Innovative Projects Realized

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

29670 Completed Projects

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801
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663
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8841
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95
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568
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1088
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Projects by Category

Continuous production of high quality carbon nanopearls

Carbon nanopearls are an exciting novel class of materials that present unique characteristics, and they turn out to be an excellent alternative to carbon nanotubes for different applications. Presently, they are experimented with success as material for cold cathodes for electron-beam based instrumentation applications and they can be used for the development of polymer nanocomposites with specific properties. We plan to develop a new chemical vapor deposition reactor with a mechanism for allowing a prolongation of the nanocatalyst lifetime that can favour the material growth process. A new fabrication process based on optimization of factors such as temperature, gas fluxes and substrate rotation speed will be determined in order to obtain the highest throughput for a continuous production

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Faculty Supervisor:

Truong Vo-Van

Student:

Partner:

Nanomed

Discipline:

Engineering

Sector:

Manufacturing

University:

Concordia University

Program:

Accelerate

Intelligent Agent Based Computing for Auditing Financial Market Transactions

Citco provides financial products and services to hedge funds, private equity and real estate firms, investors, institutional banks, Global 1000 companies, and high net worth individuals in the Netherlands and internationally. The proposed research is focused on optimizing operations by automating trade resolution and reducing risk using machine learning. Outlier detection algorithms will be proposed to improve the accuracy of existing mismatch detection procedures. Unsupervised and supervised machine learning will be used to further improve this capability. The research will also look at improving data visualization and user interface for efficient monitoring of trade mismatch. Further, we will explore use of text mining for automated resolution of trades based on e-mails exchanged between those involved in a trade. The endeavor will significantly improve the data analytics capabilities of Citco and will potentially result in an increased operational footprint in Atlantic Canada.

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Faculty Supervisor:

Pawan Lingras

Student:

Partner:

Citco (Halifax)

Discipline:

Computer science

Sector:

Administrative and support, waste management and remediation services; Finance and Insurance

University:

Saint Mary's University

Program:

Accelerate

Proximity Music System

Video games are highly interactive experience. With modern approaches to game design it becomes impossible to anticipate all the situations a player can ended up in. Building up on research regarding generative music systems at the Metacreation Lab for Creative AI, PhD student Cale Plutt will research, design and implement a generative music system tailored to Inscape VR game. In particular, the music generation will respond to affective state of the games in terms of their valence, arousal and tension.

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Faculty Supervisor:

Philippe Pasquier

Student:

Partner:

Inscape Studios

Discipline:

Sociology

Sector:

Information and cultural industries

University:

Simon Fraser University

Program:

Accelerate

Automated Fatty Liver Diagnosis

Up to 30% of the population has a Fatty Liver Disease (FLD, a condition in which fat builds up in your liver). Non-invasive ultrasound assessment of this liver condition is an increasing demand in healthcare service due to its high risks leads to advanced liver diseases. However, an ultrasound-based examination has made the manual inspection a lengthy and tedious task and observer dependent. The proposed research aims at a computer-aided liver ultrasound assessment software toolkit facilitating the diagnosis of FLD. In particular, this proposal will design computational methods, such as machine learning and recent deep learning, to automatically extract related features in ultrasound data, and to detect and grade the levels of FLD. This project is a pioneering attempt. In both industry and academia, there is limited prior work. It will provide a strategic base towards a full automatic liver ultrasound diagnosis system for the partner organization.

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Faculty Supervisor:

Shuo Li

Student:

Partner:

MEDO DX

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Technology; Information and Communications Technology

University:

Western University

Program:

Accelerate

Estimating Battery Key Performance Indicators and Forecasting Battery State-of-Health Using Machine Learning and Neural Networks Techniques

SOTI Inc. is a Canadian company providing control and management for mobile devices. Insight Agent is a product made by SOTI to help collect various battery specifications such as battery level, voltage, current and other metrics from mobile devices. This research project aims to use a machine learning and neural networks framework to predict the state-of-health for batteries in mobile devices. The intern will use the metrics collected by SOTI Insight Agent to derive formulas to calculate the key performance indicators (KPIs) of the battery system. Using the KPIs, the intern will explore all the feasible machine machine and neural networks algorithms to obtain a better understanding and prediction of batteries’ health conditions. This will help the Canadian customers minimize cost of device maintenance, as well as total cost of ownership while ensuring a minimal impact and loss to business productivity.

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Faculty Supervisor:

Murat Erdogdu

Student:

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Investigate sensors management and fusion algorithms to orchestrate data/information collection from different sensors (with various reliabilities) and in weather-challenging environments

The objective of the internship is to better evaluate/quantify the quality of sources in a challenging weather environment and adapt the behavior of the sensor-fusion algorithm accordingly. For example, if two cameras are mounted on the car, and one is obstructed (or partially obstructed) by snow, second camera should become more reliable in this condition.

