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

Intelligent Vision Based Navigation Systems

Utilizing geomatics sensors such as laser scanners, GNSS, Inertial Navigation Systems (INS), and photogrammetry cameras to provide mobile mapping solutions has been studied and utilized extensively in the past three decades. The data fusion between high-end mobile mapping systems such as laser scanning and imagery-based systems, and low-cost camera systems are still a fertile field in digital transformation. The anticipated outcome of this project is a software development kit (SDK) that enables data fusion between high-end mobile mapping systems and low-cost camera systems. This SDK will provide multidimensional digital infrastructure information for use in vision-based navigation (VBN) systems. The research could have significant impacts on the fields of LCMM, VBN for indoor navigation/mapping, and self-driving car navigation.

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Faculty Supervisor:

Aboelmagd Noureldin

Student:

Hany Ragab

Partner:

Micro Engineering Tech Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Queen's University

Program:

Accelerate

Use of XR to address coordination challenges in construction projects

Building design is a complex and iterative process that requires collaboration between designers from numerous disciplines. Quality of design has a direct impact on the project success and poor-quality designs are the leading cause of project delays, reworks, and cost overruns. This research aims to improve the quality of design by focussing on two themes: addressing the design coordination issues faced and getting design inputs related to constructability and maintainability from relevant end-users. For this aim, the use of modern technologies such as Virtual Reality (VR) and Augmented Reality (AR) which are together denoted as Extended Reality (XR), with their potentials for providing stronger spatial understanding, will be explored. The research investigates the impact of using VR and AR tools to improve the design quality and measures its potential benefits. TO BE CONT’D

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Faculty Supervisor:

Sheryl Staub-French

Student:

Devarsh Bhonde

Partner:

EllisDon

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Program:

Accelerate

A Deep Learning Approach to Soft Sensor Design and Process Optimization for an Industrial Nickel Extraction Process

The objective of this project is to use artificial intelligence (AI) approaches to solve complex industrial problems. The two biggest advantages of AI-based approaches are the ability to continuously learn and also learn adequately from historical data. Traditionally, many process information are unmeasurable during live operations because of instrumentation limitations. Also, plants are not sufficiently optimized to maximize production quality, while minimizing waste. Using AI-based approaches, we can develop complex non-linear models from historical to predict the unmeasurable process information. The models are also continuously learning from the new data coming into the plant. To optimize the process operations, another family of AI algorithms called reinforcement learning will be used. These algorithms will learn the whole process, including what happens when each process variable is changed. With this knowledge, reinforcement learning can then provide the optimal sets of inputs to maximize the plant productivity, while minimizing its waste.

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Faculty Supervisor:

Jinfeng Liu

Student:

Rui Nian

Partner:

NTwist

Discipline:

Engineering - chemical / biological

Sector:

Energy

University:

Program:

Accelerate

The Impact of Knowledge Transfer in International Business on Early Childhood Education

This research focuses on three substantive areas (1) curriculum and instruction in early childhood education, (2) international relationships and partnerships in international business and (3) business management in knowledge transfers related to the challenges and possibilities of how early childhood education engages the various national settings in the global context. This study will identify the tensions between the goals of Canadian and Chinese partners. These tensions will be explored using a specific Canadian curriculum applied to a Chinese kindergarten. The intent of the research is threefold: (1) is to aid in the development of international business opportunities, as well as nurture management relationships in the early childhood education industry; (2) to help both international scholars and practitioners understand how certain cultural aspects and economic characteristics with classroom applications can be found in both Canada and China.

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Faculty Supervisor:

Mary Bernard

Student:

Liton Furukawa

Partner:

Zhejiang University of Technology

Discipline:

Business

Sector:

Finance, insurance and business

University:

Royal Roads University

Program:

Accelerate

ParticipACTION Physical Activity Report Card for Children and Youth and the Global Matrix 3.0: Evaluation and Strategic Harmonization

Global levels of childhood physical activity are declining while sedentary behaviours are rising, leading to the global increase in non-communicable disease. The aim of this project is two-fold: 1. to contribute to childhood physical activity promotion in Canada and worldwide, and 2. to contribute to the international diffusion of the scientific knowledge concerning childhood physical activity. This will be achieved via the optimization of the development of the Global Matrix 3.0; the evaluation of the Global Matrix 3.0; and the amplification of findings from the 2018 ParticipACTION Report Card on Physical Activity for Children and Youth. This internship is in direct accordance with the overreaching goal of ParticipACTION, a non-profit organization, which aims to promote healthy active living among Canadians. 

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Faculty Supervisor:

Mark Tremblay

Student:

Salomé Aubert

Partner:

ParticipACTION

Discipline:

Epidemiology / Public health and policy

Sector:

Medical devices

University:

University of Ottawa

Program:

Accelerate

Climate change, wildlife harvest, and traditional food security in northern Quebec

The wild food system of northern Quebec is a critical natural resource, health resource, and cultural resource of the people of Eeyou Istchee and Nunavik, which has and will be impacted by climate change in many, diverse ways. The research proposed here seeks to identify the likely climate change impacts on key wild food species as well as the adaptation strategies that enable the maintenance of traditional food security in changing environments.

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Faculty Supervisor:

Murray Humphries

Student:

Nathan Badry

Partner:

Ouranos Inc

Discipline:

Resources and environmental management

Sector:

Aboriginal affairs

University:

McGill University

Program:

Accelerate

Modeling regime changes to improve portfolio diversification and performance

Asset allocation – the decision of how to divide a portfolio among the major asset classes such as cash, stocks and bonds – is a key determinant of portfolio performance. Because financial markets go through periods of strong and weak economies, the performance of an asset class varies with shifting economic conditions. These regime shifts pose a challenge to the asset allocation decision because they impact the portfolio’s return and risk. The objective of this research project is to develop efficient statistical algorithms to identify, model and forecast market regimes and the main drivers that impact the performance of an investment portfolio. Based on these algorithms, a strategy is developed to modify the asset allocation when changes in financial and economic conditions are detected. This investment strategy is expected to provide better long-term results when compared to more static approaches.

