Innovative Projects 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

Real-time COVID-19 detection in wastewater from long-term care homes

The goal of the partnership between Mantech and Waterloo is to develop a technology to manufacture smart hybrid water sensors for current and future disease prediction and detection. This technology will have an invaluable impact on human health research efforts to contain the COVID-19 and possible future pandemic spread, and put Ontario and Canada far ahead of similar efforts worldwide.

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Faculty Supervisor:

Mustafa Yavuz

Student:

Samed Kocer;Gennady Kotov

Partner:

Mantech Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Waterloo

Program:

Accelerate

Enhancement of methane oxidation in bio-based landfill covers by increasing aeration

Organic waste disposal in landfills can produce a massive amount of methane, which is a potent greenhouse gas contributing to global warming. Once the landfill is filled, it is usually capped by a clay cover or geomembrane that can trap methane but not reduce it. Changing a part of the conventional cover by compost to make a biocover provides appropriate conditions for methane consumption by methane-oxidizing bacteria. In the landfill environment, oxygen can diffuse into the biocover from the atmosphere and be used by bacteria; however, it cannot penetrate the compost deeply. Therefore, oxygen supply to deeper layers can increase the efficiency of the biocover in methane removal. This project will enhance the aeration of biocovers by (1) increasing the porosity of the compost and (2) air injection from the bottom of the biocover. This will be done through laboratory experiments with columns filled by composts collected from a biocover.

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Faculty Supervisor:

Qiuyan Yuan

Student:

Parvin Berenjkar

Partner:

KGS Group

Discipline:

Engineering - civil

Sector:

University:

University of Manitoba

Program:

Accelerate

Building a Mobile Platform to Identify Factors that Impact Student Success and Mental Health Related to Their Living Arrangements

This research seeks to discover how matching roommates can improve the living experience, academic progress, retention and mental health of students. It would be carried out using automated questionnaires, interviews, focus groups, surveys to extract user information. The research would help build a platform that can successfully match students based on preferences to help them make the right decision in selecting a roommate and achieve the above set goals.

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Faculty Supervisor:

Steven Smith

Student:

Laura Russell;Peter Fletcher

Partner:

Cohability

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

Saint Mary's University

Program:

Countermeasures for Hardening Embedded Security

The impact of attacks on Internet of Things (IoT) embedded devices range from threatening lives, such as attacks on wearable/implantable health devices, to threatening infrastructures in financial, transportation, and other sectors. In the IoT realm, hardware is distributed and embedded in our environment and must be hardened against malicious intentional and unintentional attack. Despite advances in hardening software systems using security fixes, attacks on embedded hardware remain feasible with few known defenses. Although generally attackers cannot launch their own malicious software on these embedded devices, low cost non-invasive attacks such as electromagnetic fault injection can have a detrimental impact on and often break the embedded security. This research involves hardening the embedded processor using new software and hardware countermeasures to thwart electromagnetic fault injection. These countermeasures will be verified on real embedded hardware and licensed for use to provide increased hardening and security for many embedded processor systems.

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Faculty Supervisor:

Catherine H Gebotys

Student:

Karim Amin;Mahmoud Khalafalla

Partner:

Thinktum

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

APEX Total Compensation Study

The APEX (Association of Professional Executives of the Public Sector of Canada) total compensation study seeks to provide a current assessment of executive compensation philosophies and governance within the public service sector in Canada. Issues related to limited differences in compensation between senior level managers and less experienced managers will be explored including the various compensation policies in place within federal, provincial, and municipal public sector organizations. A benchmarking of current practices will be undertaken using existing information contained within APEX’s database and additional information gathered through a survey and interviews. An analysis of the data gathered will result in a summary report and related recommendations.

