Innovative Projects Realized

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

31132 Completed Projects

2940
AB
5159
BC
837
MB
685
NL
882
SK
9291
ON
9695
QC
97
PE
601
NB
1161
NS

Projects by Category

The effectiveness of stormwater ponds in water quality management

Stormwater ponds are widely used across urban areas to improve water quality, yet their actual long-term performance under different design standards remains poorly quantified. This project will evaluate how efficiently these ponds remove sediment and associated pollutants by applying a mass-balance approach and tracking deposition rates through time. Although the technology is assumed to work, the lack of empirical data on how quickly ponds fill, how their treatment capacity changes as they accumulate sediment, and whether different designs perform consistently leaves major gaps in stormwater planning. By comparing multiple ponds built to varying standards, the project will determine whether they function similarly or diverge in performance, and how these differences influence maintenance needs, lifespan, and water-quality outcomes. The results will provide municipalities with a clearer understanding of stormwater pond efficiency, sediment accumulation dynamics, and design-driven performance variability, supporting more informed decisions about future infrastructure and long-term watershed protection.

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Faculty Supervisor:

Robert Summers

Student:

Partner:

EPCOR Utilities Inc.

Discipline:

Engineering

Sector:

Utilities

University:

University of Alberta

Program:

Business Strategy Internship

Leveraging Large Language Models to Investigate Machine Learning Specific Code Smells: An Empirical Study

This project seeks to improve the understanding of how Machine-Learning (ML)-specific code issues arise during software development by using Large Language Models to analyze developers’ code changes over time. An automated framework will be created to track code updates, detect ML-related issues, and identify the type of developer activity (feature development, bug fixing, enhancement, or refactoring) that introduced them. The project will strengthen collaboration between the institutions through shared supervision of the intern and interactions, and discussions of ongoing experiments and results. The results, datasets, and tools produced during the project will lay the foundation for long-term collaboration, student co-supervision, and future funding opportunities.

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Faculty Supervisor:

Zadia Codabux

Student:

Partner:

University of Salerno

Discipline:

Computer science

Sector:

Information and Communications Technology (ICT); Artificial Intelligence

University:

University of Saskatchewan

Program:

Globalink Research Award

L2M – Smart Lung Physio: LTC Adoption Readiness

Smart Lung Physio is validating adoption readiness for a respiratory care solution in long-term care. The project will map decision-makers, identify adoption drivers and barriers, and define non-clinical pilot readiness criteria to support an evidence-based go/no-go decision for an LTC pilot.

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Faculty Supervisor:

Bilal Farooq

Student:

Partner:

Innovation Factory

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Business Strategy Internship

L2M – A wearable home-use solution for hallux valgus management

This four-month project will support the early development of a home-use wearable approach for hallux valgus by reducing key market and validation uncertainties. The work will focus on structured discovery with clinicians to understand real-world needs, current practice patterns, safety expectations, and usability requirements for potential home use. In parallel, the project will review existing research and commercially available approaches in this area to clarify what is already known and where gaps remain. Findings will be summarized into a clear set of user and stakeholder requirements and an initial roadmap for next-step testing and evaluation. These outputs will help the partner organization make informed decisions on product direction, prioritization, and planning for future validation without disclosing proprietary implementation details.

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Faculty Supervisor:

Dafna Sussman

Student:

Partner:

Innovation Factory

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Business Strategy Internship

L2M – Selective Lithium-Ion Capture Using Hybrid Ion-Imprinted Superabsorbent Polymers

This project will evaluate a new material designed to selectively capture lithium from battery recycling solutions and lithium extraction streams in a cleaner and more efficient way. Current recovery methods often rely on high chemical use and energy-intensive processes that increase cost and environmental impact while recovering lithium inefficiently. The project will work directly with industry stakeholders to understand their needs, test the material under realistic conditions, and assess how it could be integrated into existing recovery processes. The expected outcome is a practical pathway toward a lower-cost, lower-impact lithium recovery solution that improves resource efficiency, supports Canada’s battery supply chain, and enables more sustainable recycling and extraction operations.

