Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

COVID-19, Mental Health, and Racialized Women in the Workforce

This project explores the mental health impacts of COVID-19 on racialized women in the workforce in Ontario. As groups overrepresented in poverty rates, unemployment rates, and low-waged and precarious work prior to the pandemic, racialized women are more likely to experience poor or negative mental health and wellbeing during the pandemic. Despite being one of the most vulnerable groups in Canada during a worldwide mental health crisis, racialized women have yet to be the focus of any serious study related to mental health in the pandemic. Our research provides a critical examination of the mental health experiences of these women and seeks to understand what coping mechanisms and services should be encouraged both immediately and in the long-term future. Islamic Relief Canada will also benefit from these findings as they will inform our programs and be compiled within a report that will be distributed to our donors and community members, many of whom are racialized women in the workforce themselves.

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Faculty Supervisor:

Brenda Spotton Visano

Student:

Partner:

Islamic Relief Canada

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

York University

Program:

Accelerate

Developing a new workflow for occupancy estimation using Wi-Fi sensing for building energy simulation

The current study aims to develop a new workflow for occupancy schedules estimation using WiFi sensing technology and utilizing different machine learning and deep learning algorithms. Aerial will provide preprocessed CSI data, occupied and non-occupied time series, and activity level time series to be used by intern for extracting occupancy presence pattern, the number of people estimation and pattern extraction, and human activity estimation. Pattern extraction and analysis of the three mentioned datasets will provide a basis for estimating four occupancy presence, occupancy activity, lighting, and electrical equipment usage schedules. The estimated occupancy schedules will be fed as an input of EnergyPlus (a building energy simulation software) along with other energy-related data to calculate the building heating and cooling demand. In the end, a short report will be provided to occupants as feedback of their behavior by analyzing the energy demand and occupancy behavior.

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Faculty Supervisor:

Ursula Eicker;Nizar Bouguila

Student:

Partner:

Aerial Technologies Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Environmental forensic source identification for complex contaminant mixtures using advanced computational fingerprinting

Environmental forensic investigations endeavour to identify connections between environmental pollution and polluters. There assessments are integral to legal cases spanning pollution from accidental spills to illegal disposal of chemical waste. A common challenge is the investigation of complex contaminant mixtures that may have multiple polluters or where only part of the complex contaminant mixture are indicative of the polluter.
Computational fingerprinting methods are promising tools to untangle the relevant source or polluter-specific “fingerprints” out of complex contaminant profiles.
For the proposed research, we aim to develop automated statistical fingerprinting applications based on machine learning and multivariate statistical analyses to help identify
1) The specific ignitable liquids used in different arson cases
2) Different plastic product categories based on their additive patterns
The established methods will enable the investigation of main plastic product types that contribute to local microplastic pollution and help identify individual polluters.

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Faculty Supervisor:

Roxana Suehring

Student:

Partner:

Chemistry Matters

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Accelerate

BSI – Fatima Yousafzai

This project aims to tackle the challenge of finding different ways Viva could optimize its existing work processes to generate maximum results, as well as innovating in the marketing domain. This requires the intern to observe technical insights such as user interaction and behaviour, as well as traffic across various virtual platforms. This understanding would aid in the development of new marketing strategies Viva could implement, and work towards improving current methods of customer engagement as well.

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Faculty Supervisor:

Norah McRae

Student:

Partner:

Exec Viva Inc

Discipline:

Business

Sector:

Education; Social Innovation; Technology

University:

University of Waterloo

Program:

Business Strategy Internship

Swarm Fabrication

We introduce Swarm Fabrication, a novel concept of creating on-demand, scalable, and reconfigurable fabrication machines made of swarm robots. We present ways to construct an element of fabrication machines, such as motors, elevator, table, feeder, and extruder, by leveraging toio robots and 3D printed attachments. By combining these elements, we demonstrate constructing an X-Y-Z plotter with multiple toio robots, which can be used for drawing plotters and 3D printers. We also show the possibility to extend our idea to more general-purpose fabrication machines, which include 3D printers, CNC machining, foam cutters, line drawing devices, pick and place machines, 3D scanning, etc. Through this, we draw a future vision, where the swarm robots can construct scalable and reconfigurable fabrication machines on-demand, which can be deployed anywhere the user wishes. We believe this fabrication technique will become a means of interactive and highly flexible fabrication in the future.

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Faculty Supervisor:

Ryo Suzuki

Student:

Partner:

The University of Tokyo

Discipline:

Computer science

Sector:

Education

University:

University of Calgary

Program:

Globalink Research Award

Development of Interactive, Online Quantum Computing Educational Material

In this project, the intern will work closely with the staff of Xanadu, a quantum computing company, to develop educational materials intended for an audience who are comfortable with classical computer programming, but have no prior knowledge or experience with quantum physics or quantum computers. By using interactive, web-based instructional materials, and animated graphics, the resource will increase learner engagement and success. This project will create additional learning modules on top of those already created in an earlier project. A small study will be carried out to measure the effectiveness of the new educational materials, and identify strengths and areas for improvement.

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Faculty Supervisor:

Ulrike Stege;Hausi Muller

Student:

Partner:

Xanadu;Quantum Algorithms Institute

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Community Safety and Wellbeing: How can local governments and community partners make a difference?