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Faculty Supervisor:

Philip Walsh

Student:

Ester Barinova

Partner:

The Association of Professional Executives of the Public Service of Canada

Discipline:

Other

Sector:

Other

University:

Ryerson University

Program:

Accelerate

Development of antiviral surfaces to mitigate the transmission of COVID-19

In March 2020, the new human coronavirus disease COVID-19 was declared a pandemic. As of May 21, 2020, the World Health Organization has reported over 4.8 million confirmed cases, including over 323,000 deaths worldwide. Only in Canada, the number of confirmed infections and deaths have reached over 80,000 and 6,000, respectively. Apart from the elevated rates of death and illness, this pandemic has caused major social and economic disruption throughout the world. This proposal is focused on development of thermally sprayed intrinsic antiviral coatings in order to mitigate the indirect transmission of SARS-CoV-2 virus. These coatings can be applied on touch surfaces such as the handrails, doorknobs, elevator buttons, ATM machines, and biomedical appliances in various public and service departments such as hospitals, schools, and the transport system. Another important targeted application is for air purification in the ventilation systems used in buildings, airplanes and other means of transport. Using thermal spray, a technology known for its versatility, scalability and cost effectiveness, we intend to develop antiviral coatings with materials such as TiO2, Cu2O, and TiO2/Cu2O. These materials have shown promise for their virus killing and anti-pathogen properties when exposed to UV light,TOBECONT’

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Faculty Supervisor:

Christian Moreau

Student:

Hediyeh Khatibnezhad;Elnaz Ale ebrahim

Partner:

HATCH Ltd.

Discipline:

Engineering - mechanical

Sector:

University:

Concordia University

Program:

Accelerate

Improving the magnetic properties of electrical steels – Year two

This project is intended to help the industrial partner, Stelco, to develop electrical steels with improved magnetic properties through controlled thermomechanical processing. Electrical steels are widely used in the manufacturing of stators and rotors of electric motors used in general rotating machines and electric vehicles. Improving the magnetic properties of electrical steels would result in more efficient traction motors, and consequently extending the driving range of electric vehicles. This is of particular importance for Canadians as the driving range of an electric vehicle is considerably reduced in cold weather. The research will focus on investigating the effect of the steel processing parameters on the final magnetic properties of electrical steels, both in pilot scale and in industrial production. Experiments will be carried out at CanmetMATERIALS, Natural Resources of Canada, using its pilot-scale rolling mill and other facilities. The results from the pilot-scale experiments will then be used to guide the production of electrical steels of the industrial partner, Stelco Holdings Inc. The research will involve both theoretical and experimental studies on the relationships among processing parameters, microstructure (texture), and final magnetic properties of the electrical steels.

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Faculty Supervisor:

Afsaneh Edrisy

Student:

Mehdi Mehdi

Partner:

Stelco

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Windsor

Program:

Elevate

Optimiz AIOps data normalization and visualization

Approximately 70% of data collected by ITOps is not actionable, either due to lack of timeliness or context, and real-time normalized data stored in a data lake is needed to produce actionable data. Also, AIOps tools are often poorly configured and lead to alert fatigue. The benefit to the partner organization is that they will be able to capture actionable AIOps data that can be normalized for Artificial Intelligence (AI) and Machine Learning (ML) analysis. Based on the analysis done by AI and ML interventions can be automatically applied to an enterprise IT system.

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Faculty Supervisor:

Reynard Dela Torre;Ralph Dueck

Student:

Richard Schentag;Braden Still-Routley

Partner:

Optimiz Inc.

Discipline:

Other

Sector:

Information and cultural industries

University:

Red River College

Program:

Accelerate

Exploring the Impacts of a Community-Based Post-Secondary Education Award

Canadian community foundations significantly support post-secondary institutions and students in their provision of merit and needs based awards and bursaries. Yet little is known about the impacts of these investments for students. The Edmonton Community Foundation has partnered with UAlberta (Community Service-Learning) and the Edmonton Social Planning Council (ESPC) to explore the impacts of a specific ECF Awards program for low-income and civically engaged students. Beginning with the 2018 group of award winners, the study will track these students as they enter higher education, take their courses and engage in other socially minded and career oriented activities, and transition into various forms of employment. Researchers will connect with the participants using interviews, surveys and focus groups, at four points of time across 2019-2025: during their studies, upon graduation or withdrawal, at six months after graduation and at two years after graduation. The study will compare the characteristics of those students who won awards to those who did not, and also visually map the journeys of participant students from home to school to post-secondary institution to employment sites.

