining, its applications will extend to various industries, facilitating new market entries and diversifying economic opportunities for Scatterlink.

Innovations in Talent Strategy and Work Culture in Human Resources

The challenge CrucialLogics is currently facing is how to innovate our current processes, workflows, and work culture to support our organization and its clients as we enter the new era of growth and technology. New Innovation in operations (specifically HR) is required as we scale the business and with remote work. This project aims to innovate through identification of gaps, to implement changes in our people operations (hiring operations, training, and performance management). CrucialLogics must adapt and innovate our work culture and approach to ensure that we have the right talent, and that they are supported to achieve success. CrucialLogics is at a turning point as far as its ability to properly support its clients, and to scale to support future ones and HR is required. As different generations and technologies enter both the workforce, as well as that of our customers, its imperative that we continue to innovate and hear ideas and the voices of academia.

Technical Analyst

Technical Analyst to enhance service delivery processes and ensure digitization of key data.