Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Utilizing Additive Manufacturing to Design an Enhanced Tool for Internal Skin Stitching during Colonoscopy Procedures

1 in 13 men in Canada is diagnosed with colon cancer every year. And 1 in 29 will die consequently. 1 in 16 women in Canada are similarly diagnosed leading to death in 1 out of 34 women. More than 90% of colon cancer cases start as a small benign growth called polyp. These polyps can be removed during a colonoscopy thus preventing colon cancer. When these polyps are large, the resulting defect can be a challenge to close.
Currently, the process used to close the defect is complicated, lengthy and requires highly skilled trained professional to perform it. We are still lacking proper way to achieve that. This project innovates a technique to facilitate successful completion of the procedure. This project will achieve a simpler, smoother and cost-effective technique for closing the defect.

Voir la description complète du projet
Superviseur du corps professoral :

Emeritus Mohamed Elbestawi

Étudiant :

Partenaire :

Makar Medical Research and Development

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

McMaster University

Programme :

Accelerate

Automated optimization of robotic tasks and transitions using graph-based approaches

In machining applications, the robot can rotate about the tool axis without affecting machining results. This additional freedom is beneficial in the sense that it can be used to avoid robot singularities, joint limits, collisions, etc. In this project, we will investigate methods of managing this additional degree of freedom automatically. Further, between operations, the robot must transition from the end of one operation to the start of the other operation. This transition must be collision free. In this project, we wil also investigate methods to manage such transition automaticaly.

Voir la description complète du projet
Superviseur du corps professoral :

Wen-Fang Xie

Étudiant :

Partenaire :

Hypertherm Robotic Software

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Concordia University

Programme :

Accelerate

L2M – Bio-inspired surface modifications of transepithelial implants to improve soft tissue seal and eliminate infections

Medical devices and implants that cross the skin do not seal well with the skin, making them prone to infections and eventually failure and removal. We propose a bio-inspired coating for these devices. This coating will help these devices adhere to the skin and prevent bacteria from entering the body and causing infections. The coated devices will have longer lifetime than the current ones, which will improve patients’ quality of life and reduce healthcare costs.

Voir la description complète du projet
Superviseur du corps professoral :

Marta Cerruti

Étudiant :

Partenaire :

Springboard Atlantic Inc.

Discipline :

Engineering

Secteur :

Biotechnology; Health and Related Sciences & Technology

Université :

McGill University

Programme :

Business Strategy Internship

L2M- Remote Care: Empowering patients through Remote Self-administered Medical assessment.

“RemoteCare” is a novel initiative that empowers individuals to conduct part of their medical assessments independently via a user-friendly remote digital solution. By enabling self-assessments, it reduces physician workload, minimizes wait times, and ensures quicker access to medical assistance, especially in underserved areas. However, its progress hinges on gaining the trust of traditional healthcare providers, navigating regulatory barriers, and customizing the solution through human-centric design. The “Lab2Market Mitacs BSI” program aids in these challenges by facilitating collaborations, mentorship, and knowledge exchange to create an efficient and accessible healthcare tool for all. By engaging with experts through the Lab2Market Mitacs program, “RemoteCare” aims to create a stronger, more resilient Canada by reducing strain on health resources, optimizing efficiency, and improving accessibility one person at a time.

Voir la description complète du projet
Superviseur du corps professoral :

Joseph Ferenbok

Étudiant :

Partenaire :

Springboard Atlantic Inc.

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

University of Toronto

Programme :

Business Strategy Internship

Improved quality control of blood products using high throughput mass spectrometry coupled to machine learning approaches.

We will assess the quality and suitability of blood and blood-derived products using a fast and economical approach that combines measurements of molecules in the blood product identified by their weight and computational approaches to make sense of all the data generated. Normal blood products have thousands of small molecules in common. By monitoring a large spectrum of these molecules, we will be in a position to determine the normal state and the quality of the products. Having determined the profile of molecules that are present in the normal conditions therefore any deviations should be considered abnormal and the product discarded or tested for degradation or infection by microbes. The process will increase the safety of blood and blood products in Canada and therefore will benefit all Canadians. The process will save money and time and provide new expertise for blood banks across our country. Moreover, the project will open new markets for our sponsor Phytronix

Voir la description complète du projet
Superviseur du corps professoral :

Jacques CORBEIL

Étudiant :

Partenaire :

Phytronix Technologies Inc;Héma-Québec (Montreal)

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology; Other; Biotechnology

Université :

Université Laval

Programme :

Accelerate

The Raglan Community Social Involvement (CSI) Project: Developing a Comprehensive Model with Inuit Partners

Raglan Mine is developing new, strategic and aligned approaches to its Community Social Involvement (CSI) program. The aim of this program is to partner with others to deliver long lasting value through programs of capacity building, and community social and economic development. This proposed research project involves further developing a comprehensive Community Social Involvement (CSI) model that responds to the needs and desires of both Raglan Mine and the villages of Nunavik. To do this, the intern will work closely with representatives from Glencore-Xstrata (head office), Raglan Mine, regional and local Inuit leaders, representatives from Inuit organizations, as well as community members. This Action-Research will benefit Raglan Mine because it responds to the desire of the company to create a lasting positive legacy in the communities closest to it. The comprehensive framework (CSI model) that will emerge from the results of this research project will not only form the basis for immediate action in Nunavik in 2014, but it will also serve as the foundation for other such initiatives in the future.

