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

Development of reprogrammable metamaterial midsole for footwear

Athletic footwear is designed to enhance performance, comfort, and injury prevention. Current midsoles provide a level of performance that cannot be changed after fabrication, forcing a user to wear different pairs of shoes, each specialized for a given sports activity. For example, running shoes require high energy return for efficiency, whereas basketball shoes prioritize energy dissipation to reduce impact forces. Consumers are forced to purchase multiple sport-specific shoes, increasing costs and environmental waste. This project aims to develop a reprogrammable midsole using a recently introduced reprogrammable metamaterial, enabling post-manufacturing adjustments of mechanical performance for multiple sports activities and user requirements. The project will identify the most appropriate additive process for manufacturing and conduct a range of mechanical and computational testing to characterize the reprogrammability and performance of the midsole. The partner organization will gain a significant competitive advantage by accessing cutting-edge adaptive footwear technology with strong commercialization potential.

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Faculty Supervisor:

Damiano Pasini

Student:

Partner:

CXC

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

McGill University

Program:

Elevate

Research and Development of a Novel Natural Health Product for Pain Relief

This project aims to characterize and standardize Relief Mx, a liquid designed for pain management. Relief Mx combines traditional Chinese medicine with modern pharmaceutical components as an alternative to steroid-based nerve block treatments. The formulation includes active ingredients extracted from four herbal medicines: Achyranthes bidentata, Scrophularia ningpoensis, Lonicera japonica (honeysuckle), and Dendrobium. This study will identify the key constituents of Relief Mx, assess their stability and solubility, and investigate its permeation across membranes in vitro to better understand its pharmaceutical properties. By establishing a clear pharmaceutical profile and evaluating its permeability and diffusion, this research will support product standardization, enhance quality control, and provide scientific validation. These findings will help the partner organization improve product consistency and credibility, facilitating broader clinical adoption and natural health product approval.

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Faculty Supervisor:

Neal Davies;Raimar Loebenberg

Student:

Partner:

Neurica Scientific

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

Monitoring Biogas Plants via Configurable Custom Dashboards and AI-powered Assistants

Anessa offers software solutions for different stages in the lifecycle of a biogas plant. Solutions include feasibility analysis, feedstock planning and optimization, and monitoring. This proposal focuses on improvements and advances in the areas of optimization and monitoring. As a biogas digester uses living bacteria to transform waste materials into gas and fertilizer, creating and maintaining optimal conditions even during external changes such as weather and feedstock fluctuations is key to maximizing revenue and keeping a project as profitable as possible. This research proposes two important advancements to the currently existing framework of anessa tools. Firstly, the goal is to develop a user-friendly and fully customizable dashboard system for real-time monitoring of biogas plants. Secondly, the project goal will be testing an LLM assistant integration into the dashboard system. This AI-powered component will potentially provide users with real-time insights, proactive anomaly detection and personalized guidance.

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Faculty Supervisor:

Georgiy Krylov

Student:

Partner:

Anessa

Discipline:

Computer science

Sector:

Clean Technology; Information and Communication Technology; Artificial Intelligence

University:

University of New Brunswick

Program:

Accelerate

A Pose-Correction Method for Intraoperative Measurements in Total Hip Surgery

During hip replacement surgery, current x-ray-based methods for guiding implant placement are often
affected by differences in patient positioning on the surgical table and movements of the hip joints, leading
to inconsistent and unreliable assessments. This research addresses part of these challenges using
advanced computer simulations to explore how various factors influence the accuracy of x-ray-based
measurements during hip replacement surgery. By developing improved techniques to create 3D models
of bones and implants from multiple x-rays taken at different angles during surgery, we aim to provide more
precise and reliable measurements to surgeon during operation. These “adjusted” measurements will
account for movements of pelvis and hip joint positions during surgery. The methods will be tested using
data from 100 simulated surgeries and compared with highly accurate 3D scans. The ultimate goal is to
integrate these advancements into existing assistive technologies, improving surgical outcomes and
reducing the risk of errors.

