Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

SOTI SNAP Blockly – Building Apps Without Programming

SOTI SNAP is an application development platform that allows users to create applications with little or no programming knowledge. By utilizing a block-based approach, users can drag and drop blocks and pre-made widgets and connect together to create applications in minutes. Apps made using SOTI SNAP can run on both Android- and iOS-based devices. The aim of this project would be to improve upon the existing SOTI SNAP platform to make it easier for users to tinker with and learn. User studies will be conducted to determine any additional widgets and functionality that can be added to SOTI SNAP to further improve the platform.

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Faculty Supervisor:

Fanny Chevalier

Student:

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Spoken Language Identification for Children

While taking foreign language tests, people may respond in languages other than the expected one. Typical scoring systems are trained only on the expected language, so unexpected language responses can have unusual results in speech recognition and scoring. Pearson would like to develop a more robust system for the automated speech recognition machine to know up front if the response contains non-target language content. Common language labels are English, Spanish, Chinese, Japanese, etc. Audio files are typically from 5 to 90 seconds long. There are popular softwares which are built to address these problems but their results need to be tested with the particular kinds of inputs that is obtained as test responses. These may have strong accent, be children’s speech, and various other complicating factors. Improving these systems would greatly benefit Pearson’s competitiveness in the market and would also contribute towards expanding the boundaries of knowledge in speech processing.

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Faculty Supervisor:

Gerald Penn

Student:

Partner:

Pearson Inc

Discipline:

Computer science

Sector:

Technology; Education

University:

University of Toronto

Program:

Accelerate

Improving Q-RT-PCR screening for COVID-19 by tracking viral variants

This project will extend on our labs initial findings that current q-RT-PCR based screening strategies for COVID-19 patients can fall within variant regions of the SARS-CoV2 viral sequence and may potentially lead to false negative results. This project, in collaboration with BioXplor will lead to the development of online bioinformatics tool that will allow tracking of viral mutations as they evolve as well as optimal primer design for testing assays that avoid hotspot mutations leading to more robust and accurate patients screening. BioXplor will then assist in the dissemination of these user-friendly bioinformatics tools to the greater COVID-19 research community in both Industry and Academia that are manufacturing COVID-19 test kits.

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Faculty Supervisor:

Neil Watkins;Jody Haigh

Student:

Partner:

BioXplor Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Learning to Rank through User Interest Mining: Towards Search Personalization

In online shopping, search results often have inherent ambiguity. Two customers using the same term as search query might have completely different expectations of the displayed results. For example, when the users type in the query “headphone”, some of them might expect over-ear headphone with passive noise isolation, while others might expect in-ear headphone with better portability. This project aims to extract users’ interests or preferences and understand what they want. After discovering users’ interests, it is possible to provide personalized search results for everyone by using machine learning techniques.
The company will be able to attract and keep more customers by providing innovative and personalized online shopping experience.

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Faculty Supervisor:

Roger Grosse

Student:

Partner:

Loblaws Digital

Discipline:

Computer science

Sector:

Retail trade

University:

University of Toronto

Program:

Accelerate

Photodynamic Therapy for Annihilating COVID-19 Virus

There is a paramount need to treat symptoms, find cures, and reduce/contain the virus’s continuous spread due to the global pandemic caused by the novel Coronavirus (COVID-19). The most life-threatening symptoms of COVID-19 result in severe respiratory failure due to pneumonia complications. While antiviral treatments and vaccines are under development globally, patients in critical condition cannot wait. It usually takes one to two years to develop vaccines, and cases continue to present with severe complications requiring immediate, life-saving intervention in the meantime. Thus, this research proposes to develop a photodynamic therapeutic device to treat the severe respiratory failure associated with COVID-19, to supply hospitals with a device to save lives while awaiting the medical community’s vaccine.

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Faculty Supervisor:

Majid Pahlevani

Student:

Partner:

Genoptic LED Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Queen's University

Program:

Accelerate

Applications of Quantum Monte Carlo Sampling

In today’s quantum computing environment, access to all major hardware providers is entirely cloud-based. As a result, large enterprises and other privacy-sensitive users are limited in their ability to experiment with quantum computers. Many have simply chosen to forego experimentation with quantum computers altogether. A careful application of recent research is vital to address this need via the development, testing, and deployment of security solutions designed for today’s quantum computers. This project is aimed at researching industry-specific quantum algorithms and recent academic breakthroughs for the purpose of developing task-specific, user friendly security tools that can be deployed in a real-world setting. A special focus will be given to finance applications. The project may result in scientific publications.

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Faculty Supervisor:

Henry Yuen

Student:

Partner:

AgnostiQ Labs

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

L’impact du “fly-in fly-out” (navettage) dans la vie des hommes

Des recherches dans le secteur minier montrent que plusieurs hommes rapportent vivre une fatigue chronique provenant des longues heures de transport, de travail, ainsi que de l’instabilité liée aux différents endroits pour dormir et aux conditions de sommeil. Plusieurs travailleurs indiquent se sentir isolés socialement. Ce projet veut étudier les impacts du modèle navettage dans la vie des hommes, plus précisément 1) décrire les conséquences du navettage dans les différentes sphères de la vie des hommes (santé – bien-être – famille); 2) faire un portrait sur la qualité des services d’aide offerts aux hommes qui travaillent en faisant le navettage (accessibilité des services, adéquation des interventions offertes, etc.); 3) décrire les connaissances manquantes et les solutions à mettre en place en termes de réduction des conséquences négatives du navettage sur la santé et la vie familiale des hommes. La méthodologie utilisée sera de type qualitative et la technique de l’entrevue semi-structurée sera privilégiée pour collecter les données dans les cinq municipalités régionales du comté et de la région.

