Ensuring the long-term stability and security of widely-used software is a critical operational challenge. A key part of this is “backporting,” the high-stakes process of deciding which updates to apply to stable product versions. Currently, developers often make these crucial risk-versus-value judgments without formal, data-driven guidance. This project will develop an intelligent decision-support framework to […]

Electric vehicle charging infrastructure has become a central component of transportation planning as adoption of electric vehicles accelerates worldwide. Modern research models how drivers choose a station using discrete choice models, especially multinomial logit, which capture realistic preferences such as distance, queues, and charging speed. These models are computationally expensive, making large-scale location planning challenging. […]

This project investigates the use of large language models (LLMs) as autonomous teammates to perform aircraft control, strategic reasoning, and team communication in complex aviation missions. We propose to design and evaluate an LLM-based “wingman” agent for a simulated collaborative aerial firefighting scenario, in which a human and AI fly their own aircraft to detect […]

Large software supply chains are necessary to support digitalization in all sectors. Meanwhile, these supply chains present new risks for companies, as witnessed by several news headlines in the last years. The SolarWinds attack in 2020 is a prominent example. The security of software supply chains is a priority of the Canadian Center for Cyber […]

The rise of quantum computing threatens traditional cryptographic systems such as RSA and ECC, which can be broken by quantum algorithms. This poses significant risks for the automotive industry, where in-vehicle communication networks must ensure both low latency and high data integrity. Modern vehicles rely on Controller Area Network Flexible Data-rate (CAN FD) and its […]

This research project addresses the critical future of cybersecurity in the age of quantum computing. As powerful quantum computers emerge, they threaten to break the encryption that currently protects our digital communications. To counter this, our project investigates Quantum Key Distribution (QKD), a technology that uses the principles of quantum mechanics to create encryption keys […]

In this project, we will develop a multi-objective and hybrid energy optimization framework for the optimum system cost and energy cost savings with a tolerable degree of customer discomfort. This framework will be based on artificial intelligence (AI) and artificial neural network (ANN) approaches for forecasting to track for maximum green energy production with the […]

This project explores whether surgical expertise can be measured from the way instruments move during a realistic neurosurgical simulation. The goal is to develop machine learning models that learn motion patterns from recorded instrument movements and use them to classify different levels of surgical skill. The dataset includes recordings from participants performing a surgical simulation […]

Autonomous systems such as intelligent vehicles and robotic platforms must reliably perceive their surroundings and reason about complex environments to make safe, informed decisions. Recent advances in Vision-Language Models (VLMs) and Vision-Language-Action (VLA) frameworks combine visual understanding with language-based reasoning, creating unified architectures for perception, interpretation, and decision-making. This integration enables autonomous agents to describe […]

Dans les systèmes de monitoring physiologique (comme l’ECG ou l’EEG), certains événements rares, par exemple une crise d’épilepsie ou un épisode d’hypoglycémie sévère, peuvent avoir des conséquences graves s’ils ne sont pas détectés à temps. Ces événements, souvent brefs et peu fréquents, sont pourtant cruciaux à identifier rapidement pour permettre une alerte précoce et prévenir […]

Drug discovery is traditionally slow, costly, and high-risk, with timelines exceeding a decade and expenses reaching billions. This lag is particularly problematic for neglected diseases and cardiovascular conditions, which carry significant global burdens but attract limited research investment. To address this, the project proposes leveraging quantum computing and hybrid quantum-classical algorithms to accelerate drug discovery. […]

At present, the data collected from the Fuel Management System (FMS) is only being used to a fraction of its potential. Our proposed solution is to delve into FMS data along with maintenance and operations information on critical mine site equipment such as heavy haul trucks, excavation equipment, and their light vehicle fleet to optimize […]