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

Data analytics in asset management of erosion control structures

The project aims to study the use of advanced machine learning algorithms to enhance the ability of TRCA to detect shoreline erosion. Accurate detection of shoreline erosion will have significant contribution to optimizing TRCA asset management plans. This will enable TRCA to work with local communities to reduce the impacts of climate change on shoreline erosion, which in turn will help safe shoreline properties and community spaces from increased erosion. The accurate perdition of erosion will also enable TRCA to develop effective plans to protect natural habitat. It will also support building a long-term investment plan to protect shorelines.

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Faculty Supervisor:

Tamer El-Diraby

Student:

Yunshun Zhong

Partner:

Toronto and Region Conservation Authority

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Evaluate the biodistribution of HyperMabs protein biologics therapeutics

HyperMabs is a biopharmaceutical company that designs and develops innovative therapeutics targeting lung diseases. HyperMabs is currently evaluating a drug candidate developed using in-silico methods to target lung disease. For this project, we aim to study the biodistribution of HyperMabs therapeutic, currently in its pre-clinical stage designed to treat several lung diseases. To achieve this, we wish to label the HyperMabs therapeutic with a labeling molecule to facilitate visualization of distribution of the therapeutic in lungs. The results obtained from this study will help the company to understand the efficacy of the drug which is crucial in optimising the dosing parameters to achieve maximum therapeutic benefits.

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Faculty Supervisor:

Elias Georges

Student:

Ashruti Jadvani

Partner:

HyperMabs Inc

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Improving Effective Collaboration Between Sponsorship Agreement Holders (SAHs), Constituent Groups (CGs) and Co-Sponsors in Canada’s Private Sponsorship of Refugees Program (PSR)

The proposed research seeks to learn more about the ways Sponsorship Agreement Holders (SAHs), collaborate with Constituent Groups (CGs) and Co-sponsors to sponsor refugees to resettle in Canada. For this project, the Canadian Unitarian Council (CUC), will be used as a case study. Given the limited capacity and resources that SAHs have available to them to do this humanitarian work, building effective systems of collaboration between all sponsors is important. The research findings will assist the CUC and other SAHs across Canada to improve effective collaboration among sponsors, and in doing so, maximize limited resources.

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Faculty Supervisor:

Luisa Schwartzman

Student:

Samia Tecle

Partner:

Canadian Unitarian Council

Discipline:

Sociology

Sector:

Other

University:

University of Toronto

Program:

Accelerate

Greenland shark bycatch mortality and mitigation in Canadian Arctic fisheries

Accidental fisheries catch ? or bycatch ? is a critical issue for conservation and fisheries management. Greenland sharks are a common bycatch in northern fisheries and are of concern because they are long-lived and may be vulnerable to overfishing. The proposed research addresses current data gaps related to Greenland shark bycatch through the following objectives: 1) Measure how many sharks survive encounters with fishing gear to estimate fisheries mortality rates; 2) Explore seasonal movements of Greenland shark throughout the region; and 3) Analyze fisheries data to identify patterns in shark bycatch rates over time. We will use electronic tags to measure shark bycatch survival and monitor seasonal habitat use. Fisheries catch data will be analyzed to examine when/where sharks are most often caught. Results from these objectives will help discover the impact of fisheries on Greenland sharks and identify ways to reduce fishing gear encounters with this vulnerable Arctic predator.

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Faculty Supervisor:

Nigel Hussey

Student:

Brynn Devine

Partner:

Nunavut Fisheries Association

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

Microchannel Plate & Shell Heat Exchanger for Flue Gas Heat Recovery

Natural gas power generation is a cost-effective method of generating electricity. NG power generators have been successfully installed in a wide variety of energy intensive facilities in Canada, including district energy systems, wastewater treatment facilities, schools, nursing homes, hospitals, office buildings, and residential buildings. However, more than 60% of the energy is wasted in the form of heat loss, and major heat loss is carried by the hot flue gas. The waste heat of flue gas can be recovered for domestic hot water supply, and also can be used to provide space heating in winter and space cooling in summer. In partnership with FEED Engineering Inc., the Thermal Management and Multiphase Flows Lab at UBC will develop a microchannel plate & shell heat exchanger for the effective recovery of waste heat from the flue gas of natural gas power generation.

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Faculty Supervisor:

Sunny Ri Li;Joshua Brinkerhoff;Abbas Sadeghzadeh Milani

Student:

Huaduo Gu

Partner:

FEED Engineering

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of British Columbia Okanagan

Program:

Accelerate

IN_SITU: A research study to evaluate & address the digital challenge of Co-Creation between the Arts and Artificial Intelligence

IN_SITU is a research study that investigates the possibilities and challenges of connection and bridge-building between Canadian arts sectors and the most advanced academic research centres dealing with Artificial Intelligence in Canada and beyond. The study will explore how artists and artistic organizations can augment their digital strategies, literacy and intelligence when artists co-create with tech/AI research environments. By examining and evaluating programs that integrate artists with emerging digital technologies, this study will aggregate best practices in residencies, fellowships, and incubators.

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Faculty Supervisor:

Richard Lachman

Student:

Tanya Pobuda

Partner:

Banff Centre for Arts and Creativity

Discipline:

Other

Sector:

Arts, entertainment and recreation

University:

Ryerson University

Program:

Accelerate

Mitigating goose herbivory at Westham Island tidal marsh.

