Innovative Projects Realized

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

31133 Completed Projects

2940
AB
5159
BC
837
MB
685
NL
882
SK
9292
ON
9695
QC
97
PE
601
NB
1161
NS

Projects by Category

Arctic Research Foundation – Serverless DevOp

The general objective of this project is to ensure that the development cycles for the ongoing ARF project are reliable and will focus on areas of Continuous Integration and Continuous Deployment (CI/CD). Automated testing evaluating and using tools such as Cypress or Enzyme and increasing observability of the solution by exploring tools like AWS XRay or Lumigo and determining if they fit the needs of ARF. Time permitting, analyzing, and determining a strategy for Dynamodb backups, and recommending a solution will be pursued.

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Faculty Supervisor:

Johnathan Niziol

Student:

Partner:

Arctic Research Foundation

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Red River College Polytechnic

Program:

Business Strategy Internship

Apprentissage professionnel en situation de travail des enseignants: comparaison internationale

Le développement professionnel des enseignants est reconnu comme un levier incontournable d’amélioration des systèmes éducatifs. Après des décennies de recherches consacrées à l’apprentissage par la formation, l’apprentissage « informel » (Kyndt et al., 2016; Lecat et al., 2020) ou « au et par » le travail (Bourgeois & Mornata, 2012) occupe dorénavant le centre de l’attention de la communauté scientifique et des décideurs politiques. Or, les conditions de travail (et donc d’apprentissage) des enseignants sont très diverses de par le monde (OCDE, 2021). Dans certains systèmes éducatifs (Chili, Québec…), le travail enseignant est faiblement multispatialisé (Enthoven et al., soumis), c’est-à-dire que la majorité des tâches professionnelles des enseignants sont effectuées dans l’établissement scolaire (heures de cours, préparations, corrections, collaboration). A l’inverse, dans d’autres systèmes éducatifs (Belgique, Turquie…), le travail est fortement multispatialisé. L’établissement scolaire y est avant tout perçu comme un lieu d’enseignement et les enseignants effectuent nombre de tâches professionnelles en dehors de l’établissement, notamment à leur domicile.

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Faculty Supervisor:

Adriana Morales-Perlaza

Student:

Partner:

Université Catholique de Louvain

Discipline:

Sociology

Sector:

Education

University:

Université de Montréal

Program:

Globalink Research Award

Cold Spray Additive Manufacturing of a Ti-Zr-Ni shape memory alloy for future large deployable aerospace components.

Shape Memory Alloys (SMA) are smart materials capable of recovering large inelastic strains. SMA are therefore excellent candidates for applications where deformation needs to be controlled remotely. One of the main challenges holding back a wider acceptance of SMA is their poor workability leading to high tool wear when manufactured by machining. Additive Manufacturing, also known as 3D printing, is an alternative to subtractive shaping processes as it offers a solution to build complex near net shape components requiring minimum to no machining. In this project, the properties of a Ti-Zr-Ni shape memory alloy produced by Cold Spray Additive Manufacturing (CSAM) will assessed. The investigation will provide crucial information to conclude if Ti-Zr-Ni CSAM is a good candidate for large deployable parts.

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Faculty Supervisor:

Myriam Brochu

Student:

Partner:

Japan Aerospace Exploration Agency

Discipline:

Engineering

Sector:

Aerospace; Advanced Manufacturing; Technology

University:

Polytechnique Montréal

Program:

Globalink Research Award

Uncovering the biomechanical and perceptual factors contributing to performance improvements while running in different lower limb compression apparel

Running is a very popular, low-cost form of physical activity that is utilized by Canadians as a means to improve both physical fitness and mental health. Throughout all seasons experienced by most Canadians, runners use some form of compression apparel as a means to regulate temperature, improve performance, and enhance comfort. Using an iterative and comprehensive biomechanical and psychometric approach, this research aims to understand the physiological mechanisms underpinning how compression apparel of the lower limbs improves running performance while also enhancing comfort and experience of running. Once the main objectives of this research are achieved, the partner organization will be informed on how to tailor their compression apparel to the diverse characteristics of recreationally active runners in Canada.

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Faculty Supervisor:

Michael Asmussen

Student:

Partner:

Lululemon

Discipline:

Engineering

Sector:

Manufacturing; Retail trade

University:

Mount Royal University; Vancouver Island University

Program:

Accelerate

Stochastic Control in Network Coding Enabled Wireless Systems Year One

Network stochastic control is considered as a primary goal in the design of emerging wireless networks. One of the objectives in the stochastic control of wireless networks is to enable crosslayer designs to achieve stochastically optimal resource allocation in the physical and MAC layers. Different stochastic performance criteria can be considered in the optimal control of wireless networks. Delay is one of the most challenging ones and has been addressed far less in the literature. This project focuses on delay optimal stochastic control of network coding enabled systems which are considered as an important type of emerging wireless technologies in the last decade. More specifically, the goal of the project would be to study the existing stochastic optimization techniques (e.g., Lyapunov method, stochastic ordering, dynamic coupling, dynamic programming, etc.) and enhance them to apply in such systems. In this regard, delay is the main performance attribute we will study during this project.

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Faculty Supervisor:

loannis lambadaris

Student:

Partner:

Ericsson Canada Inc (Kanata, ON);Carleton University

Discipline:

Computer science

Sector:

Education

University:

Carleton University

Program:

Elevate

Quantification of biomolecular interactions

The aim of this project is to develop novel optical and microfluidic methods to extract quantitative metrics from biological interactions. Such quantitative information will be used to understand biophysical processes – such as binding of antibodies to a cell or tissue surface as well as improving decision making in diagnostic pathology. Towards these aims, we will develop methods that leverage novel microfluidic platforms for precise fluid control and optical tools for high sensitivity molecular detection. We expect this work to be integrated into existing workflows for quantitative measurements in various aspects of biological research.

