This partnership project with Hydro-Québec focuses on providing a better-informed optimization for service point location and modernizing the architecture of the optimization system. Our objective is to leverage the abundant data from Hydro-Québec to build robust forecasting models that can predict the workload demand at each potential or available service point. We also aim to […]

Brain segmentation is crucial for providing accurate predictions to the patients due to the information which can be extracted from it, such as the shape and size of the tissue, underdeveloped or injured regions, and annual comparative results for brain growth. Segmentation of infants’ brains currently requires deep expertise and is a labor-intensive process, typically […]

Ksalsuti Wellness Resources is seeking to create a mobile application to showcase the stories from the Turtle Island Series. The stories aim to improve to social and mental wellness of children by providing culturally relevant programming and materials from an Indigenous lens. These stories will have lessons embedded that focus on building positive self esteem, […]

Au niveau des municipalités, la gestion des ponceaux est de la responsabilité des gestionnaires de la voirie. Cependant, l’inventaire complet des ponceaux n’est pas toujours disponible en raison de l’éloignement de certaines zones rurales, et la non disponibilité historique des données du ministère des Transports du Québec pour ce type d’infrastructure. Afin de détecter et […]

En partenariat avec le compagnie XLKey, le projet vise à développer un système pour centraliser les données de milliers de producteurs agricoles afin de leur offrir des analyses qui leur permettront de situer la performance de leurs cultures et de leurs opérations par rapport à d’autres producteurs partageant des conditions semblables. Concrètement, en accumulant des […]

Incorporated in 2019, Medidas Digital created TrypScore, a mobile application designed to positively impact driving behaviour and help reduce the 1.35 million fatalities and 50 million serious injuries caused by vehicle collisions across the world each year. Unlike User-Based Insurance and telematics monitoring systems, TrypScore uses gamification, incentivization and engagement to put drivers at the […]

Today’s high performance computers offer the possibility of computing complex large scale computational fluid dynamics simulations in a reasonable time. In practice, exploting the thousands of computing cores to achieve the desired solution time is very challenging. These challenges include finding enough work to keep all these cores busy, and assigning work to different parts […]

Le nombre d’articles scientifiques a grandement augmenté ces dernières années dans la plupart des disciplines et notamment en chimie. Ce flux grandissant d’informations complique le suivi des innovations techniques issues de la recherche et leur intégration dans le processus de production par les entreprises du secteur de la chimie. Ce projet vise donc à développer […]

Conventional molecular discovery relies on high-throughput screening strategies (HTS) to identify molecules that match a specific set of user-defined properties. Unfortunately, due to the enormous size of chemical spaces (10^60 molecules in the case of the drug-like chemical space), HTS is usually performed over pre-built chemical libraries of moderate size, often by employing computational/AI methods […]

Canadians have experienced tremendous mental health challenges over the last few years. At the same time, systems to address mental health are over-burdened. There is thus a clear need to scalable and low-cost technologies that could support the mental and emotional wellbeing of Canadians. This project is about developing innovations in artificial intelligence that could […]

The project is mainly in the domain of achieving real-time computational speed of methods to remove noise from video signals (for example, those taken by a professional cinema camera). Specifically, in this project, we propose first to improve the speed of current technology that we have developed in previous MITACS projects, in order to make […]

This MITACS BSI project represents a collaboration between Skillsetter.com (an online interpersonal skills training company and Partner Organization) and members of the University of Calgary’s Department of Computer Science (Professor Richard Zaho [Academic Supervisor] and Mohamad Elzhobi [PhD Student and Project Intern]) aimed at developing a machine learning model to classify aspects of judgmentalness from […]