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

User-Friendly Design Charts for Optimizing the Evaluation and Repair ofConcrete Beams using Fiber Reinforced Polymer

There is an urging need to enhance the market competitiveness of the fiber reinforced polymer (FRP) material as an alternative to conventional steel and concrete materials in building retrofit projects in Canada due to the reduced life-cycle cost of the former. Optimizing the design of FRP reinforcement is a key element toward increasing the market share of FRP products. The objective of this project is to employ statistical techniques to optimize the number and layout of FRP layers required to strength deficient concrete beams. The optimization will be conducted to achieve a minimum safety level deemed acceptable by the North American codes and standards. User-friendly design chats will be produced covering a wide spectrum of beam retrofit applications.

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Faculty Supervisor:

Fadi Oudah;Yi Liu

Student:

Connor Petrie

Partner:

NOEL Consultants

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Identification of plant immunity activators that protect cucumbers from bacterial and viral pathogens for commercial use in the agriculture sector

The Suncor/McMaster partnership is generating a pipeline of novel, green, agricultural chemicals to be applied as crop sprays. The proposed collaboration will expand the application of the sprays to various crop species in both greenhouse and field settings and contribute to the understanding of the mode of action of the active ingredients.

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Faculty Supervisor:

Robin K Cameron

Student:

Fathy Elgebaly

Partner:

Suncor Energy Inc

Discipline:

Biology

Sector:

University:

McMaster University

Program:

Accelerate

Development of AI-enabled Tools for Advanced Clinical PET/CT Imaging of Cancer Patients

Over 200,000 new cancer cases are diagnosed in Canada each year. With imaging using an appropriate modality, many types of cancer that manifest as solid tumors can be detected, treated or managed effectively. Positron emission tomography (PET) combined with computed tomography (CT) is the primary imaging modality in a range of cancer types. Scientific studies have determined that measuring the size, shape, and texture of tumors from PET/CT images can help identify patients at high risk of early cancer recurrence, or for whom the standard treatment may fail. Nevertheless, the process of image reading in the clinic remains largely qualitative, since manual tumor delineation by radiologists can significantly reduce patient throughput and increase scan wait times. The goal of this project is to design artificial intelligence (AI) tools to assist radiologists and scientists in automatic detection and delineation of tumors in PET/CT images. In collaboration with Microsoft, we will deploy such tools in the cloud, and make them available to practicing physicians and cancer researchers at BC Cancer. The expected benefits of AI-enabled PET/CT image analysis include faster diagnosis, more personalized treatment plans, improved treatment outcomes, and reduction of healthcare costs in Canada.

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Faculty Supervisor:

Arman Rahmim

Student:

Ivan Klyuzhin

Partner:

Microsoft Canada

Discipline:

Other

Sector:

University:

University of British Columbia

Program:

Accelerate

Development of a biocompatible coating for an implantable magnetic marker

Non-palpable breast cancers, needing localization before removal, make approximately 60% of the diagnosed breast cancers. The gold standard for localizing includes implanting protruding wires or radioactive seeds in the lesion. The wires are not accurate, cause pain and discomfort to the patients, while the radioactive seeds warrant strict administrative and safety requirements. MOLLI Surgical Inc. offers a wireless and non-radioactive alternative: Magnetic Occult Lesion Localization Instrument (MOLLI). The instrument has a magnetic marker (placed in the lesion) and a probe (detecting the marker during surgery). The device provides comfort and convenience to the patients and confidence to the surgeons. Inherent toxicity of the magnets, needs them to be coated. MOLLI Surgical Inc. is currently using a costly proprietary coating, but a cost-effective coating is warranted to make the device affordable and acceptable for service healthcare systems. The present study aims to develop a low-cost coating for magnetic markers.

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Faculty Supervisor:

Mark Towler

Student:

Malvika Nagrath

Partner:

MOLLI Surgical Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

Estimation Methods for Geospatial Data Management

This project will develop and test a new method of integrating geospatial measurement data in order to support a Measurement-Based Data Management System. This method and the data management system that can be built from it will have the ability to improve the operational efficiency of Land Surveying firms across Canada. The partner organization expects they will be able to develop a business-to-business data management software product based on the methodology and prototypes developed in this project. The Intern will have the opportunity to pursue further education, develop new skills, and gain hands on experience managing a research project and conducting valuable research.

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Faculty Supervisor:

Prosenjit Bose

Student:

Mike Bremner

Partner:

Dim Ideas Un Ltd

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Carleton University

Program:

Accelerate

Development of Energy Flow Emulators for Greenhouse and Industrial Facilities

360 Energy is a Canadian company specializing in energy management, providing consultation services for the, commercial, greenhouses, and industrial sectors. Their current workflow utilizes a proprietary tool that that is labour intensive, which this research will seek to automate. The proposed approach is to create a building model that will output an energy breakdown of the building. The interns will undergo research to quantify the key variables for their building, exploring various data capture techniques utilizing sensors, and algorithms for statistical analysis. This will have the expected outcome of improving predictions while decreasing labour required, thus increasing the efficiency of service delivery for 360 Energy.