Tidal marshes are essential ecosystems both economically and ecologically. They provide many natural resources, such as filtering pollutants from water and providing flood protection. However, since the 1980s, we have lost about 80% of the world’s wetlands including many tidal marshes. This internship aims to identify the role of goose herbivory on marsh vegetation as well as to identify the best way to mitigate impacts of goose herbivory on marsh vegetation. To accomplish this goal, the intern will be setting up an experiment that tests the effects of using snow fencing versus steel fencing along the substrate as a goose herbivory deterrent. This project is being conducted to better understand whether goose herbivory is contributing to loss of tidal marshes, and to inform management decisions that guide marsh vegetation restoration.

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Faculty Supervisor:

Eric Anderson

Student:

Esmeralda Martinez Bonilla

Partner:

Ducks Unlimited Canada

Discipline:

Other

Sector:

University:

British Columbia Institute of Technology

Program:

Accelerate

Evaluation of Machine Learning Methods for Portfolio Replication of VIX Futures

During the past two decades, the CBOE Volatility Index (VIX® Index), a key measure of investor sentiment and 30-day future volatility expectations, has generated much investor attention because of its unique and powerful features. The introduction of VIX futures in 2004, VIX options in 2006, and other volatility-related trading instruments provided traders and investors access to exchange-traded vehicles for taking long and short exposures to expected S&P 500 Index volatility for a particular time frame. Certain VIX-related tradable products may provide benefits when used as tools for tail-risk hedging, diversification, risk management, or alpha generation. However, all such VIX relevant derivatives simply do not react quickly enough to movements in the spot VIX, which leads to a non-effective hedging performance. On the other hand, there are many other derivatives that can help us to reduce the volatility risk. For example, Peter Carr shows us a promising result using the SPX option only to forecast VIX index by some modern approaches, such as Machine Learning. In this project, we will look at different methods to extend Peter Carr’s work, and their comparative effectiveness in using a combination of SPX options to predict VIX futures.

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Faculty Supervisor:

Matheus Grasselli

Student:

Jieyi Zhu

Partner:

QTS Capital Management LLC.

Discipline:

Statistics / Actuarial sciences

Sector:

Finance, insurance and business

University:

McMaster University

Program:

Accelerate

Effects of plant mix, restoration year, and management regime of urban meadows on plant-pollinator network size, structure, and diversity

The purpose of this project is to identify bees and evaluate plant-pollinator networks based on the biomonitoring surveys conducted at the Meadoway in 2020-2021 with the Toronto and Region Conservation Authority (TRCA). The aim of these surveys is to develop a baseline understanding of bee diversity in The Meadoway and evaluate the effects of plant mix, restoration age, and management regime to improve TRCA best practices for future projects. The intern will conduct timed bee surveys at the Meadoway at sites 1-5 years post restoration and on specific flowers. Bees will be identified to species level and used to develop a synoptic collection for the Meadoway. The plant-pollinator network properties will allow the intern to rank plants present in the Meadoway based on attractiveness and value to wild bees. This information will be available to TRCA for their ongoing projects and management practices that target biodiversity conservation in public spaces.

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Faculty Supervisor:

J. Scott MacIvor

Student:

Sisley Irwin

Partner:

Toronto and Region Conservation Authority

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Large Data Visualization in Real Time

A successful computer application can easily have millions of users, but handling the network traffic generated by millions of users is not easy. The server system has to be well designed in order to properly process large, concurrent, and distributed data streams without affecting user experience. In addition, users do not generate data constantly, they often put a burst of load on the network instead. Therefore, the server system needs to be scalable as well. This research project is to find a technique or combination of techniques that makes the server system scalable and capable of handling large scale, highly concurrent, and distributed data streams in order to improve user experience.

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Faculty Supervisor:

Nick Koudas

Student:

Linzhi Feng

Partner:

TimePlay Inc

Discipline:

Computer science

Sector:

Other

University:

University of Toronto

Program:

Accelerate

Development of an innovative portable running analysis toolbox

Studying a person’s running biomechanics has been limited to a laboratory setting due to the complex, expensive equipment needed to capture their motion and forces. Recent developments in wearable technologies may allow these measurements to be captured outside of the lab, which is not only a cost effective alternative, but may allow for the collection of data in a more “natural” environment. While these wearable sensors may represent the future for assessing a person’s running pattern, they need to be compared with the current in-lab, gold-standard approaches to ensure they are valid. In this project, we will collect data on eighty recreational runners in both lab-based and real-world settings using novel wearable technology combined with the gold-standard motion capture and force plate data collection. We will use state-of-the-art machine learning approaches to process the wearable sensor data and compare it with the lab-based measures. This research will be the first of its kind to develop a portable, wearable, minimally-intrusive analysis “toolbox” to assess a person’s running biomechanics without the traditional constraints of an indoor lab.

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Faculty Supervisor:

Michael Asmussen

Student:

Colin Robert Firminger

Partner:

Canadian Sport Institute Calgary

Discipline:

Biology

Sector:

University:

Mount Royal University

Program:

Elevate

Perioperative Opioid Usage Quality Improvement [CDTS-PDF1] – Year two

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system. Such a system could risk-stratify children and adults before surgery, so that pre-habilitation and optimized analgesic combinations can be employed to reduce persistent post-procedural pain. Artificial intelligence-augmented systems will also give clinicians actionable feedback on their practice, so they can learn how to improve their care, reduce their patients’ risk further, and
help them to recover more quickly from their procedure.
Postdoctoral fellows will lead day-to-day project activities and spend significant time working with both our clinical sites (St. Paul’s Hospital and BC Children’s Hospital) as well as industry partners (Careteam and Xerus) who will benefit from their methods expertise, ability to collaborate with clinicians and academic researchers, design, implementation, and evaluation skills.

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Faculty Supervisor:

Matthias Görges

Student:

Michael David Wood

Partner:

Careteam Technologies Inc

Discipline:

Pharmacy / Pharmacology

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

Elevate

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