Innovative Projects Realized

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

30508 Completed Projects

2882
AB
5105
BC
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projects by Category

Blockchain-based federated learning for Agri-food supply chain

This project utilizes blockchain technology, smart contracts, and federated learning techniques to enhance collaboration between multiple parties for the agri-food supply chain application. It aims to promote data trust between multiple stakeholders in the supply chain by adopting blockchain technology and federated learning techniques. Multiple parties can keep their data at their local data storage, protect individuals’ privacy, and still contribute to model training and extracting knowledge. Blockchain technology is adopted as a distributed storage to securely verify data and distribute model training data on a ledger replicated across a peer-to-peer network. Smart contracts are responsible for the automatic execution of aggregating model updates and tasks of multiple parties.

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Faculty Supervisor:

Sara Rouhani;Carson Leung

Student:

Partner:

TheoryMesh Corp.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Inspection of Bridges in Ontario for Damage Detection and Rehabilitation

This Mitacs project will undertake bridge inspections of 33 road bridges in Ontario to determine locations and level of damages in these bridges and suggest appropriate rehabilitation techniques to keep these bridges in service. The data collected will be added to the current pool of similar data already collected by the industry partner, MEDA to develop an inhouse bridge inspection manual. This manual will allow MEDA to be more productive and have a competitive advantage for the future bridge inspection projects. This Mitacs project will also undertake lab tests and computer modeling on concrete girders with various levels of defects. The data collected from this part of the project will be used to develop design guidelines for repair of damaged concrete girders of bridges. These design guidelines will help Canadian practicing engineers in designing the rehabilitation technique knowing the location and level of damages in the concrete girders.

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Faculty Supervisor:

Sreekanta Das

Student:

Partner:

MEDA Engineering & Technical Services

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

Automatic Optical Character Recognition Preprocessing for Custom Gameplay Text

Computer Games are one of the key use cases of graphics cards of AMD. To ensure highest quality and performance, extensive testing of graphics hardware and software is required. However, much of this gameplay testing is manual and requires significant efforts due to varying styles in games and their versions. In this context, an open challenge lies in the difficult to automatically pre-process multiple heavily styled and color instances of text that appear in various games which current requires manual tuning. The goal of this project is to investigate and implement machine learning-based solutions to automatically pre-process, detect and recognize text in gameplay settings. The solution developed should be able to handle varying art, text, lighting, and user-interface styles and configurations as seen in games. The development of this framework would result in saving a significant amount of manual effort needed for automated testing of games.

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Faculty Supervisor:

Babak Taati

Student:

Partner:

AMD Canada

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Solar-driven H2 production by photovoltaic-electrochemical water splitting

Presently, it is significant to reduce CO2 emission and other greenhouse gas emissions. One of the major CO2 emission contributors is transportation sector. To reduce emissions and achieve a zero-emission society, the use of H2 as a fuel in ground, air, and marine transportation, a feedstock in petrochemical industry, and an energy carrier for energy storage is one of the most promising and environmentally benign option. Rather than using traditional and emissions-intensive steam methane reforming and coal gasification for H2 production, this proposed project will integrate solar cell with an electrolyzer to produce H2 by electrochemical water splitting. To lower the operating and capital costs, a new electrolyzer will be designed using noble metal-free and bifunctional electrocatalysts. In conclusion, a solar energy-driven and low-cost water splitting and H2 production device will be developed as a result of this proposed research project.

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Faculty Supervisor:

Yulin Hu

Student:

Partner:

Aspin Kemp and Associates

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Prince Edward Island

Program:

Accelerate

Community Based Participatory Research Strategies for Combining Creativity with Sustainability in the Arts and Beyond

The proposed Creativity and Sustainability post-doctoral fellowship will be situated at Mass Culture (MC),
and executed in cooperation with University of Toronto Scarborough’s (UTSC) Urban Just Transitions
(UJT). Over the years, MC and the scholars involved in UJT have experimented with various forms of
community-engaged methods in order to generate impactful research that will inform policy-making and
advocacy work to address inequities in their respective fields of interest. This project proposes to research,
document, and evaluate relevant community-based activities and resources proposed, developed and used
by MC and UJT, particularly participatory design, implementation and assessment processes. The
Creativity and Sustainability project has two intersecting objectives. First, to empower specific marginalized
groups and communities through the use of community based participatory research (CBPR) approaches,
including annotating and adding to Artifex, and building public bibliographies for UJT. Second, by
documenting, comparing and assessing the use of community-engaged, participatory, and arts-based tools,
methodologies and frameworks at MC and UJT. The post-doctoral fellow will lead this process over a 12-
month period.
As an arts service organization, MC is known to be a central actor when it comes to sharing relevant
research on the arts across its own national network.

