Innovations Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to French? To German? To Korean? To any of the other 7000 languages in the world? Doing so would not only allow Tealbook to reach a wider audience, but also help the world stay interconnected in any language.

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Faculty Supervisor:

Gerald Penn

Student:

Khasir Hean

Partner:

Tealbook inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in integrating the data for sharing, adds additional documentation burden, and disrupts the workflow for clinicians. The solution applies Natural Language Processing and Machine Learning to identify similar order sets and their elements (attributes and responses), reduce the manual work required to compare the order sets, and expedite the decision making process for standardization.

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Faculty Supervisor:

Michael Brudno

Student:

Joseph Roussy

Partner:

Deloitte Consulting

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

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:

Cara Alexander

Partner:

AgnostiQ Labs

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

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:

Zhou Fang

Partner:

Loblaw Company Limited

Discipline:

Computer science

Sector:

Service industry

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:

Carlos Farkas Pool

Partner:

BioXplor Inc

Discipline:

Pharmacy / Pharmacology

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

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:

Aravind Varier

Partner:

Pearson Education Canada

Discipline:

Computer science

Sector:

University:

University of Toronto

Program:

Accelerate

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:

Raymond Zeng

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

University:

University of Toronto

Program:

Accelerate

Design and Development of COVID-19 Automated UV Object Disinfection Cabinet

Highly infectious COVID-19 has had widespread effects on Canadian and global health, security, and economy. While vaccines play a key role in preventing viral diseases, various measures should be taken to slow their spread. Among preventative measures, disinfection systems are of paramount importance to battle COVID-19. The objective of this project is to design and build an automated confined cabinet for object disinfection using ultraviolet germicidal irradiation.This smart cabinet would be able to detect objects, measure their sizes and adjust UV rate accordingly in a short time to make it a good candidate for major online retailers distributing hundreds of thousands of items daily.

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Faculty Supervisor:

Shahpour Alirezaee;Mohammed Jalal Ahamed

Student:

Faraz Talebpour

Partner:

Level One Robotics and Controls Inc

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Windsor

Program:

Accelerate

SOTI SNAP SDK For creating third-party widget

This project dedicates to leverage the use of SOTI snap app to a greater community by providing more flexibility for third-party users and reducing required prior programming knowledge. To do this, we will focus on building a Software Development Kit (SDK) so that third parties can create and publish new widgets allowing SNAP apps to be quickly created that support a wide range of business needs. Human-Computer Interaction and Software architecture principles will be employed to make the SDK more user-friendly. Early stages will be focused on user studies and architecture design and later stage will be focused on the scalable and extendable implementation of the backend part to make it enough fault-tolerant and flexible enough to communicate to third-party resources.

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Faculty Supervisor:

Maryam Mehri Dehnavi

Student:

Xuejie Tang

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

University:

University of Toronto

Program:

Accelerate

The design and implementation of a gamified eHealth movement and mindfulness solution for school-aged children

The online delivery of primary school curriculums may work well for subjects like math and science, but not so well for physical education. Now more than ever, it is crucial that we ensure that children continue to benefit from the countless positive mental and physical health outcomes associated with regular involvement in physical activity. To help keep children moving during this stressful time (i.e., COVID-19), Mitacs is partnering with X Movement to develop an ExerGame Smartphone App that children can use to compete in physical activity and mindfulness challenges against their school friends and family members. We will assess their weekly physical activity habits using FitBits. We are also going to examine if children who use our ExerGame see improvements to their mood and emotional control, resiliency, and life satisfaction. This partnership will help to validate X Movement physical activity and mindfulness programs, while also helping to ignite a child’s love for mindful-movement.

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Faculty Supervisor:

Sidney Kennedy

Student:

Tian Renton

Partner:

X Movement

Discipline:

Other

Sector:

Education

University:

University of Toronto

Program:

Accelerate

To develop an AI algorithm for continuous monitoring of mental health status using publicly available datasets

Poor mental health and stress are an expected outcome of the COVID-19 pandemic. Social distancing is taking another toll on the mental health of individuals. With most of the medical consultations being held online there is an urgent need to enable continuous monitoring of mental health by identifying risk factors for high stress and poor mental health and to provide individuals with information to improve their health and well-being. Wearable and mobile devices are an efficient and effective mean to achieve this goal in a very cost-effective manner. We would like to develop a new AI algorithm that will help assess mental health status of individuals in a real time fashion by using the continuous data feed from wearable devices. The aim of this project is to examine how accurately these measures could identify conditions of stress and poor mental health. We plan to apply novel algorithms on the already available datasets that are available in public domain to identify correlation between the various physiological markers and the poor mental health.

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Faculty Supervisor:

Steven Wang

Student:

Hang Du

Partner:

C2C Healthcare Inc

Discipline:

Statistics / Actuarial sciences

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Youth Employment & Education and the COVID-19 Impact

The proposed project consists of a literature review and jurisdictional scan. We are seeking to understand the past and current literature on youth economic engagement, labour market engagement, post-secondary and training strategies and research, social wellbeing, and specific vulnerabilities for youth when engaging in the labour market. CFY will use this research to shape strategic recommendations to meet today’s challenges and barriers in the COVID pandemic and “new normal” so that Choices for Youth and other partners can act now and be ready to meet the needs of youth in the weeks and months ahead.

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Faculty Supervisor:

Natalie Slawinski

Student:

Matthew Cooper

Partner:

Choices for Youth

Discipline:

Other

Sector:

Other services (except public administration)

University:

Memorial University of Newfoundland

Program:

Accelerate

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