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Faculty Supervisor:

Siu Ning Leung

Student:

Partner:

Innovation Factory

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

York University

Program:

Business Strategy Internship

Triboelectric nanogenerators-new materials development (KH)

Clean electricity is energy that is both sustainable and non-polluting. Such sources of energy are ideal for mitigating climate change. For the full benefit of clean energy generation to be realized, sustainable practices must be integrated into the development of clean technologies. This requires using materials that are both renewable and recyclable. These can indeed offset the otherwise large carbon footprint of clean energy generating technologies. The project will endeavor to integrate sustainable materials that are also compatible with electricity generation by mechanical actuation. Elastomers that are ideally suited for such actuation will be developed exclusively from renewable materials with the advantage of being compostable. The project will evaluate how renewable materials can be compounded to maximize electricity generation without sacrificing sought after elasticity. The capacity of the elastomers to generate electricity by mechanical actuation will also be evaluated. A major benefit of the project will be zero polluting technology for generating electricity that can be recycled by composting.

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Faculty Supervisor:

William Skene

Student:

Partner:

Sorbonne Université

Discipline:

Physics

Sector:

Clean Technology; Sustainability and the Environment; Green/Alternative Energy

University:

Université de Montréal

Program:

Globalink Research Award

LoC-SensAI: Low-Cost IoT RF Sensing with AI for Real-Time Precision Irrigation Decision

The LoC-SensAl project develops an affordable system to help farmers manage irrigation in real-time using low-cost sensors and Artificial Intelligence (AI). One intern will focus on designing the physical sensors to measure soil moisture, while the other will create AI models to turn that data into precise watering schedules. This technology will help farmers save money and water while improving crop yields. Ultimately, the project promotes sustainable agriculture and protects natural resources in both Canada and Tunisia by making “smart farming” tools more accessible.

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Faculty Supervisor:

Lokman Sboui

Student:

Partner:

École supérieure de communications de Tunis (SUP'COM)

Discipline:

Engineering

Sector:

Agriculture and Food; Artificial Intelligence

University:

École de technologie supérieure

Program:

Globalink Research Award

A Bayesian Optimized Multi Harmonics Index Approach for Fault Diagnosis of Gearboxes

The project aims to design and develop an algorithm that can diagnose faults in planetary and fixed-axis gearboxes. Common faults in gearboxes are often masked by the Gear Meshing Frequency, making them difficult to detect via classical spectral analysis. A multi-harmonic index approach based on an adaptive combined envelope spectrum is selected as the foundational algorithm due to its robustness to noise in bearing analysis and its cyclostationary capabilities. Moreover, a Bayesian algorithm is proposed to select the ideal frequency band, improving the time complexity as compared to other optimization algorithms.

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Faculty Supervisor:

Xihui (Larry) Liang

Student:

Partner:

University of Technology Sydney

Discipline:

Engineering

Sector:

Education

University:

University of Manitoba

Program:

Globalink Research Award

Physiopathological basis of a new neuro-ophthalmological disease linked to “chemsex”.

Chemsex refers to the recreational use of psychoactive substances to enhance sexual experiences and is associated with increased sexual risk-taking and mental health issues, including substance dependence. One of the most commonly used substances in this context is isopropyl nitrite, owing to its low cost, wide availability, and ease of inhalation. In recent years, growing concern has emerged regarding its effects on the central nervous system (CNS), particularly following reports of retinal dysfunction linked to neurodegenerative processes.
While visual disturbances after isopropyl nitrite exposure are often transient, multiple cases of irreversible retinal damage have been documented. These adverse effects appear to occur more frequently in individuals who concurrently use ritonavir, a protease inhibitor widely prescribed for viral infections such as HIV, and sildenafil citrate, a phosphodiesterase type 5 inhibitor frequently used in chemsex settings. However, stigma surrounding chemsex has led to substantial underdiagnosis, limiting current knowledge of long-term neurological consequences beyond the retina.
This project hypothesizes that combined exposure to a nitric oxide donor, a PDE5 inhibitor, and a protease inhibitor disrupts redox homeostasis in neurovascular units by increasing nitric oxide bioavailability. The resulting oxidative and nitrosative stress damages the neurovascular endothelium, induces rapid neurovascular uncoupling, and may trigger neurodegeneration.