Voir la description complète du projet
Superviseur du corps professoral :

Caroline Desbiens

Étudiant :

Partenaire :

Glencore Canada Corporation - Raglan Mine

Discipline :

Computer science

Secteur :

Mining

Université :

Université Laval

Programme :

Accelerate

Application of Transformer Models to Raw Credit Bureau Files for Improved Credit Risk Modelling Performance

This research project will look at new ways to better understand and evaluate a person’s creditworthiness using advanced computer techniques. Traditionally, when banks or lenders decide if someone can be trusted with a loan, they look at specific numbers and data. However, there’s a lot of information in written reports that these traditional methods might miss. Our project will use a technology called Natural Language Processing (NLP) to read and analyze these reports in depth. By doing so, we hope to make credit evaluations more accurate. For the partnering organization, this means they can make better lending decisions, which can lead to increased profits and fewer bad loans.

Voir la description complète du projet
Superviseur du corps professoral :

Vahab Khoshdel

Étudiant :

Partenaire :

Wealthsimple Technologies

Discipline :

Computer science

Secteur :

Information and cultural industries; Mining

Université :

University of Manitoba

Programme :

Accelerate

Optimisation de la configuration et du déploiement d’une flotte de véhicules de service électriques

La Société de transport de Montréal (STM) souhaite électrifier sa flotte de véhicules de service (VS) d’ici 2027.
Cette transition suscite divers défis pour la recharge des batteries. Contrairement aux bus thermiques, qui nécessitent un arrêt de quelques minutes, les VS électriques doivent être immobilisés pendant plusieurs heures pour une recharge. Parmi ces 500 véhicules, une centaine, de type bureau, doit pouvoir être réquisitionnée à tout moment. Cette flotte a été dimensionnée de manière empirique, avec un coefficient de sécurité élevé, alors la question d’un redimensionnement pose un défi, car il faut prendre en compte les particularités de chaque type de véhicule. L’objectif ultime est de redimensionner la taille de la flotte afin de minimiser les coûts opérationnels. Ce problème sera formulé comme un problème d’optimisation mathématiques.

Voir la description complète du projet
Superviseur du corps professoral :

Tasseda Boukherroub

Étudiant :

Partenaire :

Société de transport de Montréal

Discipline :

Engineering

Secteur :

Transportation and warehousing

Université :

École de technologie supérieure

Programme :

Accelerate

Investigation on the Large Language Model adaptation pipeline for domain specific knowledge extraction – application in digitized business scenario

Proco, a tech company that helps franchises with AI, wants to make it easier for franchise owners to find important information in franchisors’ documentation. They use a complex information retrieval system and need a simpler and more robust solution. To do this, they plan to improve an existing Large Language Model (LLM) by teaching it to understand franchisor-related information better. They want to understand if this approach will work and, if it does, how to implement it efficiently. This will help them be less dependent on outside tools and get new franchise owners started faster. The intern’s job will be to create a step-by-step process to improve an LLM and make sure it works well.

Voir la description complète du projet
Superviseur du corps professoral :

Yaoyao Fiona Zhao

Étudiant :

Partenaire :

Proco Innovation

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Selective area growth of nonpolar GaN for micrometer scale light emitting diodes

PROJECT OVERVIEW MISSING – NEEDS TO BE UPDATED INTO MOL

Voir la description complète du projet
Superviseur du corps professoral :

Simon Watkins

Étudiant :

Partenaire :

Hyperlume

Discipline :

Physics

Secteur :

Information and cultural industries; Manufacturing

Université :

Simon Fraser University

Programme :

Accelerate

Heat stress evaluation amongst underground mine workers

Heat illness is a spectrum of disorders due to environmental exposure to heat. There is a growing need to combat worker heat exposure in mines, as a function of increasing mine depth. Vale’s Thermal Management Program is designed to protect workers from the hazards of hot conditions, but in dynamic work environments, and among workers with varying personal factors, it’s difficult to implement heat stress programs accurately. This project will describe the physiological states of underground mine workers, to understand the level of heat strain sustained at Creighton Mine, owned by Vale, Canada. The intern will describe mine worker’s workloads and work tasks, and quantify worker’s personal perceptions of heat stress and recovery, during a typical shift. Information from this study will be used to make recommendations for Vale’s Thermal Management Program.

Voir la description complète du projet
Superviseur du corps professoral :

Sandra Dorman;Alison Godwin

Étudiant :

Partenaire :

Vale Canada

Discipline :

Life Sciences

Secteur :

Mining

Université :

Laurentian University

Programme :

Accelerate

Évaluation et comparaison économique entre une passerelle en aluminium traditionnelle et une passerelle optimisée par conception assistée par ordinateur

Ce projet vise à comparer les gains économiques potentiels obtenus par la réduction des coûts entre une passerelle en aluminium conçue selon l’approche traditionnelle et une passerelle optimisée en utilisant une approche préliminaire d’optimisation topologique et dimensionnelle. L’objectif principal de cette comparaison est de démontrer les bénéfices économiques potentiels offerts par l’optimisation dans la conception de passerelles en aluminium. Les résultats obtenus contribueront à l’amélioration des pratiques de conception et pourront être appliqués dans des projets futurs pour optimiser les coûts et améliorer l’efficacité des structures en aluminium.

Voir la description complète du projet
Superviseur du corps professoral :

Kadiata Ba

Étudiant :

Partenaire :

AluQuébec

Discipline :

Engineering

Secteur :

Other services (except public administration); Professional, scientific and technical services

Université :

Université du Québec à Chicoutimi

Programme :

Accelerate

Précédent
1...869870871872873874875...2,543
Suivant

Joignez-vous à un écosystème d’innovation florissant.

Abonnez-vous à notre infolettre dès maintenant!

S’inscrire

Mitacs — Retour sur innovation

Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.