Projets novateurs réalisés

Automated Formalisation of Quantum Mathematical Proofs Using Machine Learning

This project aims to build an AI system that can turn regular, human-written math problems and solutions into fully checked, error-free formal proofs, with a special focus on quantum mathematics. The project will collect open-source quantum math problems, train a machine-learning model to translate them into formal proofs using the Lean proof assistant, and create an open dataset and simple converter tool that others can use.

The greatest benefit for the institutions participating in the research partnership will be the sharing of access to new toolkits, data, and approaches to trustworthy AI reasoning. Both University of Calgary and Technical University of Munich will benefit from the up-to-date knowledge and sharing of resources in the field of AI, formal verification, and quantum math. Valuable resources such as the dataset and the coverter system will contribute to their work in the fields of ML and mathematical reasoning. The work will result in a publication in an academic journal, which will improve both universities’ academic reputation.

Designing Responsible and Efficient AI Systems for IoT Threat Detection and Retrieval-Augmented Educational Assistance

This project explores two critical areas of AI research: cybersecurity for Internet of Things (IoT) systems and responsible AI assistants for education and research. IoT devices, widely used in healthcare, smart cities, and industry, are highly vulnerable to cyberattacks due to limited resources and large-scale connectivity. We propose AI-based intrusion detection systems that are lightweight, scalable, and capable of identifying both known and unknown threats in real time, balancing accuracy with computational efficiency.

Simultaneously, the project develops AI assistants using Retrieval-Augmented Generation (RAG) to support education and research. These assistants combine generative models with external knowledge retrieval to provide accurate, traceable, and ethically responsible guidance. They address common challenges such as hallucinations, biases, and lack of transparency, embedding safeguards for privacy, fairness, and user trust.

By integrating secure IoT monitoring with responsible AI applications, this project advances both technology and society. It strengthens the protection of critical digital infrastructures while providing reliable, transparent AI tools that enhance learning, research, and knowledge management. The outcomes aim to foster innovation in digital health, education, and cybersecurity, demonstrating AI that is both effective and responsible.

Equity meets efficiency: HIV treatment distribution

What’s the best way to distribute HIV treatment equitably? In developing countries, the major challenges are a lack of resources and infrastructure. In large developed countries like Australia and Canada, a major challenge is the geography and the clustering of populations. However, everyone deserves to have access to treatment, no matter where they live. This project will investigate the best way to distribute treatments so that patients have equal chance of reaching them, no matter where they are, thus satisfying both medical and ethical requirements.

Generation and Characterization of Camelid Nanobodies for Applications in Biomedical Research

Proteins control nearly all biological processes in animals, including growth, metabolism, immunity, and responses to stress or disease. To understand how proteins work, scientists often need tools that can bind to them very specifically and stabilize them for study. Nanobodies are a new type of antibody fragment derived from camelids such as alpacas. Unlike traditional antibodies, nanobodies are very small, highly stable, and able to bind tightly to regions of proteins that are otherwise difficult to study. Two nanobodies have been approved as drugs and many more are in clinical trials, and this is a growing field due to the advantages of nanobodies compared to mammalian antibodies.
In this project, the student will participate in the generation and characterization of nanobodies that bind to a target protein relevant to animal health and biological regulation. The work will involve selecting nanobodies from large libraries using phage display, testing their binding using biochemical assays, and producing selected nanobodies in bacterial systems. These nanobodies can then be used as research tools to help determine protein structure and function, which ultimately contributes to understanding disease mechanisms and identifying new therapeutic strategies.

Qualification des équipements de mesure géospatiale pour le suivi et la documentation des structures patrimoniales

Ce projet vise à améliorer la documentation et le suivi des bâtiments historiques à l’aide de technologies géospatiales avancées. Dans la dernière décenie, une émergence de nombreuses nouvelles technologies a vue le jour, mais une analyse sérieuse de la qualité des données reste indispensable. Le stagiaire contribuera en évaluant empiriquement différentes technologies de mesure géospatiale, telles que LiDAR statique et mobile, drones photogrammétriques, photogrammétrie terrestre et systèmes GNSS. Le projet comprend trois étapes principales : l’acquisition et la préparation de données géospatiales sur des bâtiments représentatifs, l’analyse comparative de la précision, de la cohérence spatiale et de la stabilité temporelle des mesures, et la synthèse des résultats pour produire des recommandations opérationnelles. L’objectif est de déterminer quels équipements et protocoles offrent les données les plus fiables et répétables pour le suivi des structures patrimoniales, en tenant compte des défis liés aux géométries complexes et aux contraintes d’accessibilité. Les résultats permettront de renforcer la conservation durable du patrimoine bâti en fournissant des modèles 3D détaillés, des évaluations précises de l’état des structures et des protocoles reproductibles pour d’autres sites patrimoniaux. Ce projet contribue ainsi à la modernisation des pratiques de surveillance et à l’amélioration de la gestion scientifique des bâtiments historiques.

Islamic Moral Economy in Iran: Intellectual Lineage and Its Marginalization in Post-Revolutionary Islamic Finance — A Doctoral Research Chapter

This project is part of my doctoral research and examines how Islamic moral economy developed in Iran and why it gradually lost institutional influence after the 1979 Revolution. In the early revolutionary period, Islamic economists promoted ideas centered on social justice, redistribution, and protection of the oppressed. Over time, these welfare oriented visions were replaced by a more legal and technical model of Islamic finance dominated by Islamic legal scholars and contract based regulation. The project studies the intellectual roots of Islamic moral economy, the key figures and debates that shaped it, and the political and institutional processes that led to its marginalization in financial policymaking. Research will be conducted at Durham University under the supervision of Professor Mehmet Asutay, a leading scholar in Islamic moral economy, and will produce a full dissertation chapter. The project benefits Durham University by contributing original analysis of a major but understudied national case of Islamic finance, strengthening its research on moral economy and political economy. It benefits the University of Ottawa by advancing doctoral training in law and finance through international collaboration, specialized mentorship, and access to scholarly networks unavailable in Canada. The project supports knowledge exchange between institutions and contributes shared understanding.

