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

Characterization of various insulation materials, coatings, and non-metallic membrane for corrosion under insulation performance

Corrosion under insulation (CUI) is among the major damage mechanisms acting in Oil & Gas processing plants and chemical industries that causes process leaks, and the failures of thermally insulated systems. The hydrocarbon leaks from CUI result in the increased carbon footprint and can even cause catastrophic fires. CUI triggers from inevitable moisture ingress in thermal insulation, and so need to be better understood and managed for cleaner and safer operation of process facilities. The major uncertainty with CUI is from the variety of insulation materials and coatings used in the industry, the majority of which are not fully evaluated and reported for quantified corrosion risks and related implications. This research project aims to test various in market insulation materials, coatings, and non-metallic membrane for CUI performance. Other than understanding the CUI mechanisms, this project will improve the scientific literature and support refinement of industry standards on CUI.

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Faculty Supervisor:

George Jarjoura

Student:

Omar AlChaar

Partner:

Integrity Products & Supplies Inc

Discipline:

Engineering - mechanical

Sector:

Other

University:

Dalhousie University

Program:

Accelerate

Applications of tensor neural networks to financial forecasting in incomplete markets

pre-agreed price. The problem of what an option is worth is usually solved using costly numerical simulation methods.
We will apply Deep Learning methods to solve the Option Pricing Problem. This cutting edge technique has the advantage that, once trained, the model can simulate many scenarios at a low computational cost. Unfortunately, training is costly and can be unstable.
Our original contribution is to use Tensor Networks to improve this Deep Learning model. Tensor Networks are known to give an advantage when training Neural Networks, and allow for more robust training, even when the market data is incomplete.
The partner will benefit from this project by developing their software stack to tackle this commercially valuable problem.

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Faculty Supervisor:

Chi-Guhn Lee

Student:

Raj Gaurangbhai Patel

Partner:

Multiverse Computing

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Understanding the performance of pulse and cereal flours of varying particle sizes at high heating temperatures using Rapid Visco Analyzer 4800

In this project, the intern (Dr. Dong-Jin Lee; Postdoctoral Fellow) will work at the University of Saskatchewan and at the R&D facility of our industry partners ? Pulse Crops (Canada) Association and PerkinElmer Health Sciences Canada Inc. ? to control the milling processes of selected Canadian pulse and cereal crops to prepare “fine”, “medium”, and “coarse” flours and then measure the functional properties of the obtained flours. Most importantly, the pasting and gelling performance of the pulse and cereal flours of varying particle sizes will be evaluated over cooking temperatures of 95-140°C. Our collaborative research will lead to new knowledge and technologies meaningful for creating new flour ingredients from Canadian pulses and cereals for more diverse food applications, especially in high-temperature food processing (e.g., canning, extrusion, and jet-cooking). Furthermore, the new findings will be valuable for the agri-food sector to explore the possibility of including Rapid Visco Analyzer 4800 to support their ingredient innovation efforts.

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Faculty Supervisor:

Yongfeng Ai

Student:

Dong-Jin Lee

Partner:

Pulse Canada

Discipline:

Food science

Sector:

Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Scale-up synthesis and commercialization of poly(3-alkyltellurophenes)

Polytellurophenes are an emerging class of semiconducting polymers showing promises in organic electronics. However, their commercial potentials are still held back by the synthetic scale. In this collaborative efforts with 1-materials, we aim to develop a synthetic strategy to produce polytellurophenes from a laboratory scale to a pilot scale to meet the increasing market demands. The synthesis will be scale up to produce 500 mg and 2.5 g polytellurophenes in one single batch at Stage 1 and Stage 2, respectively. A thorough assessment of safety, efficacy, and economic factors in both stages will be performed. This is an opportunity for the partner to bring this cutting-edge material to the public market. Polytellurophenes have the potentials to become one of the partner’s feature products.

