This project assesses the safety of blending hydrogen with natural gas in Québec’s pipeline network, which is a crucial step towards Canada’s transition to cleaner energy. During a 13-week research internship, the project will identify safety risks, such as material degradation and explosion hazards, using risk assessment tools like HyRAM+. The anticipated benefits are twofold: […]

This research investigates whether tensor networks can serve as interpretable surrogates for graph neural networks (GNNs). It explores whether tensor networks can approximate the functional behavior of GNNs while offering a more structured and interpretable internal representation. The project aims to quantify the contribution of nodes, edges, and features to predictions through this surrogate representation, […]

Antibiotic resistance is a rising threat worldwide, making infections increasingly hard to treat. This project aims to tackle this urgent issue by mapping out the hidden genetic relationships within harmful bacteria, including Escherichia coli and related pathogens. By analyzing vast amounts of genetic data, we will identify critical points—called genetic hubs—essential for bacterial survival. Targeting […]

Climate change is one of the main concerns of our society and is closely linked to the large consumption of fossil fuels and their associated carbon emissions. An appealing alternative is the production of hydrogen from water, powered by sunlight. Our project aims to develop a first family of efficient hybrid dyadic catalysts for this […]

Mobility-as-a-Service (MaaS) is an emerging service that enables users to plan, reserve, and pay for different on-demand and shared mobility services through an integrated platform. MaaS is relatively more advanced and widespread in European countries than in North America. In parts of Europe, shared mobility services can also be found in mobility hubs (dedicated on-street […]

Ce projet de recherche vise à mieux comprendre comment des orthèses de genou personnalisées peuvent aider les adolescents à prévenir les blessures graves au genou, notamment la rupture du ligament croisé antérieur (LCA). Ces blessures sont fréquentes chez les jeunes sportifs, surtout lorsqu’ils présentent un désalignement du genou appelé “valgus dynamique”. En s’appuyant sur des […]

Cancer leaves behind unique mutation patterns, known as mutational signatures, which provide insights into its origins and potential treatments. Traditionally, these signatures are identified using tumor tissue samples, but obtaining biopsies can be invasive and challenging. A promising alternative is circulating tumor DNA (ctDNA)—small fragments of tumor DNA found in the blood. Liquid biopsies offer […]

This project focuses on developing innovative, biocompatible microrobots for targeted drug delivery, particularly in cancer treatment. By integrating smart hydrogels with magneto-active properties, these tiny robots can navigate the body and deliver highly precise chemotherapy drugs, reducing side effects and improving patient outcomes. Advanced 3D microfabrication techniques, such as two-photon lithography and digital light processing, […]

The dramatic growth of the Internet has enhanced access to information, fostering seamless communication and promoting effective collaboration. Unfortunately, advanced network traffic control and monitoring systems have empowered state-level actors to deploy large-scale surveillance and censorship mechanisms that track people’s Internet activities or limit their ability to freely access and publish information. Recently, multiple initiatives […]

The use of orbital angular momentum (OAM) for free-space optical (FSO) communications is almost unexplored. The proposed research will investigate the bit-error rate (BER) performance of FSO systems using OAM. The analysis will begin by considering the ideal case of separable OAM-modulated FSO system performance, to be followed by the individual and combined effects of […]

This project will develop novel circuit metrics to predict model performance under realistic noise conditions, offering a practical approach to enhancing QML trainability. The research will investigate optimal parameter resilience across different circuit depths, qubit counts, and problem types, while comparing overparameterized and underparameterized regimes. Additionally, circuit metrics will be developed to predict model performance […]

Machine learning (ML) is transforming industries like IT, finance, and healthcare, but the code that powers these systems is still mostly written and updated by hand. This project explores how Large Language Models (LLMs) can assist developers by predicting and suggesting code edits for ML projects. By analyzing real-world code from public repositories, the research […]