The surge in data driven by economic expansion has increased the demand for fast, reliable internet. However, existing technologies struggle to keep up, causing video buffering, game lag, and slow file transfers. At the same time, rising cyber threats make data security a top concern, with high-profile breaches compromising millions of users and causing financial […]

Le projet propose une approche innovante d’instrumentation et de suivi des performances des ventilateurs industriels dédié à un banc de test selon la norme AMCA (Air Movement and Control Association). Dans le cadre du programme Lab2Market, cette initiative intègre des systèmes avancés de mesure et d’acquisition de données, permettant une surveillance en temps réel de […]

Rapid and accurate detection and classification of pathogens (viruses vs. bacteria) is a global challenge affecting healthcare, public health, and environmental safety. Current methods like PCR and CRISPR are accurate but slow, expensive, and require centralized labs and trained personnel. Rapid antigen tests are faster but lack accuracy and cannot differentiate between bacterial and viral […]

In light of the recent concerning growth of cyberattacks in pace, scale, and sophistication empowered by contemporary Artificial Intelligence (AI) techniques with multiple complex hacking and penetration tools, Small and Medium Businesses (SMBs) suffer continuous and serious technical, financial, and societal hits as severe damages of these attacks. This surge in cyberattacks boosted by AI […]

This project aims to explore whether brain tissue deformation, observed through a surgical microscope, can be used to estimate instrument-brain contact forces during epilepsy surgery. Two interns will work on key aspects: one will develop computer vision techniques to track tissue deformations in real time, while the other will create machine learning models to translate […]

This project explores how AI can create expressive, stylized portraits while keeping a person’s identity and emotions intact. By developing advanced AI models, it will help artists, enhance digital content creation, and support industries like entertainment, advertising, and cultural heritage. The technology can be used in museums for interactive exhibits, in film and gaming for […]

L’industrie minière canadienne joue un rôle clé dans l’économie nationale, représentant 5 % du PIB et employant directement plus de 400 000 personnes. Cependant, les arrêts non planifiés des broyeurs SAG Mill entraînent des pertes économiques considérables, atteignant plusieurs milliers de dollars par heure. Ce projet vise à répondre à ce défi en développant une […]

This research project focuses on using advanced machine learning techniques to better predict stock prices, specifically targeting stocks from the S&P 500. By combining powerful deep learning methods—such as LSTM and GRU networks—with adaptive attention mechanisms inspired by Transformer models, the project aims to create forecasting systems that can dynamically adapt to changing market conditions, […]

The past decade has revolutionized the astronomical observation of black holes. In 2015, the gravitational waves generated by the merger of two black holes were detected, which confirmed the predictions of general relativity and led to a Nobel prize. In 2019, an array of telescopes spread across the globe took the first image of a […]

The proposed project aims to develop a Quantum Convolutional Neural Network (QCNN)-based approach to detect vulnerabilities in smart contracts, which are critical components of blockchain technology. By leveraging quantum machine learning techniques, the project seeks to enhance the accuracy and efficiency of identifying security threats in smart contracts, such as reentrancy attacks and integer overflows. […]

This project aims to enhance the annotation of small nucleolar RNAs (snoRNAs) in the Rfam database, a key resource for classifying non-coding RNAs (ncRNAs). Rfam groups ncRNAs into families based on evolutionary relationships, using initial manual curation followed by a computational pipeline developed by the Rfam team. SnoRNAs are ncRNAs that guide RNA modification and […]

Standard medical imaging techniques used to diagnose and inform treatment of spinal conditions include X-Ray, computed tomography (CT), and magnetic resonance imaging (MRI). These images neglect to capture the in vivo dynamic behavior of the spine during activities of daily living, since patients remain as still as possible to capture clear image. In 2023, 20% […]