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Faculty Supervisor:

Jennifer McArthur

Student:

Gary Chang;Michael Stock

Partner:

360 Energy Inc.

Discipline:

Architecture and design

Sector:

Information and cultural industries

University:

Ryerson University

Program:

Accelerate

Accelerated Time-Stepping for Computational Aerodynamics

The design of next-generation cleaner and quieter aircraft will rely on accurate simulations of turbulent flows. These simulations, referred to as Computational Fluid Dynamics (CFD), are critical in the design of both the external shape of an aircraft, as well as other components such as jet engines and propellers. The industry partner, ANSYS, develops one of the most widely-used CFD solvers – Fluent. The objective of this project will be to develop new time-stepping methods for Fluent specifically for unsteady flow solutions. These time-stepping methods will allow unsteady simulations to be completed faster, with reduced computational cost. Ultimately, this will improve the performance of Fluent and allow it to obtain accurate simulations more quickly for aerospace applications, leading to improved aircraft designs.

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Faculty Supervisor:

Brian Vermeire

Student:

Siavash Hedayati Nasab

Partner:

ANSYS Canada Ltd

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Development of a Methane Flux Sensor

This project supports development of a laser-based sensor capable of accurately measuring methane releases from oil and gas wells, an important source of greenhouse gas emissions. This sensor will lead to a more accurate understanding of greenhouse gas emissions and enable mitigation actions in the upstream oil and gas industry. This is a critical step in developing effective climate change policy which affects all Canadians. By supporting this project, INO wants to ensure the technological and commercial viability of this important new sensor. Success in these objectives will give Canadian industries rapid access to a state-of-the-art tool enabling them to quantify and reduce methane emissions, which is critical to helping Canada meet its stated commitments to reducing oil and gas sector methane emissions by 40–45% by 2025.

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Faculty Supervisor:

Matthew Johnson

Student:

Simon Festa-Bianchet

Partner:

National Optics Institute

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

UV Mapping Assistance through Deep Learning

The goal is to create a conversation loop between 3D designers and artificial intelligence programs. This will help the AI provide suggestions to the designer, while the designer provides the AI with feedback. This can help make it easier for designing complicated objects as well as complicated textures that belong to the surface of 3D objects. Through this interaction, the hope that AI can extend the utility of design software.

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Faculty Supervisor:

Mark Coates

Student:

Fatemeh Teimury

Partner:

Autodesk Canada Co

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

CO-Away: A Rapid Response Digital Tool to Tackle COVID-19

When our society has faced existential threats in the past, we have banded together to use the technology at hand to overcome them. The COVID-19 outbreak is one such threat that requires the same level of societal effort today. However, in the 21st century, we can combine social innovation, citizen science, and digital epidemiology to harness the power of the ubiquitous digital tools that almost all members of our society have in hand. We must bring together people and provide them with the ethical surveillance tools they need to help them overcome their fear, be better informed, and help our health and financial systems monitor the situation. CO-Away would be one such digital epidemiological app that will leverage the approach of SMART Platform in integrating ethical surveillance, integrated knowledge translation, and policy and behaviour interventions. SMART Platform is being implemented through the Digital Epidemiology and Population Health Laboratory (DEPtH Lab) at JSGS.

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Faculty Supervisor:

Tarun Katapally

Student:

Eric Kwabia;Prasanna Kannan;Luan Manh Chu

Partner:

Lung Association of Saskatchewan

Discipline:

Medicine

Sector:

Other services (except public administration)

University:

University of Regina

Program:

Accelerate

A robust, device agnostic client platform for EMR integration: A proposed architectural model and UI/UX design for a mobile health client portal

Closing the Gap Healthcare has been delivering high-quality health care in communities since 1990. Closing the Gap (CTG) offers a range of services for clients of all ages and are a leader in complex care cases. The Centre for Mobile Innovation (CMI) at Sheridan College has collaborated with CTG and is in the process of developing a responsive client portal that offers a mobile-friendly view for patients to see their upcoming appointments and details about their care program and care providers. Currently, CTG’s 5,000 patients need to use the phone to find this information which is inconvenient and consumes substantial resources both from CTG and the clients. The proposed novel Mobile Client Portal will address the gap in health care services that clients are current seeking.

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Faculty Supervisor:

Ed Sykes;Syed Tanbeer

Student:

George Kopti

Partner:

Closing the Gap Healthcare

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Sheridan College

Program:

Accelerate

Developing a tool to identify epitopes for drug therapy using semi-supervised and supervised machine learning

The COVID-19 pandemic has been caused by a novel coronavirus, SARS-CoV-2. Viral infections cause the human immune system to respond in two ways: a fast, non-specific response, and a slow response that produces antibodies that will target the infecting virus. Each antibody will recognize a small segment of the virus, called an epitope. If the best segments to target can be identified, it is possible to manufacture antibodies to test for the infection and help the immune system to boost its response when fighting the infection. Identifying these epitopes manually is a labor-intensive process, that is time consuming and expensive. In the current project, we will use machine learning techniques to gather data of known epitopes and predict new epitopes to new infections. We expect this work will revolutionize the discovery of antibodies when fighting new infections in an epidemic or pandemic context.

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Faculty Supervisor:

Eldad Haber

Student:

Philipp Witte

Partner:

Genomica

Discipline:

Geography / Geology / Earth science

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

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