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Faculty Supervisor:

Sergio Crespo Garcia

Student:

Partner:

University of Alcalá

Discipline:

Life Sciences

Sector:

Education

University:

Université de Montréal

Program:

Globalink Research Award

Psychology in the works of Nietzsche and Canguilhem

I am going to Weimar to study for one semester (from April 2026 to August 2026) at the Bauhaus-Universität in Weimar. I will be hosted by Professor Henning Schmidgen, a specialist in the history and philosophy of science and technology. Professor Schmidgen will lead philosophy seminars in German, which I will attend and for which I will be evaluated. In addition, he will be available to supervise my research and support the writing of my thesis with his in-depth knowledge of the philosophers I am studying, Friedrich Nietzsche and Georges Canguilhem. Weimar is also a strategic city for me, as it is home to the Nietzsche Archives. This will allow me to benefit from their activities, specialists, and documents to deepen my understanding of the German thinker. Furthermore, I will take advantage of my presence in Europe to make several trips to Paris, where the Canguilhem Archives are located, for research stays. My co-supervisor, Prof. Pierre-Olivier Méthot, and I intend to organize one of these stays in Paris in April for this same purpose.

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Faculty Supervisor:

Pierre-Olivier Méthot

Student:

Partner:

Bauhaus-Universität Weimar

Discipline:

Sociology

Sector:

Education

University:

Université Laval

Program:

Globalink Research Award

Electrochemical detection of droplets in microfluidic systems

The combination of electrochemical sensing with miniature fluid handling systems (microfluidics) can lead to the creation of a miniature and portable all-in-one analytical platforms or “lab-on-a-chip”. Lab-on-a-chip technology is used in a variety of sectors, including healthcare (e.g., medical diagnostic tests) and the environment and natural resources (e.g., remote monitoring & sensing). However, electrode fabrication methods for high resolution and small feature sizes are expensive while low-cost methods cannot reach the microscale resolutions needed for microfluidics. Recently, we have developed a simple and straightforward method to combine electrodes formed by the laser-induced graphene (LIG) process with high resolution microfluidic channels. LIG electrodes are formed by irradiating a carbon-rich substrate with high energy laser, generating graphene. This is a low cost process that is amenable to rapid prototyping and can achieve electrode sizes compatible with microfluidic channels. Our new method requires additional characterization and test applications to mature the technology so it can be applied to a variety of applications. Here, the intern will work to characterize the effect of different parameters of the underlying substrate for the LIG electrodes and seek to integrate LIG-based electrodes with a droplet microfluidic device for proof-of-principle applications.

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Faculty Supervisor:

Darius Rackus

Student:

Partner:

École Supérieure de Physique et de Chimie Industrielles de la Ville de Paris

Discipline:

Physics

Sector:

Education

University:

Toronto Metropolitan University

Program:

Globalink Research Award

L2M – Market Validation for a Next-Generation Green Hydrogen Production Solution

This project focuses on validating a next-generation green hydrogen production technology and advancing its path toward commercialization. Green hydrogen is widely recognized as a critical solution for reducing greenhouse gas emissions in industries such as chemicals, energy storage, manufacturing, and transportation. However, today’s green hydrogen production methods are still expensive and energy-intensive, limiting large-scale adoption.
Through the Lab2Market Validate program, this project supports the commercialization of a novel green hydrogen solution developed by the Canadian startup Faradix. The technology aims to improve the efficiency and reduce the cost of green hydrogen production by combining electrochemical innovation with intelligent energy management, enabling hydrogen to be produced more sustainably and closer to where it is used.
Over four months, the project will engage directly with industrial stakeholders, technology integrators, and policy experts to understand real customer needs, economic requirements, and regulatory constraints. These insights will be translated into market use cases, cost models, and deployment strategies that help determine where and how the technology can deliver the greatest value.
The outcome of the project will be a market-driven commercialization roadmap, including validated customer segments, economic performance benchmarks, and pilot opportunities. By bridging technical innovation with market reality, the project contributes to Canada’s clean energy ecosystem and supports the development of globally competitive climate technologies.

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Faculty Supervisor:

Maxime van der Heijden

Student:

Partner:

Innovation Factory

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Business Strategy Internship

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.