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Faculty Supervisor:

Dwight Seferos

Student:

Shuyang Ye

Partner:

1-Material Inc

Discipline:

Chemistry

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Production of Flow-Through Z-Pinches Using Advanced Methods

This project will develop a low cost prototype fusion reactor to create energy from water. We will find a better way to add the power to run it and to increase the efficiency of operation over previous versions of the machine. The interns will increase Fuse’s knowledge of the workings of the reactor and the devices that help run it and monitor it. Fuse will then be able to build a new and improved reactor that will achieve a long sought after goal of the scientific community of getting as much energy out of a fusion reactor as is put into it. This will attract a large amount of capital for Fuse to continue its research. Fuse, the University of Saskatchewan and Canada will be widely celebrated for this achievement.

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Faculty Supervisor:

Lénaïc Couëdel;Chijin Xiao;Michael Bradley;Andrei Smolyakov

Student:

Jeisson Vanegas;Nishka Sheth;Brad Dempsie

Partner:

Fuse Energy Technologies Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Scalable Chatbot Framework for Multi Layered Chatbots and Memory.

The general objective of this research project is to develop a new natural and empathic chatbot by integrating the transformer and intent-based systems. The goal is to implement a system for expressive 3D interactive characters that can move between the structure of an intent-based system with specific Question and Answer pairs and the more open-ended smart system of the Transformer. Most currently existing chatbot systems are limited in their abilities to engage in open-ended and natural dialogues with human users. As such, this research project will investigate the possibility of expanding the knowledge base of existing chatbots to answer questions outside of the original knowledge base.

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Faculty Supervisor:

Steve DiPaola

Student:

Maryam Ahmadzadeh

Partner:

Reimagine AI Inc

Discipline:

Interactive arts and technology

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

The Geography of Capacity–An Analysis of Individual, Organizational and Community Needs and Resources in Three Communities in Canada – Year two

This research presents a conceptual model of the geography of capacity and explores, through a small-scale study, the experiences of capacity across the nonprofit sector at the individual, organizational and community level in three different locales in Canada. By identifying the varied nonprofit capacity needs in different socio-economic and geographic locations, and by examining how organizations and communities understand these needs and strategize to identify resources, this research contributes to the discourse on the geography of nonprofits, infrastructure organizations and service provision. It challenges the dominant assumption that all agents within the nonprofit sector have equal access to resources, knowledge and ultimately the power needed to achieve outcomes. This study problematizes the capacity needs of the sector and corresponding infrastructure supports provided through the lens of socio-economic and geographic difference. TO BE CONT’D

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Faculty Supervisor:

Susan Phillips

Student:

Megan Elizabeth Conway

Partner:

Capacity Canada

Discipline:

Resources and environmental management

Sector:

Education

University:

Carleton University

Program:

Elevate

Reliability evaluation of strain-based design for pipelines using probabilistic demand/capacity models. – Year two

Ground movement can impose excessive deformation violating pertinent pipeline limit states. Currently, the integrity assessment of pipelines subjected to soil movement is generally performed by analyzing the stresses and/or strains in pipelines using various engineering techniques, including finite element analysis (FEA). However, given the wide variability of the pipe and soil engineering properties, using deterministic approaches alone may be inadequate. The desired approach is a semi-probability-based approach using safety factors or a full-probability-based approach, specified in Annex C and Annex O of CSA Z662:2019, respectively. However, probabilistic demand or capacity models are required but missing in Annex C because of the lack of mature and established models for calculating the strain capacity and the demand due to the site-specific nature of ground movement. The objective of this project is to develop probabilistic strain demand and capacity models for reliability analysis of pipelines subjected to geotechnical loads by leveraging FEA and quantitative reliability methods. The results obtained using these desired approaches will be compared. The deliverables of this project will not only help industries, such as Northern Crescent, to improve the pipeline integrity assessment programs with better efficiency and safety but also be useful to update the design codes (CSA Z662).