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Faculty Supervisor:

Mary Elizabeth Luka

Student:

Partner:

Mass Culture Canada

Discipline:

Sociology

Sector:

Arts, entertainment and recreation

University:

University of Toronto

Program:

Accelerate

Fast Phylogenetic Mapping of Functional Anchors from the Mining Microbiome

Microorganisms have radically shaped Earth’s atmosphere and landscapes. From providing oxygen in the air we breathe to nitrogen in soils for farming, their innumerable ecosystem services have long gone unappreciated and under utilized. Recent advances in DNA sequencing technology – where the letters of an organism’s DNA are read – and computing have revolutionized our understanding of the microbial world around us. Now, it is time to apply these lessons to industry. To this end, Koonkie Canada Inc. is a proud member of the international cyber-infrastructure development project “Mining Microbiome Analytics Platform (MMAP)”. MMAP will provide a database and software ecosystem supporting breakthroughs in microbiome-based resource exploration, extraction, mine closure and remediation, and position Canada as a global leader in ecosystem-aware mining, ensuring a prosperous economy and environment. The work proposed here focuses on enabling the rapid identification of enzymes mediating valuable processes in resource extraction to increase efficiency and mitigate environmental impact. As one of several pipelines and tools being developed for the MMAP platform, resulting data products will be used by synthetic biologists and engineers to create much needed technologies, and accelerate the mining industry’s transition to a low carbon future.

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Faculty Supervisor:

Steven Hallam

Student:

Partner:

Koonkie Canada Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Optimized lighting and defoliation strategies to increase yield and chemical uniformity in Cannabis sativa

Cannabinoid uniformity plays an important role on the quality and marketability of cannabis. Several strategies to optimize cannabinoid uniformity have not been extensively researched to date. The objective of this study is to evaluate lighting and defoliation strategies to maximize yield and uniformity of cannabinoids throughout cannabis plants. A randomized block design will be used to separate treatments. Each table will contain four lighting treatments which include HPS overhead, LED overhead, HPS with LED interlight and LED with LED interlight treatments. Two tables will be used per room with varying defoliation techniques. Aggressive defoliation and minimal defoliation techniques will be compared. The experiment will be replicated with a treatment randomization for a second cycle. This study will benefit the partner organization by determining which lighting and defoliation strategies increase efficiency in their production facility.

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Faculty Supervisor:

Mark Lefsrud

Student:

Partner:

Rose Lifescience

Discipline:

Engineering

Sector:

Agriculture

University:

McGill University

Program:

Accelerate

Exploring Deep Learning Models for Understanding Consumer Language

With the ultimate goal of enhancing Nexxt Intelligence’s market research SaaS platform, inca, this project will create a robust, scalable algorithm for clustering consumer utterances into groups which are useful to ad-hoc market research objectives, and interpretable via natural language descriptions to market researchers. Due to the multifaceted and nuanced nature of consumer opinions and feedback, this algorithm will leverage the latest advances in natural language processing for the purpose of representing semantics of complex sentences and phrases, detecting brand and product names even of hypothetical or proposed products, as well as extending work in human emotion modeling. The resulting algorithm will be applied to several downstream tasks, including a human-in-the-loop utterance analysis system and to a conversational framework for facilitating dynamic information-seeking dialogues.

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Faculty Supervisor:

Annie Lee

Student:

Partner:

Nexxt Intelligence

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Static loading tests and numerical analyses of movement of helical piles in soft clays

A helical pile is a screw steel pile comprising a small diameter hollow shaft welded with one or multiple helices. It has been widely used to retrofit structures or provide foundation support for infrastructure. The current research and design practice of helical piles have heavily focused on the “capacity”. In contrast, little attention has been paid to the performance of these piles, i.e., the movement of piles. This research project aims to understand the load-movement response through static loading tests of helical piles with and without post-grouting in soft clays. The 3D finite element models calibrated with loading test data will be used to conduct parametric analyses. The results of the experimental and numerical analyses will be used to improve the Unified Design Method. The outcomes of this research will advance the understanding of axially loaded helical piles and improve design analyses of helical piles in subsided and non-subsided ground.