Experimental Set Up and Data Collection for DV and CV-QKD Optimization on Kirq Testbed

The objective of the project is to plan data collection for the design of machine learning models and algorithms capable of characterizing quantum interference between optical and quantum channels, or between quantum channels. We plan to use the NUMANA testbed to deploy the experiments to collect the required data. This will involve generating a quantum channel in conjunction with other optical channels, and then designing the data to be collected to characterize the interferences.

Reconstructing Past Redox and Microbial Environments in Deep-Sea Ferromanganese Deposit Minerals

Deep-sea ferromanganese nodules and crusts are not only potential resources for critical minerals such as cobalt and nickel, essential for the green energy transition and secondary battery technologies, but also valuable geological archives recording millions of years of ocean environmental history. However, traditional bulk geochemical analyses often fail to capture the fine-scale chemical and biological variations recorded within the microscopic growth layers of these deposits.

This project aims to reconstruct high-resolution records of past seafloor redox conditions and biological activity by combining sulfur isotope analysis of barite minerals preserved within ferromanganese deposits with organic matter mapping. These analyses will allow us to distinguish barite formed in the water column from that formed within sediments through microbial processes. This research will assess how reliably ferromanganese deposits record past ocean chemistry, and the role that microbial activity plays in their formation.

The project represents a strategic collaboration between Pusan National University (South Korea), providing unique intact deep-sea samples and micro-mineralogical analysis expertise, and the University of Saskatchewan (Canada), contributing world-class facilities for isotope and organic geochemical analyses. The results are expected to refine models of deep-sea mineral formation, supporting responsible resource development and improving our understanding of long-term environmental change in the deep ocean.

Understanding the role of astrocytes in neuroendocrine adaptation to stress

Stress signaling in the brain is critical for adaptation in the face of various challenges. Adaptation to stress requires the engagement of specific brain circuits that control production of stress hormones including cortisol, including the hypothalamus-pituitary-adrenal (HPA) axis. Overactivation of HPA axis however, results in pathological stress that can contribute to psychiatric disorders including anxiety depression. As the number of people in Canada living with anxiety and depression continues to rise, there is a pressing need to understand the brain circuits that regulate stress hormone levels and how these circuits malfunction in stress-related disorders.

In this project, we set out to investigate the fundamental mechanism underlying regulation of the stress hormone production with a specific focus on previously overlooked cells in the HPA axis – astrocytes. Our previous work has shown that astrocytes are highly sensitive to stress and that they drive various negative impacts of stress on behaviour. With this in mind, we hypothesize that these brain cells play a key role in regulating the HPA axis. This project will reveal the role of astrocytes in the neuroendocrine control of stress adaptation.

Analyse de la composition et la concentration de gaz plasma avec un appareil FTIR

À ce jour, les technologies de purification de l’air se base sur la filtration, où les contaminants sont emprisonnés dans des filtres, qui présentent certaines limites. Ce projet de recherche propose une nouvelle approche, une technologie de décontamination de l’air à partir de plasma froid et de la catalyse oxydative. Cette technologie permettrait non pas d’emprisonner, mais de décomposer divers polluants et bio pathogènes hautement résistant et ce sans produire de sous-produits nocifs. Une telle technologie pourrait être utilisée par des établissements publiques ou privés et par des environnements confinés tel que les cabines d’avions et modules habités de vaisseaux spaciaux. L’air serait décontaminé plus efficacement et pourrait garantir une purification efficace et totale de l’air ambiant, avantageant ainsi la santé publique et une meilleure préparation aux futures pandémies. La collaboration entre l’université Slovaque et l’UQAR sur ce projet permettrait à chacun de développer leurs champs d’expertise et de recherche en lien avec le plasma froid, ils seraient également les premiers pays à y développer des applications. Enfin, ce projet permettrait aussi aux étudiants des deux universités d’aller dans l’autre pays pour des stages ou des études.

Analyse de la dynamique des dunes sous-marines dans le Saint-Laurent

Ce projet de recherche porte sur l’étude des dunes sous-marines dans le fleuve et l’estuaire du Saint-Laurent, des structures sableuses mobiles situées sur le fond marin qui peuvent représenter un enjeu important pour la navigation. Plus précisément, le projet se concentre sur la Traverse du Nord du Saint-Laurent et certains secteurs au large de la Ville de Québec, où ces dunes sont particulièrement abondantes et actives en raison de forts courants.
L’objectif principal du projet est de mieux comprendre la forme et le déplacement de ces dunes à partir de données bathymétriques acquises par sonar multifaisceaux. Pour y parvenir, deux approches sont comparées : une méthode manuelle, basée sur l’interprétation experte des données, et une méthode automatisée utilisant des techniques d’analyse morphométrique. Cette comparaison permet d’évaluer la fiabilité, la précision et les limites de chaque méthode.
Le projet vise également à analyser l’évolution des dunes dans le temps, en comparant des levés réalisés à différentes périodes. Ces analyses contribuent à améliorer la compréhension des dynamiques sédimentaires dans l’estuaire du Saint-Laurent.

Etude théorique et numérique d’injection pulsée de gaz dans un plasma à ondes de surface

Lorsque l’on injecte du gaz dans un plasma (gaz chaud ionisé) à basse pression, beaucoup de phénomènes apparaissent. Ces phénomènes complexes semblent s’apparenter à des turbulences fluide et nécessitent l’utilisation d’outils numériques pour être compris.