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Faculty Supervisor:

Yong Li;Samer Adeeb

Student:

Sylvester Agbo

Partner:

Northern Crescent

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

University of Alberta

Program:

Elevate

Develop an AI-backed geospatial data collection and analysis platform as a marketable software package

The ubiquity of smartphones and their embedded technologies today can provide transportation agencies with affordable travel survey methods which place less burden on respondents and enables collection of continuous, high quality travel data. Such technologies, however, have not yet made the leap from speciality tools of academia to industry, primarily due to the specificity of domain knowledge required to produce useful information and gaps in the literature due to the difficulty of implementation. Most importantly, there is not yet a user-friendly and reliable platform for collecting, analyzing and inferring travel information from smartphone-based surveys. This project seeks to develop an AI-backed geospatial collection and analysis platform (named the HexMap platform hereafter) to allow transportation authorities to independently design travel surveys with custom questions and prompts, distribute and publish these surveys through a mobile application, and monitor the data collection process. The HexMap platform will then use artificial intelligence methods, with a focus on deep learning algorithms, to infer mobility information from collected GPS trajectory data.

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Faculty Supervisor:

Zachary Patterson;Louis Patrick Leroux

Student:

Ali Yazdizadeh

Partner:

HexMap Inc

Discipline:

Environmental sciences

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Synthesis and modeling of stimuli-responsive polymers for fracturing fluids use

Currently, the global warming alerts, oil prices fluctuations and clean energy have paved the way of investing in the producing wells by enhancing the recovery of hydrocarbons compared to exploration wells. Applying hydraulic fracturing from injected fluids is most common method used. These fluids create cracks in the bedrock and push the hydrocarbons to the surface. The well usually have harsh conditions of high temperatures up to 200 °C and a variant pH between 3-11 which cause challenges to the injected fluids. Our aim is to develop a new type of polymer from a green polymerization initiation technique to produce a recyclable viscosifying agent that can create a well transporting of the recovered hydrocarbons. In addition to the experimental work, a mathematical model will be developed based on the polymerization mechanism to establish a robust polymer system that can change its viscosity based on a stimulus. The mathematical model will be able to simulate the viscosity of the product under the disturbance conditions of these wells. The product will be more economical than current polymers used, inherently safer due to green reactants materials involved in the reaction and allow fast and efficient removal of the polymer.

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Faculty Supervisor:

Thomas Duever

Student:

Mohammed Hafedh Awad

Partner:

PolyAnalytik Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Elevate

Valuable Opportunities to Inspire Change thru Empowerment (VOICE) Program

This Mitacs project will support the VOICE program in building evaluation capacity and supporting evaluation of their program curriculum and mentor-mentee relationships as a result of completing the program. The Mitacs intern will work collaboratively with the VOICE project leaders in developing and carrying out an evaluation framework, and will work to ensure that the evaluative results inform meaningful change to the varying components of the program. This project provides VOICE with the resources they need to monitor the impacts of their work, the effectiveness of their program in facilitating conversations and changed views of gender-based violence in communities, and the achievement of their goals. By participating in this project, we will build their capacity and support in assessing the impacts of their work , collect evidence about the impact of the program on the community, and provide evidence that can be used to refine the VOICE project to better meet the participants who complete the program

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Faculty Supervisor:

Rebecca Gokiert;Marilyn Hawirko

Student:

Nick Denomey

Partner:

Golden Bears Alumni Association

Discipline:

Education

Sector:

Education

University:

University of Alberta

Program:

Accelerate

Engaging Inuit Communities Using Participatory Video to Document Perceptions and Solutions on Global Changes

Rapid environmental change in the Canadian Arctic has been affecting people by changing their environment, livelihoods, resources, as well as their cultural and biological diversity (IPCC, 2007; Rockström et al., 2009). This research project aims to document resilience and analyse perceptions and solutions related to global environmental changes in Tuktoyaktuk, Northwest Territories. Using participatory digital tools, youth participants will explore how plastics/microplastics in their environment and climate change affect their traditional foods and subsistence activities. In addition, the use of distance learning tools will be assessed as a way to share knowledge with schools and the communities and connect northern communities with the South.

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Faculty Supervisor:

Jutta Gutberlet

Student:

Maeva Gauthier

Partner:

Live It

Discipline:

Geography / Geology / Earth science

Sector:

Education

University:

University of Victoria

Program:

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