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

Democratizing data preparation for AI

Artificial Intelligence (AI) has attracted significant attention in both industry and academia recently. On one hand, people are feeling excited about seeing the breakthroughs that AI has made. On the other hand, they are also worried that these advanced AI technologies will only be mastered by a very small number of organizations in the future. Therefore, there is a strong need to democratize AI (i.e., make AI accessible for everyone).There are three kinds of resources that AI requires: Algorithm, Computation, and Data. In the past, signification efforts have been made to democratize Algorithm and Computation. In terms of Data, however, the progress is still very slow. Data scientists, who are considered as the hottest job in the 21st century, can spend 80% of their time on data preparation. In this project, we will develop innovative technologies and open-source software tools to fulfil the vision of democratizing data preparation for AI.

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Faculty Supervisor:

Jiannan Wang

Student:

Pei Wang

Partner:

Union Mobile Financial Technology Canada Corporation

Discipline:

Computer science

Sector:

Finance, insurance and business

University:

Simon Fraser University

Program:

Accelerate

Flight, energy, and traffic management systems for electric and hybrid aircraft

Leading aircraft manufacturers have gradually turned their attention to the development of all-electric prototype airplanes, some of which have been flown recently. Such is the case of the Airbus E-fan aircraft that in 2015 has crossed the English Channel, completing the 74 kilometer flight from Lydd, England to Calais, France, in about 37 minutes. With battery performance constantly improving, its advantage over kerosene fuel becomes more and more evident, especially in terms of being CO2 emission free. However, with limited battery capacity it is essential to incorporate a Flight Management System (FMS) in future all-electric and hybrid airplanes. This proposal will study an optimal control framework for FMS and energy management of all-electric and hybrid aircraft. The research will focus on developing algorithms that will be validated in simulation and also obtaining Pareto-optimal trade-off curves. 

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Faculty Supervisor:

Luis Rodrigues

Student:

Weihong Yuan

Partner:

Marinvent

Discipline:

Engineering - computer / electrical

Sector:

Aerospace and defense

University:

Concordia University

Program:

Accelerate

Wideband envelope detector for dynamic supply control in RFIC PA’s

Radio frequency integrated circuit power amplifiers (RFIC PAs) operating at microwave frequencies (e.g. 5 to 6 GHz) and at millimeter-wave (mm-wave) frequencies (e.g. 60 GHz) are electronic components used in the front-end modules (close to the antenna) of mobile communication equipment such as cellular handsets. Envelope detectors constitute a critical component in a newly proposed dynamic biasing technique for RFIC PAs based on positive envelope feedback, for power efficiency improvement and distortion reduction. However, it requires a different type of detector from what has been proposed so far in the scientific literature, given the specific characteristics required for a positive envelope feedback embodiment. Hence Skyworks has identified the need to develop a new envelope detector for this purpose.
Therefore, this work will contribute to improve the competitiveness of Skyworks’ RFIC PA products, thereby contributing to this company’s economic success. 

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Faculty Supervisor:

Nicolas Constantin

Student:

Jean-Sébastien Dominique

Partner:

Skyworks Solutions Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

École de technologie supérieure

Program:

Accelerate

Carbon prepreg filaments for 3D printing high performance parts

There has been an extensive growth in additive manufacturing, 3D printing, over the past couple of years. At the moment, pure polymers are mainly used for manufacturing parts and they yield low strength and stiffness, not suitable for load-bearing products. The use of carbon fiber composites in 3D printing can significantly improve structural properties. Currently, there is no commercial 3D printing head capable of printing with carbon fiber prepreg filaments. A 3D printing head will be custom-built to accept these filaments and produce parts with high strength. If this project is successfully completed, Teijin Carbon can bring high performance materials to the 3D printing market. Canadian companies involved in 3D printing will benefit from this material and can manufacture structural parts to be used across wide range of industries. Aerospace, automotive, oil and gas are some examples.

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Faculty Supervisor:

Kazem Fayazbakhsh

Student:

Sadben Khan

Partner:

Teijin Carbon America Inc

Discipline:

Aerospace studies

Sector:

Advanced manufacturing

University:

Ryerson University

Program:

Accelerate

Time series clustering and classification

Financial indicators of an individual firm may be in the form of time series, vectors, or even richer data, such as text or images. The purpose of this work is to explore and develop methods for dealing with such data, and in particular perform the clustering/classification of such data into similar groups. In the project the intern will develop the tools that will allow to determine whether a client should be issued a loan or not.

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Faculty Supervisor:

Rafal Kulik

Student:

Youssouph Cissokho

Partner:

ZetaTango Technology Inc

Discipline:

Mathematics

Sector:

Finance, insurance and business

University:

University of Ottawa

Program:

Accelerate

Assessing statistical bias in credit markets, an application to SMEs

This research project aims to evaluate whether members of minority groups or women face higher barriers to access credit in the small and medium-sized enterprises credit market. The intern will analyze loan-level data provided by the business partner to evaluate whether these biases are detectable in the portfolio of SME loans of the business partner. Discrimination in credit allocation prevents efficient credit allocation, besides being demeaning for the individual subject to discrimination. Notably, the business partner is committed to providing fair access to credit to all its clients, independently from gender or minority membership. Unfortunately, biases may still influence the applicant screening methodology, due to the use of variables that are highly correlated with group characteristics. This research project aims thus to contribute to the effort of the business partner to insure that its clients face fair access to credit.

