Innovative Projects Realized

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

31914 Completed Projects

3006
AB
5256
BC
878
MB
703
NL
913
SK
9488
ON
9949
QC
98
PE
629
NB
1215
NS

Projects by Category

Design and prototyping of reconfigurable intelligent surface (RIS) aided communication systems

Reconfigurable intelligent surface (RISs) are man-made surfaces of electromagnetic (EM) material that are electronically controlled with integrated electronics and have unique wireless communication capabilities. However, a major limitation of current research on RISs is the lack of accurate and tractable models that describe the reconfigurable meta-surfaces as a function of their EM properties. In addition, the details of the current experimental tests are often difficult to find, and are not sufficient to judge the actual potential of RISs in realistic operating conditions. Therefore, the first intern will contribute by proposing innovative RIS element structures along with their EM models. The second intern will develop a compressive testbed which consists of a versatile RIS module that includes both passive elements as well as a few active elements. The partner’s commitments during the design and prototyping phases will enable them to enlarge their offering and enhance their competitive advantage. The findings and advancements will provide sufficient insights on the use of RIS toward improving the radio network spectral and energy efficiency. This is also intimately related to the Canadian community concerns with respect to reducing the carbon footprint.

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Faculty Supervisor:

Messaoud Ahmed Ouameur

Student:

Partner:

BCi Technique

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

Validity and reliability of a novel alternative to force plate technology for position specific isometric strength tests and their relationship to dynamic performance in collegiate athletes

Ignite athletics is a strength and conditioning company that works with thousands of athletes every year. Ignite has developed new technology to improve the tracking and reliability of strength metrics, while simultaneously improving the cost, portability, and credibility. The goal of the project is to bring together
Engineers, Sport Scientists and Strength and Conditioning Coaches to validate new technology that can be used in a standard gym setting, mitigating the constraints that currently exist. The primary goal of this study is to determine the test-retest reliability and criterion validity of a new portable and low-cost device being developed called the “Force Finder”. The technology will be validated by comparing force-time characteristics measured from the Force Finder with those derived from the use of the gold standard force plates.

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Faculty Supervisor:

Jonathan Farthing;Joel Lanovaz

Student:

Partner:

Ignite Athletics Inc

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Individualizing high-intensity functional training (HIFT) for optimal fitness and health adaptations: exercise limitations and individualization with wearable technology

This project will bring together a motivated intern, an experienced researcher, and a nationally-ranked coach to solve a unique problem in the world of health and fitness. High-intensity functional training is a highly popular method of training, but is one that needs research on the physical and mental aspects to best design individualized training programs. With the addition of wearable technology during exercise, the research collaboration will identify the key aspects of the exercise training and the individuals who use it to optimize their adaptations to this training. The results of this work will help guide the programming for the partner organization, Synergy Strength, to assist their clients, and those across Canada using this methodology, in obtaining the best results possible.

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Faculty Supervisor:

Scotty Butcher;Philip Chilibeck

Student:

Partner:

Synergy Strength and Sports Therapy

Discipline:

Life Sciences

Sector:

Arts, entertainment and recreation

University:

University of Saskatchewan

Program:

Accelerate

Zooplankton species composition during hatching and development of Atlantic whitefish (Coregonus huntsmani) in the upper Petite Rivière watershed, Nova Scotia

This research project aims to build a greater understanding of the diet of endangered Atlantic whitefish. The only wild population in the world inhabits three lakes of the Petite Rivière watershed in Nova Scotia. The species has great historical significance being the most primitive of all whitefish species in Canada. Yet, there is little known about this unique fish, including their diet. Since 2018, the non-profit environmental organization, Coastal Action, has collected samples of tiny aquatic invertebrates, zooplankton, which are a main food source for juveniles. Previously, samples were collected monthly from Atlantic whitefish habitat from June through September, and specimens were identified to determine the diversity of zooplankton species. This project intends to build on these records by sampling weekly, starting in late winter rather than early summer, which will provide insight on the availability of different zooplankton species during a critical period of juvenile Atlantic whitefish development.

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Faculty Supervisor:

Paul Bentzen

Student:

Partner:

Coastal Action

Discipline:

Life Sciences

Sector:

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

University:

Dalhousie University

Program:

Accelerate

Optimizing the delivery of ministring DNA (msDNA) to the central nervous system for use in gene therapy applications

Gene therapy has risen as one of the more promising treatment options for disorders of the central nervous system (CNS). Using modified viruses to deliver genetic material has shown success however has several disadvantages including increased safety risks. Using a non-viral vector system has the potential to overcome many of the challenges that arise with using viral vectors. Mediphage Bioceuticals proprietary DNA construct, ministring DNA (msDNA) is a non-viral system that has the potential to be a safer and effective method of DNA delivery. This project will focus on optimizing the delivery of msDNA vectors to the brains of mouse models and will provide the necessary foundation to move forward with developing msDNA vectors for targeted therapies to treat CNS disorders in pre-clinical and clinical settings.

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Faculty Supervisor:

Jagdeep Walia

Student:

Partner:

Mediphage Bioceuticals Inc

Discipline:

Life Sciences

Sector:

Pharmaceuticals; Biotechnology; Health and Related Sciences & Technology

University:

Queen's University

Program:

Accelerate

Quantum Deep Neural Nets for Spatial-Temporal Problems

Atmospheric behaviour will change substantially with Climate Change and is one of our generation’s most pressing challenges. The world requires accurate estimates of future the impacts from droughts, floods, heat waves, increase hazards, from freezing rain to hurricane to plan, prepare and mitigate. Combatting climate change requires reducing our emissions in a strategic way. Current computers can only approximate these coming changes. Employing quantum computing and machine learning algorithms, we’re developing open-sourced spatiotemporal models and tools that will improve forecasting accuracy of coming events from days to centuries. The developed models are expected to benefit Lakes Environmental in decreasing computational cost and expanding its weather forecasting market share in Canada and internationally.