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Faculty Supervisor:

Cheng Lin

Student:

Partner:

TerraCana Foundation Solutions Inc.

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Victoria

Program:

Accelerate

Direct and Selective Electroless Metallization of low-cost 3D Printed Composite Filaments Loaded with Metals to Enhance Surface Properties

The selective and direct metallization (electroless plating) of low-cost FFF 3D printed objects will be investigated in this research project. After 3D printing, the workpiece will be directly subjected to the electroless plating process (skipping the etching and catalyzation steps). We show that conventional low-cost conductive composite filaments loaded with metals can be used for direct plating. We will not only forego pre-treatment (i.e., harsh chemical etching), but we will also employ a formaldehyde-free (green) electroless copper solution, making this a major step forward in sustainable plastic metallization. Allowing complex and functional devices printed on a low-cost commercial desktop 3D printer to be rapidly and selectively metallized without modification is a significant advancement in lowering the cost and manufacturing complexity of 3D printed parts, increasing efficiencies, and reducing weight, and thus represents a turning point in the technology’s adoption. VPMR is developing custom 3-D products development and printing service, currently based on polymer FDM process. It is VPMR’s strategic objective to expand into low-cost 3-D printed metal products, based on the use of composite filaments, and later also debinding and sintering capability (such as currently available in system like XERION’s Fusion Factory).

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Faculty Supervisor:

Haniyeh (Ramona) Fayazfar

Student:

Partner:

VPM Research Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Ontario Institute of Technology

Program:

Accelerate

Barrelfish: Smart recruiting solution using artificial intelligence

The proposed research would use AI to create an application called Barrelfish that will help in the recruitment process. The project focuses on lowering the time it takes to discover data, screen applicants, and retrieve recommendations. Clients will be able to select employees based on their skills, abilities, and experiences, as well as conduct virtual tours and interviews, using the technology. Understanding and getting further perspectives on how to design new distinctive features, as well as continuing to improve current features, will be the emphasis of the project’s next stage of development. In addition, an algorithm audit will be performed to guarantee that the system is independent of bias when it comes to recruitment decisions.

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Faculty Supervisor:

Robert Soden

Student:

Partner:

SRA Staffing Solutions

Discipline:

Computer science

Sector:

Administrative and support, waste management and remediation services

University:

University of Toronto

Program:

Accelerate

Cancer treatment using drug-loaded thermosensitive liposomes with non-invasive ultrasound thermal therapy and temperature monitoring and control in an in vivo animal model

Chemotherapy is the most commonly used method for treating different cancer types that involves the delivery of chemotherapeutic drugs, leading to the death of cancer cells. However, the non-uniform distribution of chemotherapeutic drugs within the tumor and systemic toxicity has multiple side effects, and the delivery problem remains unsolved. Drug delivery carriers such as liposomes are used to deliver the drug to the targeted regions. To this end, a controlled and reliable release of the loaded chemotherapeutic drugs from a liposome core has remained a problem to overcome. The combined use of drug-loaded thermosensitive liposomes (TSL) and localized heating methods, ultrasound, can be used to deposit the drug in the heated region selectively. The efficacy of the proposed targeted treatment method will be based on the release of chemotherapeutic drugs from thermosensitive liposomes at the targeted region that is maintained at a predefined temperature for a specific time. This results in delivering concentrated and localized therapy and minimizing the side effects of systemic drug administration. To achieve this, we aim to develop a non-invasive ultrasound thermometry technique in combination with a non-invasive focused ultrasound thermotherapy technique (LIFU), and use the method toward achieving controlled drug release from thermosensitive liposomes

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Faculty Supervisor:

Michael Kolios;Jahan Tavakkoli;Carl Kumaradas

Student:

Partner:

FUJIFILM VisualSonics;Cancer Rx

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Accelerate

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