The 5G network provides an innovation in cloud assets delivery that will transform multiple application domains such as health care, autonomous driving, smart cities, Industry 4.0, etc. Relying on the ENCQOR infrastructure (the first 5G network in Canada), this research will apply machine learning to improve network failure detection and optimize network recovery for continuity […]

In this project the intern will work with an expert team from the company Xanadu, to explore new computational methods and approaches which could be helpful for optimizing hybrid calculations involving both classical and quantum computing combined together.

The intern shall participate in a research and development project to create applications for the Goodlocal organization, that will help the organization expand it’s support of local businesses by providing logistical and operational services. Goodlocal’s body of work have confirmed that their successful online marketplace has largely benefited local business owners and in line with […]

The intern shall participate in a research and development project to create applications for the Goodlocal organization, that will help the organization expand it’s support of local businesses by providing logistical and operational services. Goodlocal’s body of work have confirmed that their successful online marketplace has largely benefited local business owners and in line with […]

Tugboat has 1000s of questions and responses submitted by clients. Users upload questions which can be answered using the “Auto Answer” functionality. The “Auto Answer” technology leverages weighted search vectors to search answer databases and prioritize which answers to recommend for a given question. The objective of the project is to leverage this dataset by […]

This project aims to employ a universal design framework to employ a social robot-aided training system to support the visually impaired community in attaining an inclusive job interview process. The universal design framework advocates that any given environment is accessible by persons with disabilities, to the greatest extent possible, without the need for adaptation or […]

In medicine, imaging-based exams are used to support diagnostics, treatment planning andlor the treatment itself. Considering the number, integration and nature of devices in a multi-surface environment (e.g. smartphones, tablets, multi-touch surfaces and wall displays), this project proposes a system for imaging visualization and manipulation that takes advantages from each device’s capabilities in the environment. […]

L’objectif de ce projet pilote est d’équiper des drones longue portée avec un système complémentaire de navigation assistée par l’intelligence artificielle. Plus précisément, ce système permettra aux drones de mieux percevoir leur environnement et d’y réagir plus intelligemment. La principale préoccupation concernant les drones volant hors visibilité directe (HVD) est reliée au partage de l’espace […]

La compagnie XEOS Imagerie œuvre dans le domaine de l’acquisition de données lidar (Light Detection and Ranging). Elle désire extraire automatiquement les points associés au sol et aux objets à partir du nuage de points 3D brut de l’acquisition lidar. Deux stages précédents ont permis d’identifier les points « Sol » et « Eau ». […]

In light of the recent COVID-19 pandemic, contact tracing has been found an effective measure to mitigate the spread of the corresponding SARS-CoV-2 virus. The aim of contact tracing is to identify, notify and potentially quarantine persons who have been in close contact with infected individuals, thereby breaking the chain of infections. Next to manual […]

A Peer-to-Peer (P2P) lending platform allows small businesses to obtain working capital funds through an online system, where individuals can anonymously pool together funds for investment. Instead of relying on a third-party website for crowdfunding (such as Kickstarter and Indiegogo), we propose a decentralized platform for P2P. Unlike traditional P2P lending which is usually done […]

In many real-world machine learning problems, inadequate labeled data and extensive unlabeled data are usually available. Normally, unlabeled data is collected routinely, though the high cost associated with labeling the data is high for generating the labeled training dataset for supervised learning. Moreover, the lack of domain experts and the time-consuming data labeling, especially in […]