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Faculty Supervisor:

David Peacock

Student:

Oscar Javier Baron Ruiz

Partner:

Discipline:

Geography / Geology / Earth science

Sector:

Other services (except public administration)

University:

University of Alberta

Program:

Accelerate

Traffic Estimation and Stable Resource Allocation Using Distributed Machine Learning

The proposed research will develop novel distributed machine learning techniques for stable resource allocation and improving traffic estimation in networks. It is a well-known fact that networks are becoming complex and user demand is growing in many directions including the traditional demand for capacity and less delay, as well as improvements in Quality of Experience (QoE). Backhauling the multiplexed demand over the core networks calls for accurate traffic estimation. On the other hand, control of the resource allocation, based on such predictions, needs stable and robust solutions. This is a highly challenging problem since when multiple agents use the information collected from the field, they may converge to conflicting decisions which risks the stability of the network. In certain cases, the agents themselves might not even converge, let alone the whole network. Therefore, techniques that consider control, stability and assurance must be developed. This project will develop fundamental solutions for next generation ultra-agile networks.

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Faculty Supervisor:

Melike Erol-Kantarci

Student:

Shahram Mollahasani;Mohammad Sadeghi

Partner:

Nokia Canada Inc.

Discipline:

Engineering - computer / electrical

Sector:

University:

University of Ottawa

Program:

Accelerate

Applicability and Utility of the PHEMI Secure Clinical and Multiomics Platform for Precision Medicine

Advanced prostate cancer (PCa) manifests as metastasis and metastasis is the leading cause of death for PCa patients. The underlying mechanisms remain poorly understood. We hypothesize germline variants may modulate a tumor’s propensity for metastasis. If validated a saliva or blood based test could be developed to predict risk of metastasis. Our objectives are: (1) identify a cohort of high-grade treatment naïve prostate tumors half that metastasized and half that did not following prostatectomy. The cohort of 50 tumors will have a minimum follow-up of 8 years. (2) perform DNA sequencing on the tumor DNA and adjacent normal tissue (germline). (3) identify the proteins expressed in the tumor and adjacent normal tissue. (4) employ computational tools to identify candidate germline and tumour drivers of metastasis. (5) link these to differences in the proteome of the tumor and the tumor microenvironment between non metastatic and metastatic tumors. (6) validate differentially expressed proteins using immunohistochemistry on tumor microarrays and databases. Germline, somatic or proteomic signatures of metastasis will be validated in large independent cohorts. Data security and sharing will be piloted using PHEMI software installed on servers at the VPC.

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Faculty Supervisor:

Colin Collins

Student:

Yen-Yi Lin

Partner:

PHEMI Systems

Discipline:

Other

Sector:

University:

University of British Columbia

Program:

Accelerate

Optimal design of composite structures

A composite material is a macro-level combination of two or more material whose properties can be tuned based on the macro-scale distribution of the material. D.I. Self-Composite Alloys Inc., are working on developing a new generation of materials. Their preliminary findings have shown that it is possible to create metals with improved mechanical properties by just tuning the manufacturing process. They are interested in a design optimization tool for composites. Since traditional design optimization would an iterative time-intensive process, the project will aim to “teach” machine learning algorithm optimal solutions for different designs. Specifically, design optimization will be performed for a sample application over a constraint space, and an artificial neural will be trained on this data. This train network can then predict the optimal design without the need to perform a full optimization.

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Faculty Supervisor:

Krishna Vijayaraghavan

Student:

Wesley Romey

Partner:

DI Self-Composite Alloys Inc.

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

Simon Fraser University

Program:

Accelerate

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