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Faculty Supervisor:

Valentina Galvani

Student:

Yuqing Wang

Partner:

ATB Financial

Discipline:

Economics

Sector:

Finance, insurance and business

University:

University of Alberta

Program:

Accelerate

Mobile Mesh Technology For Improved Connectivity In Canada

Lack of affordable, reliable access to the Internet in remote, rural, and Indigenous communities in Canada and internationally has led to a digital divide affecting billions. Left has developed its RightMesh technology, which lets nearby mobile devices connect without the Internet. Normally data flows from a phone, through Internet Service Providers (Telus, Shaw), to the cloud (Google, Amazon), and back to reach another person, despite being nearby. With the RightMesh network, data can flow from phone to phone to phone until it reaches the intended person. Research will be conducted to improve network performance; develop best practices and methods to support designing software for remote, rural, and Indigenous communities; implement engagement strategies encouraging participation in mesh based apps; and develop incentives fostering connection with the mesh network. Simulations and case studies in remote Inuit communities will support this research and help RightMesh expand to other locations worldwide.

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Faculty Supervisor:

Daniel Gillis

Student:

Nicolas Durish

Partner:

Left

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

Multi-level modeling methodologies for aircraft thermal architecture optimization – Year two

The proposed project will contribute to Bombardier’s research initiative “Virtual Aircraft” with the overall objective to improve modelling and simulation throughout the development process to enable innovation and reduce development risk to extensive design space exploration.
The objective of the project is to develop models of thermal aspects, traditionally investigated later in the design, when the aircraft architecture is already defined, to enable the development of an aircraft thermal architecture analysis and optimization. This can be used to assess the thermal capacity of a specific equipment zone as well as the passenger comfort in the cabin.
This is especially important for new technology integration such as more electrical systems within a condensed space and the use of composite materials for structures. Furthermore, a methodology will be developed to analyze thermal aspects for aircraft systems consistently throughout the development process (conceptual, preliminary, detailed design) by using a multi-level approach.

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Faculty Supervisor:

Susan Liscouet-Hanke

Student:

Florian Sanchez

Partner:

Bombardier Inc.

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

Program:

Elevate

The Development of an Improved Model for Start-up Accelerators

The goal of this study will be to develop a new and improved model for start-up accelerators. These accelerators can be defined as programs that help start-ups develop their business model and acquire capital such that they can grow and thrive in today’s business environment. To create the new model, start-ups that are part of the Masters in Technology Management and Entrepreneurship (MTME) program will be examined. This way, it will be possible to find which program characteristics have the greatest effect on start-ups and how they can be improved. Overall, this study will allow accelerators to be more efficient and produce a greater number of successful businesses.

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Faculty Supervisor:

Dhirendra Shukla

Student:

Samuel Poirier

Partner:

New Brunswick Innovation Foundation

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Program:

Accelerate

Investigation of mechanical and electrical properties of polymeric nanocomposites under erosion

In the upstream pipelines, the application of the internal pipeline coatings with specialized polymer has been utilized to protect pipeline from corrosion and abrasive wears. The coatings are rearranged or re-lined when the coating wears out. However, there is no direct and continuous monitoring for the integrity of internal pipeline coatings. Thus the rearrangement or re-lining of the coating is performed pre-emptively before fully utilizing the coating. It is required to develop a novel technique, not only for the efficiency but also to prevent pipeline leakage. The proposed project will develop a system embedded inside the coating, changing its electrochemical properties upon damage. Various nanocomposite compositions will be tested, leading to the optimized sensor system. The proposed project gives ROSEN group advantages in the pipeline industry as they could extend the lifetime of coating and ensure the safety of pipeline.

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Faculty Supervisor:

Simon Park

Student:

Chaneel Park

Partner:

ROSEN IPS Canada

Discipline:

Engineering - mechanical

Sector:

Nanotechnologies

University:

Program:

Elevate

Blockchain-based Consent Management for Personalized Medicine

This multidisciplinary project will investigate the social, data, and technical issues surrounding design and implementation of a blockchain-based solution for the management of consent for the use of individuals’ “omics” data in medical research. Blockchains are distributed ledgers in which confirmed and validated blocks are organized in an append-only chain using cryptographic links. This project will study how blockchain technology can be used to provide users with greater control of, and reward for, the use of personal omics data, including genomics, proteomics, exposomics, phenomics, microbiomics and metabolomics, in medical research studies. It will also explore how the technical design of blockchain solutions may support privacy-preserving analysis of “omics” data with machine-learning. To achieve these research objectives, project team members will identify legal, regulatory and other requirements for the management of omics data and then use heuristic techniques and agile software development to implement a proof-of-concept blockchain solution that meets identified requirements for user consent of their omics data in studies to be run by the industry partner, Molecular You, as well as those to be run by its partners. “TO BE CONT’D”

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Faculty Supervisor:

Victoria Lemieux

Student:

Ravneet Kaur

Partner:

Molecular You Corporation

Discipline:

Library and museum studies

Sector:

Medical devices

University:

Program:

Accelerate

Identification of potential areas and associated benefits of MUT on the territory of the city of Montreal

The City of Montreal desires to evaluate the potential for the implementation of Multi-purpose Utility Tunnel (MUT) within its territory and to assess the overall benefits it could derive from it. This exercise would be initiated by a review of the state of the art to identify the criteria of choice and the associated benefits of developing MUT that have been used in the places around the world where MUT have been built. In a second step, we will work with the city to analyze the opportunity of building MUT by involving all the partners associated to the project. The result of this opportunity analysis will mainly be the creation of a multi-criteria grid that can be applied in future infrastructure projects to determine the locations where it would be appropriate to install MUT. TO BE CONT’D

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Faculty Supervisor:

Amin Hammad

Student:

Yisha Luo

Partner:

Centre d'expertise et de recherche en infrastructure urbaine

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

Program:

Accelerate

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