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Faculty Supervisor:

Bahram Gharabaghi

Student:

Partner:

Lakes Environmental Software

Discipline:

Earth science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Guelph

Program:

Accelerate

Designing MVP for Atare Foods

This summer student position will help define Atare Food’s technology needs for future mobile application. Intern will work on several tasks that would ultimately define minimum viable product for the organization.

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Faculty Supervisor:

Kin-Choong Yow

Student:

Partner:

Atare Foods

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing

University:

University of Regina

Program:

Business Strategy Internship

Béton bitumineux

Le projet de recherche a pour but de valoriser les sous-produits et résidus miniers de l’industrie de l’aluminium. Pour rendre possible cette valorisation, le projet consiste à évaluer des options d’utilisation des résidus de bauxite et sous-produits, comme ingrédients dans les recettes d’enrobés bitumineux (enrobés de surface, enrobés de liaison et grave-bitume). L’objectif principal est le développement de produits manufacturés et/ou matières premières alternatives qui implique le développement de procédés pour le traitement des résidus. Afin de pouvoir commercialiser ces produits dans la vie de tous les jours, les résidus de bauxite et sous-produits seront utiliser comme granulats dans les enrobés bitumineux ; cela permettra de réduire l’empreinte carbone ainsi que les coûts de production des infrastructures routières.

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Faculty Supervisor:

Guy Simard;Ahmed Rahem

Student:

Partner:

Centre de recherche et de développement d’Arvida

Discipline:

Engineering

Sector:

Technology; Sustainability & the Environment; Mining

University:

Université du Québec à Chicoutimi

Program:

Accelerate

Standardized Ai-Based Corporate Sustainability Reporting

Corporate sustainability reporting is becoming mainstream. An increasing number of investors considers and integrates environmental, social and governance (ESG) criteria in their investment analyses. However, corporate sustainability data is still costly, not standardized, and sometimes even missing, Hence, the project will analyze how AI can be used for standardized corporate sustainability accounting and reporting. Based on Natural Language Processing (NLP) and machine learning tools will be created that help companies to report their sustainability performance in standardized forms compatible to standards, such as TCFD and SASB. The analyses of the results of these tools will help ESGai Technologies Inc. to validate the reports created by the AI-based tools.

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Faculty Supervisor:

Olaf Weber

Student:

Partner:

ESGai Technologies Inc.

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Enhanced recommendation systems using machine learning

Artificial Intelligence (AI) and Machine Learning (ML) will play key roles in the RWA platform. A significant area to which these technologies will be applied is the recommendation algorithm connecting users to resources that are most relevant to their 3 personal wellness journey. The app features a collection of both community resources and in-app resources that have been developed by Refresh. Each of them meets different mental health needs, and not everyone will respond the same way to each resource. Therefore, Refresh is seeking a ML-based solution that will take in various user inputs–such as demographics, journal entry sentiments, and usage patterns–and output recommendations of resources that are highly suited to the user’s needs at that particular time. In this project, four interns will work together to develop and implement this model, beginning with just two features: journal entries and usage patterns. As this will represent the first ML component of the RWA platform, the implementation must be done in such a way so as to support additional ML applications in the future.

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Faculty Supervisor:

Orland Hoeber;Nuelle Novik

Student:

Partner:

Refresh Enterprises Inc.

Discipline:

Computer science

Sector:

Artificial Intelligence; Health and Related Sciences & Technology; New and Digital Media

University:

University of Regina

Program:

Business Strategy Internship

Designing and Implementing Accessible Software for the Canadian Media and Entertainment Space with the Cansbridge Fellowship

This project encompasses the research, design, and implementation of innovative improvements in a 3D animation software for a Canadian-based media and entertainment company. The main objective is to attract and better serve the business’ underrepresented customer segment of artists in the Asian market. This aligns with the Cansbridge Fellowship’s primary mission to support Fellows in creating disruptive impact and advocating for the causes they pursue. Through recommending product solutions for long-term business strategy, this project bridges the gap between the company and the needs of its Asian user base, contributing to Cansbridge’s ongoing Canada-Asia engagement initiatives. Lastly, the project will bring insights and data on Asian markets to the Cansbridge database, which will be made available to the Canadian business community and other stakeholders in the 3D industry who can leverage this information to deliver value to a more diverse range of users.

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Faculty Supervisor:

Norah McRae

Student:

Partner:

Cansbridge Fellowship

Discipline:

Business

Sector:

Technology; Entertainment and Media; New and Digital Media

University:

University of Waterloo

Program:

Business Strategy Internship

Artificial intelligence for automated identification of cannabaceae family plant diseases and gender on low-resource devices

Automated and early identification of plant diseases from their leaves is an important task in agriculture and can have positive impacts on crop yield and quality. Crop pathogens and pests reduce the yield and quality of agricultural production. They cause substantial economic losses and have a direct impact on food security and nutrition worldwide. Due to the wide variety of crops and diseases, even a farmer or pathologist can often fail to identify plant diseases by visualizing the affected leaves. However, visual observation remains the primary approach to disease identification. With the advances in artificial intelligence (AI) and mobile technologies in recent years, it is becoming possible to develop an embedded solution using machine learning that is accessible to farmers on their cell phones. In this project, we propose to develop and optimize deep learning models to detect diseases and gender for plants
in the cannabaceae family.

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Faculty Supervisor:

Moulay Akhloufi

Student:

Partner:

GrowDoc App Inc

Discipline:

Computer science

Sector:

Agriculture

University:

Université de Moncton

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.