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 […]

Quantum communication stands at the frontier of next-generation secure communication systems, leveraging the principles of quantum mechanics to address the limitations of classical cryptography. Among quantum-based techniques, Quantum Key Distribution (QKD) has emerged as a revolutionary solution enabling provably secure key exchange. While bipartite QKD protocols (such as BB84) are well-studied, there remains a significant […]

This project aims to improve the simulation of complex materials such as layered paint, fabrics and coated metals in computer graphics applications. We will develop a neural network-based sampling model that allows accurate and efficient light transport within these materials. In addition, we will integrate this model with general path-guiding techniques to minimize noise on […]

The proposed project aims to modernize the Township of Terrace Bay’s records and data management systems by integrating AI-powered tools that streamline operations and enhance decision-making. Currently reliant on manual processes and limited digital infrastructure, the municipality faces challenges in organizing, analyzing, and retrieving key service data. This initiative will introduce automated classification systems, predictive […]

Accurately assessing and managing pain in dogs is one of the most challenging aspects of veterinary medicine because animals cannot verbally communicate their discomfort. Current methods rely heavily on behavioral observations and standardized scoring tools, which are often subjective and prone to inconsistencies. This project aims to address these limitations by developing an AI-powered predictive […]