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Faculty Supervisor:

Ilker Hacihaliloglu

Student:

Partner:

Torus Biomedical Solutions Inc.

Discipline:

Life Sciences

Sector:

Manufacturing

University:

The University of British Columbia

Program:

Elevate

Novel Machine Learning Visualization of Threat Analysis for Cybersecurity Operations

This project will combine graduate level research expertise with best-in-class managed detection and response security operations, to develop ‘collaborative intelligence’ oriented tooling, in order to support Security Operations Centre (SOC) personnel in rapidly assessing the threat potential of suspect command lines and similar text objects. From a recent analysis of SOC AI usage, it is evident that rapid threat analysis of obfuscated or otherwise complicated code objects is a prime opportunity to enhance SOC performance. We will leverage modern ML, AI, and visualization tools to develop innovative and highly functional SOC threat analysis tooling.

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Faculty Supervisor:

Jian Zhao

Student:

Partner:

eSentire

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

High-resolution UAV-LiDAR Mapping for Assessing Erosion and Infrastructure Vulnerability Along the Niagara Escarpment

This project explores the critical geohazards affecting the Niagara Escarpment using advanced UAV-LiDAR technology. By mapping erosion patterns and assessing infrastructure vulnerabilities at sites like Shorthills, Wainfleet, and Balls Falls, the research aims to enhance public safety and inform conservation strategies. A key outreach component, “GeoHikes”, will engage the public through interactive 3D models and educational materials integrated into a digital hub. The project brings together experts in structural geology, fluvial geomorphology, UAV surveying, data science and science communication to deliver cutting-edge insights while promoting community awareness of the region’s unique geological heritage. This work will empower the public with tools to better understand and protect the escarpment’s natural and cultural resources.

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Faculty Supervisor:

Alexander Peace;Elli Papangelakis

Student:

Partner:

APGO Education Foundation

Discipline:

Earth science

Sector:

Education; Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Innovative Recycling Solutions for Transforming Plastic Waste: Advancing Acrylonitrile Butadiene Styrene (ABS) Sustainability

This project addresses the growing problem of plastic waste by developing a method to recycle waste plastics into high-quality materials. Interns will work with Polystyvert, a recycling technology provider, to create a new type of recycled ABS (rABS) plastic using waste materials. They will experiment with blending recycled SAN (rSAN) with both virgin and recycled rubbers to produce durable rABS materials. This process will involve detailed testing of the material’s properties to ensure it meets industry standards. By improving recycling methods, this project aims to reduce environmental impact, lower production costs, and support the development of sustainable materials. The expected benefit for Polystyvert is the creation of more efficient and environmentally friendly recycling processes, leading to high-quality products and a stronger position in the recycling industry.

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Faculty Supervisor:

Patrick Lee

Student:

Partner:

Polystyvert

Discipline:

Engineering

Sector:

Administrative and support, waste management and remediation services

University:

University of Toronto

Program:

Accelerate

Application of Artificial Intelligence (AI) for improved and sustainable swine production

Artificial Intelligence (AI) is changing the way we do things, and pig farming is no exception. To improve pig production in Canada, researchers from the Canadian Centre for Swine Improvement, the Prairie Swine Centre, and the Centre de développement du porc du Québec are teaming up with tech companies. They’re testing new AI tools to help farmers make better decisions. These tools can help identify problems like early piglet death and health issues. The goal is to make pig farming more efficient, sustainable, and profitable. The project will focus on using real-time data to improve pig health and productivity. By using AI, farmers can make data-driven decisions that can lead to healthier pigs and more efficient farms.