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Faculty Supervisor:

Govind Kaigala

Student:

Partner:

ETH Zurich

Discipline:

Life Sciences

Sector:

Education

University:

The University of British Columbia

Program:

Globalink Research Award

Characterizing the wood construction waste stream in BC and evaluating the mechanical performance of new recycled products

Wood waste from Construction, Renovation and Demolition (CR&D) contributes about 7 % of the total waste sent to Canada’s municipal solid waste (MSW, or landfill) sites, according to a 2013 report from Natural Resources Canada (NRCan).
This preliminary project aims to consider viable alternatives to utilize waste wood to manufacture engineered wood products for the construction industry that account for variations in dimensions, moisture content, wood species, etc. The objective is to characterize the raw material available suitable for reuse in engineered wood products and assess their mechanical properties.
This project should demonstrate the potential for the recycling of wood waste, thus contributing to mitigate climate change by reducing the pressure on Canadian forests and the need for landfilling wood waste.

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Faculty Supervisor:

Julie Cool

Student:

Partner:

Urbanjacks

Discipline:

Earth science

Sector:

Sustainability & the Environment; Manufacturing and Construction; Clean Technology

University:

The University of British Columbia

Program:

Accelerate

Multi-hazard Risk & Resilience Assessment for Real Asset Decision-Support (continuation) – Asset Interdependency Risk

The proposed project is an extension of a previous project “Multi-hazard Risk & Resilience Assessment for Real Asset Decision-Support” which aims to develop a methodology and software for performing rapid high-resolution multi-hazard risk assessment for asset portfolios by combining commercial/publicly available hazard models with high-resolution vulnerabilities derived from multi-physics simulations of different asset archetypes. The proposed project adds a component that captures cascading risk due to interdependency through the use of network models, which will be implemented as part of the risk assessment software.
The expected outcome of the project will be a network module that can be integrated into Kinetica Risk’s existing risk assessment software to carry out portfolio risk studies. The project will also result in academic publications in high-resolution network models for capturing cascading risk.

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Faculty Supervisor:

David Bristow

Student:

Partner:

Kinetica Risk

Discipline:

Engineering

Sector:

Environmental Science and Technology; Sustainability & the Environment; Construction

University:

University of Victoria

Program:

Accelerate

A Flexible Development Pipeline for Optimal Anomaly Detection in Derivative Markets

When a previously trained machine learning model is put into production, the production phase begins where said model makes predictions on the inputs provided to it. When the distribution of production data changes over time, we talk about data drift. Then the model is likely to become less efficient, or even obsolete. The project consists of building an intelligent system capable of alerting in the event of a data drift that would have a significant impact on the system.

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Faculty Supervisor:

Maxime Lamothe;Foutse Khomh;Heng Li

Student:

Partner:

Bourse de Montréal

Discipline:

Engineering

Sector:

Finance and Insurance

University:

Polytechnique Montréal

Program:

Accelerate

Using Artificial Intelligence to Classify Interpersonal Skills

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 video recordings. The intern will develop a theoretical framework for integrating multimodal data with text-based classification models, create a text-based machine learning model to classify different aspects of judgmentalness from video recording transcripts, and integrate the model with existing services and data pipelines at Skillsetter. The project’s primary impact on the partner organization will be to substantially enhance the commercialization of their technology, including supporting their entry into new international markets. The project’s secondary impact will be to directly advance knowledge about the ability of machine learning algorithms to classify nuanced and contextual interpersonal communications.

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Faculty Supervisor:

Richard Zhao

Student:

Partner:

Skillsetter

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Calgary

Program:

Business Strategy Internship

Software Acceleration of Video Noise Filtering and its integration into real-time video applications

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 it commercially valuable and second to integrate this new real-time technology into video applications that require noise-free inputs in order for them to have high performance output. The architecture of personal computers allows us to use several processing units simultaneously and this lead to speed up significantly but the program code should be well managed to use all of these resources together. Since currently our code does not have this feature and processing speed is slower than desired, by modifying the program we expect to meet the acceptable speed. We are targeting two important applications: video compression and face recognition. Early investigation shows that we will noticeably improve their performance by either removing noise from their input or estimating that noise.

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Faculty Supervisor:

Aishy Amer

Student:

Partner:

TandemLaunch Inc

Discipline:

Computer science

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Real-time food analysis using deep learning for Diabetes Self -Monitoring Phase 2

Our proposed research is to create an algorithm capable of pre-evaluating diabetes patients’ meals before they consume them with the snap of a picture. We are attempting to accomplish this goal by employing AI, machine learning as well as computer vision for real-time analysis. Our goal is to analyse a user’s meal to return an accurate carb count and offer portion size adjustments to reduce their blood sugar fluctuations. By developing a model that uses these technologies, we believe we can create an algorithm that will revolutionize how diabetes patients manage their condition and allow users to maintain consistent and healthier blood sugar levels. This research will greatly benefit the partner organization as it will help accelerate the growth of development heavily on the technology side to bring this to a level where it can be commercialized to generate revenue and used by others.

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Faculty Supervisor:

Lueder Kahrs;Naimul Khan

Student:

Partner:

Glucose Vision

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

Toronto Metropolitan University; University of Toronto

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.