Innovative Projects Realized

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

29670 Completed Projects

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801
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663
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825
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8841
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9197
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95
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568
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Projects by Category

Interactive Annotations of Large-Scale Image Data for Training of Recognition Models

The main objective of this project is to investigate, develop and evaluate state-of-the-art color image/video analysis and machine-learning algorithms, which are suitable for accurate modeling and recognition from large-scale image datasets that are weakly labeled. In particular, we will focus on investigating and developing interactive (partially-supervised) algorithms for annotating massive sets of color images, while minimizing the user efforts. The ultimate goal is to build stat-of-the-art color image classification models, a computer vision application area of high interest to QuindiTech. The specific objectives are: (1) Interactive object delineations in massive image/video data sets; and (2) Active categorization of images at a web-scale level. Learning weakly supervised image recognition models typically leads to complex and ill-posed optimization problems. This project will leverage some limited and targeted interactions with humans, as needed, to set optimization constraints and to drive advanced learning methods. TO BE CONT’D

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Faculty Supervisor:

Ismail Ben Ayed;Éric Granger

Student:

Partner:

QuindiTech

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

The influence of local and global stressors on coral reef ecosystems

Vibrant coral reefs are amongst the world’s most diverse and economically important marine ecosystems, but are also imminently threatened by climate change and local threats, including fishing and pollution. Understanding how these threats impact coral reefs, and the capacity for reefs to recover after bleaching events is critically important. This project will focus on Kiritimati (Christmas Island), a ‘natural laboratory’ in the equatorial Pacific Ocean, which experienced extensive coral bleaching during a recent intense heat wave. We will use underwater surveys and videos, along with novel acoustic and imagery methods, to quantify how coral and fish communities, as well as the structure of the reef habitat itself, have changed in the four years following the event. We will also examine if underwater acoustics can be used to assess reef health. This information will inform World Wildlife Fund’s Coral Reef High Impact Initiative’s efforts to develop solutions for coral reef conservation.

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Faculty Supervisor:

Julia Baum

Student:

Partner:

World Wildlife Fund (St. John's, NL)

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

University of Victoria

Program:

Accelerate

Bipolar Membranes for Electrochemical Technologies

Bipolar membranes (BPMs) are already a commercially relevant technology as they are used in the electrodialysis process, that is, they are used to convert salt water into industrially useful acid and base products. Recent research, on the laboratory scale, has demonstrated that bipolar membranes also have useful applications in water splitting technologies that produce hydrogen gas, which can then be captured, stored and used as an alternative to fossil fuels. This project aims to develop next-generation bipolar membranes by combining the cutting-edge membrane technologies developed at Simon Fraser University with the industrial throughput capabilities of Ionomr Innovations Inc.

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Faculty Supervisor:

Steven Holdcroft

Student:

Partner:

Ionomr Innovations Inc

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Building a framework to use banking data for learning, warning, and prevention

This project, in partnership with ATB Financial, will focus on the application and development of machine learning techniques in banking. We will delve into early prediction of customer events, such as encountering financial difficulties, that could indicate other issues and present opportune moments for ATB Financial to help customers get back on track. We will develop a framework to make statistical inferences from such early predictions of customer events to measure more accurately risks across the financial institution. Analyzing the situation around the 2016 Fort McMurray wildfire, a particular focus will be on the study of how people react to a disaster and change their banking transactions in such an event.

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Faculty Supervisor:

Christoph Frei

Student:

Partner:

ATB Financial

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

University of Alberta

Program:

Accelerate

Global Dynamic Financial CGE Model

This project aims to develop a dynamic financial computable general equilibrium model (CGE) with interaction between real and financial side of the world economy. It seeks to understand how monetary policy changes such as interest rate changes, QE measures, and exchange rate changes affect the real economy by applying the financial dynamic CGE model. This project collaborates with the partner organization–the Infinite-Sum Modeling Inc.—to build a CGE-FDI database and to develop the financial CGE model. It will provide the partner organization and the academic institutions with a model of policy simulation to unde

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Faculty Supervisor:

Jing Li

Student:

Partner:

Infinite-Sum Modeling Inc;Beijing Technology and Business University

Discipline:

Sociology

Sector:

Finance and Insurance

University:

Simon Fraser University

Program:

Accelerate

Étude des contraintes mécaniques des films de MgO : mise en évidence de gradients diminuant la symétrie locale par la spectroscopie TERS

De nos jours, les ordinateurs, les téléphones cellulaires et beaucoup de gadgets électroniques voient leur taille diminuer de plus en plus au fur et à mesure que les années passent. Actuellement, la technologie de ces dispositifs électroniques est basée sur le silicium. Or, le silicium atteint les limites de sa performance plus la taille des dispositifs électroniques diminue. Les chercheurs doivent donc trouver d’autres moyens pour fabriquer les mêmes appareils mais sans utiliser le silicium. Le film de MgO est le candidat idéal qui entre dans la fabrication des jonctions de tunnel magnétiques (JTM) qui constituent la composante essentielle des mémoires magnétorésistives volatiles à transfert de spin. Mais lorsqu’on dépose le MgO sur un autre matériau pour fabriquer les JTM, il y a apparition de contraintes mécaniques qui altèrent significativement les propriétés électriques et optiques du MgO. Mon projet de recherche consiste à calculer les contraintes mécaniques occasionnées dans les films de MgO à l’aide de simulations numériques afin de valider nos résultats expérimentaux obtenus par TERS […]

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Faculty Supervisor:

Andreas Ruediger

Student:

Partner:

Université de Toulon

Discipline:

Physics

Sector:

