This project focuses on improving the trustworthiness of a RISC-V processor design intended for use in aircraft systems by carefully checking that it works correctly and securely. Modern aircraft depend heavily on software and digital hardware, so even small design errors or hidden security weaknesses can create safety risks. The project will verify a security-enhanced […]

The project advances the development of an AI-based system for automatic cutting tool condition characterization using machine learning and machine vision. It addresses the limitations of indirect tool wear monitoring by enabling direct, image-based wear analysis both on- and off-machine, with a focus on reducing downtime and improving tool utilization. A key challenge is adapting […]

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, […]

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 […]

This project seeks to improve the understanding of how Machine-Learning (ML)-specific code issues arise during software development by using Large Language Models to analyze developers’ code changes over time. An automated framework will be created to track code updates, detect ML-related issues, and identify the type of developer activity (feature development, bug fixing, enhancement, or […]

La création d’images de synthèse ultra-réalistes nécessite des calculs de lumière complexes, souvent trop longs pour les besoins actuels. Les algorithmes récents (tels que ReSTIR) accélèrent le rendu en réutilisant les informations lumineuses d’une image à l’autre, mais ils risquent d’introduire des distorsions visuelles. L’objectif de ce stage est d’analyser les statistiques de ces méthodes […]

This project will help improve BenchBoss, a sports performance tracking app created by Breton Group, by moving it from an early prototype to a fully tested and reliable platform. The intern will research better ways to capture real-time performance data, build and validate easy-to-understand analytics dashboards, and test the app with youth coaches and parents […]

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 […]

In the context of developing an academic activity as part of the intern’s postgraduate studies and building a new international research collaboration, the University of Alberta and the Tecnológico de Monterrey propose this research stay project, promoting a strategic initiative of artificial intelligence (AI) and the establishment of Industry 5.0 in fields such as agriculture […]

This project will design a new AI system to help Ciena’s Blue Planet division automatically understand and solve complex problems in communication networks. Currently, AI tools can only answer simple, fact-based questions. The research intern will develop a more advanced “GraphRAG” system that connects all network data—like equipment status and error logs—into a smart knowledge […]

This Master’s thesis project, conducted under a Mitacs Globalink research internship, aims to address persistent challenges in hospital pharmaceutical supply management—such as fluctuating medication demand, supply-chain delays, and inefficient manual forecasting—by developing an end-to-end AI-enabled solution. Using a large dataset of 6 million prescription records and 2 million stock movement entries, the student will apply […]

The project explores how to enable robots to perform multi-step tasks in realistic, changing environments by integrating visual information in different aspects of planning. Instead of assuming a perfect internal map of all objects, we will use camera input both to understand the scene and to guide the robot’s decisions during planning and execution. Demonstrations […]