This research project aims at applying machine learning over the existing financial forecasting methods currently employed in the commercial real estate industry. Businesses are actively collecting more data than what can be analyzed effectively using the standard spreadsheet models which have become industry standard over the past few decades. Machine learning algorithms are known to […]

This project develops a new project management method for software development targeting next-generation network providing unprecedented quality of cellular service to Canadians and small and medium businesses, stimulating innovations and improving the quality of life of our people. Relying on the ENCQOR infrastructure, which is the first 5G network in Canada supported by three governments […]

This Phase I proposal is intended to undertake a requirements-gathering and an initial system design for a system that exploits the integrity guarantees of blockchain technology and the high throughput capability of commercial/open source transactional database management systems (DBMS). Although current approaches will be a part of the solution, innovation is required to allow for […]

For both aircraft assembly and maintenance, mechanics need to quickly access information about parts and determine part numbers. Part numbers can be retrieved from 3D models of the aircraft but locating such models within an airplane is very difficult, particularly on small mobile devices. An additional complication is that the objects to be recognized are […]

The main objective of the project is to upgrade the existing system at Gnowit to create a complex self learning automated decision support system. The system(crawlers) will automatically collect all the data related to any company, political system or a specific entity from the articles, blogs and reviews and create a more actionable report. The […]

Ce projet vise à développer et approfondir les connaissances et techniques nécessaires à la mise en oeuvre des algorithmes d’intelligence artificielle sur des données issues du monde réel. En partenariat avec de multiples acteurs industriels de la grande région de Québec, la Faculté de Science et Génie de l’université Laval, au travers de ses étudiants […]

It is not fully understood how structural brain connectivities give rise to functional brain connectivities. The objective of this project is to apply Deep Learning and Machine Learning techniques to explore the complex relationship between structural and functional brain connectivities and accurately describe this important structure-function relationship. A linear brain dynamic network model will be […]

Generative models enable the researchers to address multiple problems spanning from noise removal to generating novel samples with properties of the domain. Generative models are commonly studied for images and in this project the idea will be expanded to 3D structures or volumes. Single-particle cryo-electron microscopy (cryo-EM) is a technique to estimate accurate 3D structures […]

OPTIC is a state of the art piece of research software designed to allow computers to autonomously plan complex tasks, such as construction projects, rail timetables and other planning and scheduling tasks. Currently, OPTIC handles the scheduling process using a technique known as Mixed Integer Programming (MIP). In this project, the aim will be to […]

Recent progress on word and sentence embeddings has enabled efficient representation and learning of complex high dimensional probability distributions over rich text data. The proposed research aims at addressing some of the fundamental questions in this field: What are the natural mathematical structures on that latent spaces? How to find a meaningful basis? What is […]

We address the problem of 3D human body motion capture and prediction to be used in the context of a live music concert performances. The difficulty of capturing the motion of a performer in this context comes from the harsh environment in which it takes place that includes strong and varying lighting, smoke generators, and […]

Cancer develops from the accumulation of mutations in key genes, which drive disease progression in individual patients. Currently, cancer genomic analysis results in the reporting of dozens to hundreds of mutations and other genomic alterations, without providing any indication of which genes are the most functional, and relevant for the survival of the cancer cell. […]