Nanotechnology; Advanced Manufacturing; Technology

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Globalink Research Award

Beyond Diffusion: Animal-Mediated Nutrient Transport at Different Spatial Scales

Ecosystems are linked by exchanges of both energy and matter. These exchanges can be passive, as in water run-off, or active, as when an animal moves between ecosystems. These two types of exchanges can act against each other but, while research has focused on passive exchanges, not much is known about active exchanges. In this project, we propose to develop a mathematical model to describe how animals move matter between different ecosystems via the most common form of movement: foraging. Our foraging model will include the distance between two ecosystems, the quantity and quality of food available, and the risk of finding a predator. We will validate our model with real-world data from two different study systems, the alpine highlands of Argentina’s Andes and the boreal forests of central Newfoundland. Our foraging model will be a useful tool for researchers, managers and policy-makers to address real-world issues, such as the active transfer of artificial chemicals from croplands to forests by wild herbivores foraging in the former and resting in the latter.

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Faculty Supervisor:

Shawn Leroux

Student:

Partner:

Yale University

Discipline:

Life Sciences

Sector:

Education

University:

Memorial University of Newfoundland

Program:

Globalink Research Award

Intégration de la fabrication additive pour accélérer le cycle de développement de simulateurs médicaux

CAE Santé a besoin de fournir rapidement des simulateurs médicaux à ses clients et de concevoir des prototypes fonctionnels. L’objectif du stage est de mettre en place un outil d’aide à la décision en intégrant les procédés de fabrication additives afin qu’elle puisse diminuer ces cycles de développement de produit. L’outil permettra d’évaluer les pièces conçues par CAE Santé en matière de spécifications techniques, économiques et délais de mise en forme afin de proposer des processus alternatifs qui permettront une mise sur le marché plus rapidement tout en garantissant l’efficacité des pièces existantes. Enfin cet outil devra prendre aussi en considérant les méthodes organisationnelles actuelles employées par CAE Santé lors du développement d’une nouvelle pièce.

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Faculty Supervisor:

Sylvie Doré

Student:

Partner:

CAE

Discipline:

Engineering

Sector:

Advanced Manufacturing; Health and Related Sciences & Technology; Technology

University:

École de technologie supérieure

Program:

Accelerate

Synthesis of an irreversible inhibitor of Pol?

One aspect of modern drug development involves understanding how enzymes function in terms of the progress of certain diseases in humans. This MITACS project involves the synthesis of small-molecule labels that can bind to a specific enzyme of interest, so as to better understand the mode of action of this enzyme as related to the progress of cancer. This work will involve the preparation of organic molecules possessing appropriate structural features that will enable selective and irreversible binding to the desired enzyme. The understanding gained as a result will enable the partner organization (Repare Therapeutics) to develop more effective treatments for cancer.

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Faculty Supervisor:

Mark Stradiotto

Student:

Partner:

Repare Therapeutics

Discipline:

Physics

Sector:

Manufacturing

University:

Dalhousie University

Program:

Accelerate

Design of a Multi-modal Electronic Stethoscope for the Digital Acquisition and Automatic Diagnosis of Auscultation Signals

The proposed research project aims to develop a multi-modal stethoscope, containing superior digitized heart and lung sounds, telemedicine capabilities and assistive diagnostics. This is achieved by leveraging new advancements in piezo, microphone, wireless and machine learning technologies. The project will investigate these technologies and integrate them into custom made electronics and mechanical designs to achieve an optimal digitized sound that provides superior auscultation capabilities to medical professionals for lung and heart sound diagnosis. Furthermore, a streaming application will be created to visualize, store and share the digitized data for demonstration of telemedicine capabilities. Machine learning algorithms developed during the research project will also be applied to the data to provide a prototype of the assistive diagnostics capabilities of the proposed product. The partner will benefit from the novel prototype developed during the research project as it demonstrates a highly versatile product for medical professionals that can be commercialized.

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Faculty Supervisor:

Christopher Yip

Student:

Partner:

Impact Center;9868208 CANADA INC

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Advanced machine learning techniques for ore body modelling

Geostatistical techniques offer a means of mathematically approximating the spatial patterns of geological parameters. The geostatistical interpolation and simulation methods are commonly used for modeling ore bodies. The accuracy of these models has significant impacts on the reliability of mine planning and design. The proposed research project aims to apply advanced machine learning methods, geared specifically to the drillhole data type, to better predict the spatial distribution of rock properties (e.g. ore grade and rock hardness) in metallic ore bodies. Both classical and quantum machine learning techniques will be used to develop the ore body models. The accuracy of the machine learning models will be compared to the geostatistical models and with the field data.

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Faculty Supervisor:

Kamran Esmaeili

Student:

Partner:

StratumAI Inc

Discipline:

Engineering

Sector:

Mining

University:

University of Toronto

Program:

Accelerate

Novel Additives to Enhance the Delivery of Foliar Crop Sprays

Crop yield is increasingly important for feeding the global population and making Canada a more self-sustaining country. Active AgriScience is a BC based company that is developing novel technologies and formulati,ons for improving yield in many types of crops including canota, wheat, com, barley, and others. One of the key services that !clive AgriScience offers is the ability to combine a number of agrochemicals into a single formulation, while maintaining the stability and benefits of each individual ingredient. Combining multiple ingredients into a single solution greatly reduces the amount of work required for delivery to the plants, such as reducing the total volume and number of passes in crop spraying. This project aims to combine both optimal chemistry and physical properties to generate better ferti lizers for crop spraying.

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Faculty Supervisor:

John M Frostad

Student:

Partner:

Active AgriScience

Discipline:

Engineering

Sector:

Agriculture

University:

The University of British Columbia

Program:

Accelerate

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