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

Design principles and clinical application of a wearable vibration device for individuals with proprioception deficiency

Sense of limb position will be defected or deteriorated as a result of injuries to the nervous system or aging. This project will address the design principles and application of a wearable sensory assistive device with the goals of improving the sense of limb position in elder adults or individuals with stroke. A prototype of the device will be designed and its effects on brain activity and movement performance will be explored on healthy adults. The results of the experimental part of this project will provide a proof-of-concept basis for future clinical trials using this novel assistive device on special populations.

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Faculty Supervisor:

Cheryl Glazebrook

Student:

Niyousha Mortaza

Partner:

10040910 MANITOBA INC

Discipline:

Kinesiology

Sector:

Life sciences

University:

University of Manitoba

Program:

Accelerate

Integration of Machine Learning with Distributed Temperature and Acoustic Sensing to Build Data-Driven Dynamic Reservoir Model

This project will develop practical workflows, algorithms and programming codes for inferring unknown reservoir properties from distributed temperature and acoustic sensing data. In-situ pressure and flow conditions can be interpreted from downhole fiber signals gathered in real time, which are used to estimate unknown heterogeneous reservoir parameters continuously. Machine learning methods will be incorporated to facilitate the handling of large amount of measured data and computations more efficiently. The project outcomes will help to advance the deployment of fiber-based instrumentation and optimize operations of inflow/outflow control devices for downhole monitoring and production diagnoses of oil and gas wells. One PhD student will be trained.

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Faculty Supervisor:

Juliana Leung

Student:

Hossein Izadi

Partner:

RGL Reservoir Management Inc.

Discipline:

Engineering - chemical / biological

Sector:

Mining and quarrying

University:

University of Alberta

Program:

Accelerate

Chipless RF Sensing for E-smart Composite Pipeline Integrity

Recent pipeline projects in Canada and the US have attracted lots of attention due to their importance for our future economy and environment. In the proposed project University of Alberta and Shawcor propose to work together towards developing E-smart pipelines and creating defect free system. We will utilize the vast amount of emerging and cutting-edge technical know-how in wireless technologies and apply that for the benefit of our energy and environmental sectors. Such information provides the opportunity to intelligently develop defect free pipeline. The project will create synergy between three of Canada’s strategic sectors of Environment, Information & Communication Technologies, and Energy. In addition, it will provide the opportunity for capacity building to highly qualified personnel to the advance the state-of-the-art high-tech systems, making them ready to join the industry, protect the environment and optimize usage of Canada’s natural resources.

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Faculty Supervisor:

Mojgan Daneshmand

Student:

Navid Hosseini;Sameir Deif;Morteza Lotfi Neyestanak;Zahra Abbasi

Partner:

Discipline:

Engineering - computer / electrical

Sector:

Oil and gas

University:

University of Alberta

Program:

Accelerate

Implementation of the Engagement Score of Libro Credit Union’s Owners

Libro Credit Union wants to improve the Owners’ (customers) financial experience engaging them actively through the institution’s initiatives. Therefore, Libro is dedicating efforts to objectively measure which initiatives have a greater impact on the owner’s engagement; so they can have better insights into their audiences and can ensure best-served owners with tailored initiatives. Our main goal is to create an Owner’s Engagement Score described by three dimensions: Services, Products, and Experiences to help Libro impact positively on the owner’s financial experience through initiatives designed to meet their individual needs. We will apply machine learning methods to evaluate the owner’s engagement indicator. Consequently, Libro will be able to prioritize their strategies and focalize their initiatives. Additionally, our solution will help Libro to determine a set of possible ways for their owners to transit along with Libro’s products, services and experiences with a positive impact on the owner’s needs and expectations.

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Faculty Supervisor:

Juan Luis Suarez

Student:

Antonio Jiménez Mavillard;Yadira Lizama;Daniel Varona Cordero;Ana Gabriela Ruiz Segarra

Partner:

Libro Credit Union

Discipline:

Cultural studies

Sector:

University:

Western University

Program:

Accelerate

Field testing of selected salt tolerant screened balsam poplar (Populus balsamifera) clones for use in reclamation around end-pit lakes associated with bitumen extraction in northern Alberta.

The fundamental challenge when reclaiming oil sands areas is to ensure not only survival, but vigorous growth of the plant material. Finding plants suitable for high salt conditions has offered the opportunity for Alberta-Pacific Forest Industries Inc. to investigate the potential role of using native balsam poplar (Populus balsamifera) as a key reclamation species for the oil sands region. The main objective of this research is to identify and select balsam poplar clones from Al-Pac’s PB1 (Alberta-Pacific Controlled Parentage Program Plan) for balsam poplar that are well adapted to potentially challenging sites at an oil sands reclamation mine site near Ft. McMurray, Alberta. This project will try to supply the energy sector with well adapted, native balsam poplar trees to be used in reclamation projects across the oil sands region, where appropriate, while meeting all regulatory requirements.

