Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

30156 Completed Projects

2861
AB
5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
NS

Projects by Category

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

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Faculty Supervisor:

Jacques CORBEIL

Student:

Partner:

Phytronix Technologies Inc;Héma-Québec (Montreal)

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Other; Biotechnology

University:

Université Laval

Program:

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.

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Faculty Supervisor:

Caroline Desbiens

Student:

Partner:

Glencore Canada Corporation - Raglan Mine

Discipline:

Computer science

Sector:

Mining

University:

Université Laval

Program:

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.

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Faculty Supervisor:

Vahab Khoshdel

Student:

Partner:

Wealthsimple Technologies

Discipline:

Computer science

Sector:

Information and cultural industries; Mining

University:

University of Manitoba

Program:

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.

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Faculty Supervisor:

Tasseda Boukherroub

Student:

Partner:

Société de transport de Montréal

Discipline:

Engineering

Sector:

Transportation and warehousing

University:

École de technologie supérieure

Program:

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.

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Faculty Supervisor:

Yaoyao Fiona Zhao

Student:

Partner:

Proco Innovation

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

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

PROJECT OVERVIEW MISSING – NEEDS TO BE UPDATED INTO MOL

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Faculty Supervisor:

Simon Watkins

Student:

Partner:

Hyperlume

Discipline:

Physics

Sector:

Information and cultural industries; Manufacturing

University:

Simon Fraser University

Program:

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.

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Faculty Supervisor:

Sandra Dorman;Alison Godwin

Student:

Partner:

Vale Canada

Discipline:

Life Sciences

Sector:

Mining

University:

Laurentian University

Program:

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.

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Faculty Supervisor:

Kadiata Ba

Student:

Partner:

AluQuébec

Discipline:

Engineering

Sector:

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

University:

Université du Québec à Chicoutimi

Program:

Accelerate

Development of spectroscopic imaging technology for grain quality inspection

Fusarium fungi infestation causes Canadian grain producers a loss of almost $1 billion dollars per year. Fusarium fungi produce toxins, e.g., deoxynivalenol (DON) which cause toxic effects in animals and possibly humans. We will develop a portable hand-held hyperspectral imaging device to detect, in the field, Fusarium infestation in grains. We will also evaluate the applicability of spectroscopic Optical Coherence Tomography to accurately and quickly determine DON level in grains with high sensitivity (1 ppm to 10 ppm). Such accurate, fast, practical and sensitive spectroscopic imaging technology could be widely deployed on farms to help farmers store pathogen-free grains. The industrial partner, Channel Systems, is a vendor of hyperspectral imaging systems. The availability of a portable handheld hyperspectral imaging hardware, as well as novel grain quality inspection application, would increase the market share of the industrial partner. It will result in considerable economic benefits for the industrial partner and Canada

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Faculty Supervisor:

Sherif Sherif

Student:

Partner:

Channel Systems Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Distributed and Partitioned Join Index

The overall goal of this internship is to improve the query capacity of the Informatica Data Vault data management system. In particular, better support for join operations, that combine the information of various tables of data warehousing appliactions, will be provided. For that, a specialized join index will be designed, developed and evaluated on standard data warehousing queries. The goal is to partition and distribute the index in order to be efficient in terms of storage requirement, query performance and manageability. The improved join performance within the Data Vault architecture will allow for better query performance scalability and predictability. These are crucial for Informatica to address new use cases and improve its capability to play an important role in the areas of Big Data and Internet data.

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Faculty Supervisor:

Bettina Kemme

Student:

Partner:

Informatica

Discipline:

Computer science

Sector:

Information and Communications Technology

University:

McGill University

Program:

Accelerate

Targeted synthetic and biosimilar disease modifying antirheumatic drugs in pregnancy: Patterns of use among females with rheumatic diseases and outcomes

Our proposed research project aims to answer the overall question: how do new arthritis medications taken during pregnancy affect mothers and their children? Many types of arthritis strike in females during their childbearing years. Even though we now know more about the effects of arthritis drugs when taken during pregnancy, the picture is not yet complete. Most of what we know is on impacts on babies with lesser information about impacts into childhood and on mothers. We also do not know how very much about how newer drugs, such as biosimilars and targeted therapies, are being used during pregnancy and their impacts. To solve this problem, we will use “big healthcare data” in British Columbia (BC) which contains key information on prescription drugs and a pregnancy registry. We will apply state-of-the art statistical methods to these data to study use of these medications during pregnancy and the health of mothers and their children.

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Faculty Supervisor:

Mary De Vera

Student:

Partner:

Arthritis Research Canada

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Pharmaceuticals

University:

The University of British Columbia

Program:

Accelerate

Apprentissage machine fiable pour la centrale électrique virtuelle québécoise

L’apprentissage machine est un outil extrêmement polyvalent qui ne cesse de gagner en popularité à l’ère des données. Il peine pourtant à obtenir l’acceptabilité industrielle en énergie. Traditionnellement, l’apprentissage machine est peu interpré-table, n’offre pas de garanties de performance et est parfois imprévisible; ces particularités nuisent à la confiance qu’on lui accorde et freine son intégration dans un secteur aussi sensible que l’énergie. Dans ce projet, on cherche à développer de nouveaux modèles d’apprentissage machine fiable pour répondre directement aux besoins d’Hilo, la filiale d’Hydro-Québec en charge de monter la centrale virtuelle québécoise. Ces modèles serviront principalement à améliorer l’algorithme de pré-diction de la consommation normale (baseline) des immeubles commerciaux intégrés à la solution Hilo.

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Faculty Supervisor:

Antoine Lesage-Landry

Student:

Partner:

Hilo

Discipline:

Engineering

Sector:

Utilities

University:

Polytechnique Montréal

Program:

Accelerate

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