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Faculty Supervisor:

Henry Leung

Student:

Partner:

Thales Canada Inc (Montreal, QC)

Discipline:

Computer science

Sector:

Information and Communications Technology; Transportation (excluding aerospace); Technology

University:

University of Calgary

Program:

Accelerate

Cannabis and Death-Anxiety

In partnership with True North Clinical Research, two studies are proposed to examine the moderating effect of using cannabis on anxiety in response to death-thoughts. In Study 1, participants will be randomly assigned to consume cannabis either before or after thinking about death. Self-reported affect will be assessed to determine if cannabis helps reduce death-anxiety. Study 2 will examine several potential moderators (e.g., personality factors associated with sensitivity to rewards and punishments; investment in pro-cannabis beliefs and values) and mediators (e.g., reactive approach motivation; reduced threat sensitivity) of the relationship between cannabis and anxiety following death-contemplation. This research will help True North understand the potential benefit of prescribing cannabis for the clinical treatment of anxiety. More broadly, it may also contribute to a growing literature on the medicinal effects of cannabis, as well as the literature on how people cope with the awareness of death.

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Faculty Supervisor:

Joseph Hayes

Student:

Partner:

True North Clinical Research

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

Acadia University

Program:

Accelerate

Data-driven building simulation for thermal and electrical energy demand prediction by using deep machine learning algorithms, RNN and LSTM for energy management

Building energy consumption prediction is becoming increasingly vital for energy management, equipment efficiency improvement, cooperation between building energy and power grid, and so on. However, it is still hard work to obtain accurate prediction results because of the complexity of the building energy behavior and the frequent undulations in the energy demand. In the building energy consumption prediction, the existing historical data are usually used to construct the traditional machine learning models and the deep learning models. This project, will mainly focus on developing a deep learning algorithm using recurrent neural networks and LSTM to have a more efficient and accurate prediction of electrical and thermal demand based on the energy consumption data from buildings. I have been selected to do my thesis in Canada for developing my project by starting a collaboration between DataOptima.it and CIISE in Concordia University.

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Faculty Supervisor:

Jia Yuan Yu

Student:

Partner:

Politecnico di Milano

Discipline:

Engineering

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

The Leisure, Sport, And Recreation Labor Market In Alberta: History And Current Trends

The project looks to explore the trends and directions of the labor market in the recreation, sport, and leisure industry for the Province of Alberta. Within this 6-month project, a review of the current literature in the human resource area of the field will be undertaken along with look at the current and past trends of the labor market within the province. These activities will lead to two chapters written for the partner organization which will help guide their future policies and directions as it relates to both awareness and advocacy of the industry to the general public and the various key stakeholder groups throughout the province.

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Faculty Supervisor:

Brian Soebbing

Student:

Partner:

Alberta Recreation & Parks Association

Discipline:

Sociology

Sector:

Arts, entertainment and recreation

University:

University of Alberta

Program:

Accelerate

LGBTQI2S Seniors’ Safety in Public Services

This project will result in a national environmental scan on LGBTQI2S seniors’ safety in health care, social care and municipal public services. It aims to identify promising policies and practices as well as systemic and structural barriers. It will also include the experiences of LGBTQI2S workers who serve seniors, a largely unexplored area. Egale Canada Human Rights Trust (Egale) and the Canadian Union of Public Employees (CUPE) are national organizations with common interests and distinct positions from which to influence change. They have identified this environmental scan as an important step in mapping out challenges and opportunities for collaboration and member engagement in education and advocacy. The results will be shared in a discussion paper, a fact sheet and lists of non/government service providers and champions, offering resources to improve safety for LGBTQI2S seniors and workers across the country.

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Faculty Supervisor:

Susan Braedley

Student:

Partner:

Egale Canada Human Rights Trust

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

Carleton University

Program:

Accelerate

Assessing the impact of STEM programming on children and youth.

In the twenty-first century, coding literacy provides individuals with a host of useful skills and competencies as well as accompanying psychological benefits. Yet, at present, very few pedagogical models or curricula include coding literacy as a central focus. STEM interventions, often found in after-school care programs and summer camps, help address this gap by offering targeted programming aimed at developing these competencies in children and youth. The present project will help assess the benefits and effectiveness of one of these programs by investigating how an exposure to STEM programming impacts the grit levels of the children in grades 1 through 8. This study will also assess the program’s structure, and include interviews with program participants assessing their experience.

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Faculty Supervisor:

Carolyn FitzGerald;Julie Mueller

Student:

Partner:

Canada Learning Code

Discipline:

Sociology

Sector:

Education

University:

Wilfrid Laurier University

Program:

Accelerate

Experimental testing and characterization of a new wireless heart pump

Heart failure is a common cardiovascular disease that is becoming even more prevalent worldwide. The current gold standard treatment for end-stage heart failure is heart transplantation. However, heart transplant therapy is a limited option due to the available number of donors, thus heart pumps emerged to offer circulatory support to patients in the heart transplant waiting list. Although heart pumps’ therapy improves the quality of life and survival rate, a significant number of patients still suffer from blood trauma adverse events such as infections and blood flow-channel obstructions, leading to further surgical interventions.
Therefore, blood trauma remains an unmet challenge in the field of mechanical circulatory suport. The purpose of this study is to experimentally test and characterize through in-vitro test rig different heart pump configurations of a new design. The primary outcome of the project is to select an optimal design that could eventually provide a long-lasting and minimally invasive wireless solution for patients with heart failure. It is believed that in the future, heart failure treatment will rely heavily on improved cardiovascular technologies that provide the reuired physiological function with the least invaiveness while remaining cost-effective. TO BE CON’T

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Faculty Supervisor:

Renzo Cecere;Rosaire Mongrain

Student:

Partner:

Yale University

Discipline:

Life Sciences

Sector:

Education

University:

Research Institute of the McGill University Health Centre

Program:

Globalink Research Award

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