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Faculty Supervisor:

Jamie Ahloy Dallaire

Student:

Partner:

Centre de développement du porc du Québec

Discipline:

Computer science

Sector:

Agriculture; Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

The Feasibility, Fidelity and Acceptability of Implementing a High-Impact, Growth Mindset and Trauma-Informed Tutoring Model to Improve Educational and Well- Being Outcomes among Indigenous, Crown Ward and Child Welfare-Involved Youth

The proposed research project, aided by 2 interns (PhD students) from the University of Toronto and University of British Columbia, aims to evaluate the feasibility, fidelity and acceptability of a specialized tutoring program designed to support the social and emotional development of Indigenous and child welfare-involved youth. This program, offered by TutorBright, combines academic tutoring with growth mindset principles and trauma-informed practices to help students build essential skills, such as emotional regulation, resilience, and social awareness.
Through the study, the interns will gather data on the program’s impact on both academic performance and emotional well-being. For TutorBright, this research provides valuable insights into how to tailor tutoring services to meet the unique needs of vulnerable youth, enhancing the effectiveness and reach of their educational support.

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Faculty Supervisor:

Jennifer (Jen) Vadeboncoeur;Ashley Quinn;Ashley Quinn;Jennifer (Jen) Vadeboncoeur

Student:

Partner:

TutorBright

Discipline:

Sociology

Sector:

Education

University:

The University of British Columbia; University of Toronto

Program:

Accelerate

3D Interactive Immersive Experience in Hospital and Long-Term Care

This study proposes to address these gaps using 3D Interactive Immersive Experience technology. By leveraging advanced 3D projection and sensor systems, the project will create accessible, engaging, and interactive virtual environments without reliance on headsets. Research will be conducted with older adults living with dementia in both a hospital unit and a Canadian LTC facility, employing Human-Centered Design to define user needs and system requirements. Implemented in three phases—planning, on-site intervention, and evaluation—this co-development strategy aims to enhance resident well-being, promote ethical data use, and explore large-scale feasibility. Findings will inform integration strategies, fostering the safe and effective use of 3D immersive technology in dementia care.

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Faculty Supervisor:

Lillian Hung

Student:

Partner:

Motive Force Tech Canada Corp.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Elevate

Conversational AI companion for older adults with memory loss

This study explores the use of an AI chatbot to support people with dementia in long-term care (LTC). Dementia affects memory and can cause anxiety, leading people to ask repetitive questions. The chatbot is designed to offer compassionate responses and emotional support. Using a collaborative approach, the study will involve residents, families, and staff in planning, testing, and evaluating the chatbot over a year. The goal is to create a helpful, user-friendly tool that meets the needs of LTC residents. The findings will guide future improvements, aiming to enhance care and address the emotional needs of those with dementia.

View Full Project Description
Faculty Supervisor:

Lillian Hung

Student:

Partner:

CloudMind Software Inc.

Discipline:

Life Sciences

Sector:

Life Sciences (not health); Health and Related Sciences and Technology; Artificial Intelligence

University:

The University of British Columbia

Program:

Elevate

Cold-season subtropical air mass intrusions into the Saint-Lawrence River Valley: dynamic-thermodynamic impacts on extreme precipitation and regional climate change

The heavily populated region of Québec’s Saint Lawrence River Valley (SLRV) experiences
among the largest number of hours of freezing rain on the North American continent. Some of
the region’s most impactful freezing rain events, including the Great Ice Storm of 1998 and
the recent April 2023 ice storm, were characterized by very warm, moist subtropical air above
the valley’s entrenched cold air. The Intern’s research is designed to identify an associated
subtropical temperature- and moisture-based metric that signals an increased likelihood of
extreme winter precipitation, particularly freezing rain, in the SLRV region of Canada. This
research promises to provide improved guidance to the Québec stakeholders on the
likelihood of extreme winter precipitation in an environment of ever-increasing global
warming. The results of this research are expected to benefit the partner organization,
Ouranos, in providing regional climate-change projections to the citizens of Québec.

View Full Project Description
Faculty Supervisor:

John Gyakum

Student:

Partner:

Ouranos Inc

Discipline:

Physics

Sector:

Accommodation and food services; Agriculture; Professional, scientific and technical services; Public administration

University:

McGill University

Program:

Accelerate

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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.