Increasing safety and wellbeing is a desired outcome for most communities across the globe and the path to improving these results is murky and complex. These outcomes are influenced by many factors including the priorities of multiple levels of government, the community development approaches that are undertaken and the leadership styles and quality of relationships that are developed amongst leaders to achieve results. Amidst this complexity, municipal public servants and community leaders, many of whom have devoted their careers to improving social outcomes, are challenged to identify and implement best practices that meaningfully improve community safety and wellbeing. This research is designed to support the partner organization, Strathcona County, and all municipalities as it identifies best practices to achieve meaningful results.

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Faculty Supervisor:

Mary Bernard;Tracy Smith-Carrier

Student:

Partner:

Strathcona County;Civida

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology; Public administration

University:

Royal Roads University

Program:

Accelerate

Understanding of intra-annual wood formation and phenological development of black spruce and balsam fir over the spatial gradient in the boreal forest of Quebec

Climate warming may have resulted in altered initiation and termination dates of the primary growth (e.g. phenological development) and the secondary growth (e.g. stem xylem growth) of trees in the boreal forest, consequently impacting wood quality, forest growth and productivity, and carbon sequestration. This project will analyze the intra-annual wood formation and phenological data collected for black spruce and balsam fir over an altitudinal gradient in the Parc National des Monts- Valins from 2010-2013, and the proxy data of wood formation (onset, duration and termination) reconstructed for black spruce from 1950-2010 over a latitudinal gradient between 48-51ºN in Saguenay-Lac-Saint-Jean area, Quebec to address the current knowledge gaps in phenology and wood formation for the two species with climate warming. The results may contribute to better assessment on the potential growth responses of trees and forests to future climate warming over time, and better modelling and predicting of wood formation and quality, phenology as well as forest growth and productivity in the Quebec’s boreal forest under climate warming.

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Faculty Supervisor:

Annie Deslauriers

Student:

Partner:

Produits forestiers Résolu (Dolbeau-Mistassini, QC);Consortium de recherche sur la foret boreale commerciaIe;Coopérative de solidarité en recherche et développement forestier de l’Abitibi-T;Université du Québec à Chicoutimi

Discipline:

Earth science

Sector:

Agriculture

University:

Université du Québec à Chicoutimi

Program:

Accelerate

The impact of parent coach training on the clinical practice of early interventionists

The proposed research project aims to develop, implement, and evaluate the impact of a parent coach training program for a group of 12 Early Intervention (EI) professionals. The training will be grounded in evidence-informed practice and structured using an established framework for clinical competency education. The EI professionals will learn about the theories that inform parent coaching, the processes involved in parent coaching, and learn how to engage in parent coaching practices with families on their caseloads. The trainees will self-reflect on their progress with video feedback, fidelity rating scales, and trainer support. Finally, following the completion of the training, trainees will be interviewed to explore their perceptions of the training procedures and on the impact the parent coach training had on their clinical practice in working with families.

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Faculty Supervisor:

Veronica Smith

Student:

Partner:

Vancouver Island Health Authority (Victoria, BC)

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

University of Alberta

Program:

Accelerate

A novel passive hand tremor attenuator for Parkinson’s patients

The aim of this research is to introduce a novel tremor suppression device capable of attenuating both Parkinsonian and Essential tremors. The approach taken involves treating tremors as vibration challenges and applying the theory of a vibration absorber to design and optimize the novel device. Detailed analysis of vibration absorption is used to identify key parameters and relationships in suppressing unwanted vibrations. Moreover, the challenge of biofidelity of the human-arm model in both mathematical and computer modelling is shown to be significant in achieving a viable solution.

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Faculty Supervisor:

Hadi Mohammadi

Student:

Partner:

Summit Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Spectral Methods in Quantum Kernel Classifiers

Quantum Machine Learning is an emerging field of science, exploring the role that quantum computers can play when combined with machine learning models and methods. Within this field, kernel methods have quickly become one of the most promising and exciting techniques to show benefits in performance, even when using the current primitive quantum computers that are available today. Despite these exciting experiments, a deep understanding of the role played by the quantum system in kernel methods, and the origin of the benefits is still lacking. This project seeks to further develop the fundamental theory and conduct simulations in order to deepen understanding and further improve this emerging technology.

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Faculty Supervisor:

Achim Kempf

Student:

Partner:

Xanadu

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Optimization of Waste-to-Resource Plants with Machine Learning and Multi- Objective Reinforcement Learning

In waste-to-resource processes, variations in operating conditions are common, to accommodate varying process objectives and ambient disturbances. In these cases, well-tuned operating conditions are disrupted, and correlations among process and quality variables are broken, leading to unexpected outcomes. Due to large number of involved variables and their complex relations, it is challenging to re-tune system parameters. Further, process optimization focus may change, or multiple objectives need to be optimized concurrently. Therefore, the goal of this project is to optimize the waste-to-resource plants owned by Anaergia by developing a set of advanced time series, machine learning and reinforcement learning algorithms, aimed at improving the existing parameter tuning and optimization mechanism. The proposed research program addresses the aforementioned challenges through 3 projects: a) Develop machine learning models to detect key correlations from the data for further process modeling; b) Design multi-objective reinforcement learning based recommendation system for multiple optimization objectives; c) Develop a process monitoring and diagnosis framework for real-time anomaly detection and root cause analysis.

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Faculty Supervisor:

Qinqin Zhu;Hector Budman

Student:

Partner:

Anaergia Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

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