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Faculty Supervisor:

Maciej Augustyniak

Student:

Kassimou Abdoul Haki Maoude

Partner:

Caisse de dépôt et placement du Québec

Discipline:

Mathematics

Sector:

Finance, insurance and business

University:

Université de Montréal

Program:

Accelerate

NOVA (Network Optimized Video Analytics)

Project NOVA will build on the University of Ottawa and Ciena’s advanced analytics capabilities to allow networks around the world to understand where video flows run over their network.  This will allow the network operators to improve video Qualify of Experience for their end customers, more quickly and cost effectively fix video impacting network problems, plan their networks to better support video, and provide greater customer service awareness of end customer over the top video quality. Ciena anticipates this capability will propel it into be the world leader in network video analytics with a growing employee base to support this significant business and associated research initiatives to evolve and expand its capability within this market and in to adjacent markets.

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Faculty Supervisor:

Shervin Shirmohammadi

Student:

Hossein Ebrahimi Dinaki

Partner:

Ciena Corp.

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Ottawa

Program:

Accelerate

Elaboration of a Phase II clinical study protocol for the treatment of metastatic non-small cell lung cancer (NSCLC) using AB-16B5, an epithelial to mesenchymal transition (EMT) inhibitor, in combination with docetaxel

The molecular mechanisms responsible for the occurrence of metastatic cancer are beginning to be elucidated with the identification of key regulators. Increasing evidence points to tumor cell epithelial to mesenchymal transition (EMT) as an important contributing process to metastatic evolution. The identification of factors that are stimulated during EMT might provide the means to develop new drugs required to increase the effectiveness of current regimens and improve patient outcome. Alethia Biotherapeutics is developing its AB-16B5, a humanized monoclonal antibody that targets secreted clusterin, a protein that is stimulated during EMT and contributes to invasion of tumors cells. The treatment with a true inhibitor of EMT is predicted to increase the effectiveness of current therapy and decrease metastasis, which should result in improved patient survival. Alethia Biotherapeutics has recently completed a first-in-human Phase I study with AB-16B5 in patients with advanced carcinomas. The primary objective of the proposed project is to elaborate a Phase II clinical trial protocol to test the hypothesis that treatment with AB-16B5 in combination with docetaxel, a cytotoxic agent, will result in an increased response rate.

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Faculty Supervisor:

Grégoire Leclair

Student:

Elisabeth Viau

Partner:

Alethia Biotherapeutics Inc

Discipline:

Pharmacy / Pharmacology

Sector:

Pharmaceuticals

University:

Université de Montréal

Program:

Accelerate

Characterization of back-illuminated complimentary metal-oxide semiconductor detector arrays for CASTOR

We seek to test the behaviour of candidate detectors for the proposed CASTOR space telescope. We are focused on the response to dim images, the behaviour when resetting portions of an image during exposure, and the behaviour when using multiple reads throughout an exposure to reduce the effect of random noise generated when reading the detector. We will do this by performing these readouts on the detectors when they are illuminated by a known light source under laboratory conditions in a cold vacuum chamber.

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Faculty Supervisor:

Patrick Côté

Student:

Robert Gleisinger

Partner:

Honeywell International

Discipline:

Physics / Astronomy

Sector:

Information and communications technologies

University:

University of Victoria

Program:

Accelerate

Marine Additive Manufacturing Centre of Excellence

The proposed NBIF RIF project will establish a UNB Marine Additive Manufacturing Centre of Excellence (MAMCE) in Atlantic Canada. The focus of the centre is the marine and defence sectors with vision for global marine technology trend for 2030, which includes additive manufacturing, and advanced materials. MAMCE’s mission is to accelerate the adoption of metal additive manufacturing (AM) technology in the Atlantic Region, mainly New Brunswick, through research, workforce training, and commercialization. As a capacity building project, the MAMCE will bring infrastructure, expertise and knowhow to the Atlantic region. One of the key challenges facing AM adoption is knowledge and expertise. The establishment of the MAMCE and related research activities will build a strong foundation for manufacturers in the Atlantic region to exploit the benefits of additive manufacturing. The technology is already disrupting the traditional manufacturing paradigm, and regional companies will have the opportunity to be leaders in the field.

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Faculty Supervisor:

Mohsen Mohammadi

Student:

Ramin Shamsdini

Partner:

Lockheed Martin Canada

Discipline:

Engineering - mechanical

Sector:

Advanced manufacturing

University:

Program:

Accelerate

Improving Human-centric Facility Management through Machine Learning Analysis and Visualization

Buildings represent up to 40% of primary energy consumption. To optimize that energy cost vs. the comfort of its occupants, Facility Management (FM) relies on data from sensors, and on automation, to increase efficiency. The majority of existing buildings however have limited automation, so it is up to Facility Managers to interpret and act upon the information resulting from the various building sensors. This is often difficult without the appropriate contextual information to guide and support decisions. This project aims at addressing this issue by using Machine Learning methods applied to FM data, and make the results more explicit for human users, by providing better informational context as well as the development and application of new data visualization techniques, and improve Facility Managers’ decision-making.

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Faculty Supervisor:

Fred Popowich

Student:

Shanghao Chen

Partner:

CopperTree Analytics

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

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