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Faculty Supervisor:

Oscar Labra;François Déry

Student:

Partner:

Groupe Image

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Accelerate

Journalism Product Innovation and Audience Engagement at The Conversation Canada

The Conversation Canada (TCC) is an independent news startup that specializes in short-form, evidence-based explanatory journalism written by experts in universities and curated by professional journalists. TCC is supported by a consortium of universities, agencies, and governments. News articles are freely available online and may be republished at no cost under a Creative Commons license. In 2018 The Conversation Canada published nearly 1,000 stories, and has around 1.3 million monthly views, two-thirds from outside Canada. Research will be undertaken to help The Conversation Canada to further develop impactful explanatory journalism by experimenting with new journalism products in three new formats: podcasting, newsletter, and long-form journalism. As well, analytics will be used to assess The Conversation Canada’s current audience. The focus will be on articles in The Conversation Canada’s section on Culture, Society, and Critical Race Issues.

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Faculty Supervisor:

Charles Davis

Student:

Partner:

The Conversation Canada

Discipline:

Sociology

Sector:

Information and cultural industries

University:

Toronto Metropolitan University

Program:

Accelerate

Technologies for Improved Sustainability of Long-Life Flexible Pavements

A sustainable pavement is one that is safe, smooth, efficient, economic, and environment friendly,
meeting the needs of present-day users without comprising those of future generations. Sustainable
flexible (asphalt) pavements, in particular, are those that minimize environmental impacts through the
reduction of fuel and energy-based materials (asphalt cement, for example) consumption, more
effective use of natural resources, and reduction of greenhouse gas emissions while meeting all
performance conditions and standards. The proposed research focuses on the development of
different applied technologies in design, construction and maintenance for improved sustainability of
long-life flexible (asphalt) pavements to: minimize the use of natural resources through recycling;
reduce pavement temperatures in hot seasons; enhance pavement performances; reduce user fuel
consumption; and reduce greenhouse gas emissions. The developed technologies for light-coloured
grey asphalt pavements and high performance granular layers using reclaimed materials will foster
improved designs for sustainable long-life flexible pavements.

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Faculty Supervisor:

Peijun Guo

Student:

Partner:

Shiloh Canconstruct Ltd

Discipline:

Engineering

Sector:

Clean Technology; Environmental Science and Technology; Clean Technology; Environmental Science and Technology

University:

McMaster University

Program:

Accelerate

Thales – Prédiction logistique en pharmacie

Les pharmacies au détail s’appuient principalement sur leurs propres données empiriques pour planifier et prévoir leurs stocks. Ce type de données a ses propres caractéristiques, qui peuvent être saisonnières et être affectées par des événements spéciaux et imprévus tels que les maladies pandémiques. Toutefois, à mesure que la quantité de données s’accumule, il n’est pas évident de savoir comment prévoir efficacement leurs stocks, découvrir les habitudes d’achat de certains médicaments à certaines périodes de l’année et prévenir davantage les pénuries. L’apprentissage automatique et l’analyse prédictive permettent d’analyser les données, de découvrir les habitudes d’achat des clients, les habitudes d’achat de médicaments à la demande, les associations et les informations potentiellement utiles cachées dans les données, ce qui est pertinent pour ce projet.
Le but de ce stage est d’étudier les sujets de recherche suivants. Comment pouvons-nous mieux modéliser les données logistiques des pharmacies ? Existe-t-il des caractéristiques indirectes autres que l’historique d’achat des clients que nous devons saisir à des fins prédictives ? Quel type d’algorithme est approprié pour prédire les modèles de demande de médicaments et les modèles de pénurie des fournisseurs ?

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Faculty Supervisor:

Christian Gagné;Jonathan Gaudreault

Student:

Partner:

Thales Canada Inc

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology

University:

Université Laval

Program:

Accelerate

Monitoring the sustainability of agricultural system for Ontario’s Greenbelt

This project aims at developing information and knowledge that will promote public and policy support for the long-term sustainability of the agricultural system surrounding the greenbelt. Based on a preliminary research led by the Friends of Greenbelt Foundation, this research will develop a monitoring framework for the viability and protection of the agricultural system in the greenbelt and assess the trends of agricultural viability and protection in Greenbelt during the past 15 years. It also looks into the urbanization trend and farmland loss approaching the greenbelt and aims at investigating its impact on the sustainability of the greenbelt. This project will be of interest to the policy makers, municipal leader and communities who are interested in the sustainable development of the greenbelt and the Greater Golden Horseshoe. This research project will directly benefit the greenbelt foundation’s future work by creating a framework which could guide through the further monitoring projects, and provide an in-depth review on the status of the greenbelt during the past 15 years.

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Faculty Supervisor:

Wayne Caldwell

Student:

Partner:

Friends of the Greenbelt Foundation

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

University of Guelph

Program:

Accelerate

Yield optimization of an agrifood production process using AI tools and Industry 4.0 technologies

Food manufacturers experience significant waste when transforming raw materials into refined finished products. In the food processing industries, a single line can have 50% or more of raw materials loss while simultaneously producing varying degrees of quality simply because processing equipment is not optimally configured to the characteristics of the suppliers’ raw materials. Worximity proposes a project to use artificial intelligence, combined with industrial sensors (IIoT) and computer vision to optimize food production yield, improve quality, safety, and reduce waste in food manufacturing.

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Faculty Supervisor:

Maha Ben Ali;Robert Pellerin;Christophe Danjou

Student:

Partner:

Worximity Technology Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

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.