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Faculty Supervisor:

Barb Thomas

Student:

Yue Hu

Partner:

Alberta-Pacific Forest Industries Inc.

Discipline:

Resources and environmental management

Sector:

Forestry

University:

University of Alberta

Program:

Accelerate

An in vitro Platform of Antigen-Presenting Cells to Evaluate Critical Quality Attributes in Vaccine Formulations

Sanofi-Pasteur is developing new vaccine formulations that need to be evaluated on their efficacy and potency. Traditionally, the use of animal models to predict human immunity has been accepted as the best way to select vaccine formulations. However, animal models can be costly and time-prohibitive, and the assays employed to assess vaccine efficacy and potency are not ideal for rapid screening and optimization of multiple formulations. To overcome these limitations, we propose to test new vaccine formulations utilizing laboratory cultured macrophage cells. Vaccine interactions with macrophages ultimately determine the effectiveness of a given formulation.

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Faculty Supervisor:

Mauricio Terebiznik;Roberto J Botelho

Student:

Javier Roberto Jaldin-Fincati

Partner:

Sanofi Pasteur

Discipline:

Biology

Sector:

Pharmaceuticals

University:

Program:

Accelerate

Production of synthesis gas via Dry Reforming of Methane: Fundamentals and Applications

The aim of this proposed research is the development of an efficient technology to convert carbon dioxide (CO2) via Dry Reforming of Methane (DRM) to produce value-added products. DRM, one the promising CO2 utilization technologies, has gained much attention as not only it reduces greenhouse gases (GHG), but also converts them to a valuable product, syngas. There are two main knowledge gaps associated with DRM process, which hinders the industrial application: 1. Catalyst deactivation, and 2. The high energy requirement for the CO2 conversion reaction. This proposed research is designed to bridge these gaps by using novel catalysts to mitigate coke formation, followed by high-level heat recovery and plant-wide optimization. These innovations will ensure that the technology will advance towards commercialization. This study will allow us to meet major milestones required to reduce GHGs emissions and transition to a lower carbon economic system.

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Faculty Supervisor:

Nader Mahinpey

Student:

Sanaz Daneshmandjahromi;Rufan Zhou;Mansour Tijani;Amr Abdalla Ibrahim Abdalla;Garima Jain;Paulo Affonso Latoh de Souza;Felipe Gomes Camacho;Mohanned Mohamedali

Partner:

Canadian Natural Resources Ltd.

Discipline:

Engineering - chemical / biological

Sector:

Mining and quarrying

University:

University of Calgary

Program:

Accelerate

Microbial detection of hydrocarbon seeps offshore Nova Scotia

Offshore petroleum exploration requires a multitude of techniques to identify a petroleum system in an offshore area. Novel microbiology technologies which focus on the distribution of marine microbes (microbial biogeography) have been proposed as complementary tools to conventional techniques for oil and gas exploration. Hydrocarbon seepage from subsurface petroleum reservoirs is hypothesized to explain the transport of thermophilic bacterial endospores, i.e. “thermospores”, to cold seabed sediments. A microbial biogeography informed approach to identifying and quantifying petroleum reservoir derived thermospores in marine sediments could offer a strategy to locate reservoirs and improve the success of offshore oil and gas exploration. A data mining-based evaluation of published microbial community assessments of petroleum reservoirs will be used to determine the presence and abundance of thermophilic, endospore-forming bacteria. Prominent thermospores will be compared with those identified in heated incubations of marine sediments from hydrocarbon explorative areas. Analysis of genetic material will be used to evaluate the adaptations of thermophilic endospore-forming bacteria, in sediments overlying known petroleum reservoirs, that would permit growth in a petroleum reservoir, and survival during transport from the hot deep reservoir to cold surface sediments.

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Faculty Supervisor:

Casey Hubert

Student:

Daniel Gittins

Partner:

Offshore Energy Research Association of Nova Scotia

Discipline:

Biology

Sector:

Mining and quarrying

University:

University of Calgary

Program:

Accelerate

Understanding the contribution of ??-tetrahydrocanabinol and cannabidiol isomers and related compounds to the therapeutic effects and safety of cannabinoids using zebrafish larvae

Most of the medicines available today are either purified from plants or derived from compounds produced by plants. The Cannabis (marijuana) plant in particular produces an enormous variety of molecules that have valuable pharmaceutical potential – in addition to tetrahydrocannabinol (THC), which is the primary psychoactive molecule in the pant, the cannabis plant produces dozens of other molecules with poorly understood effects on animal cells. The variety of different molecules and the large number of possible combinations in which they may be present makes it challenging to test these compounds for potentially beneficial properties. Zebrafish share most of the molecular and cellular mechanisms that are affected by cannabinoids with humans. This project will use zebrafish larvae to try to find cannabinoids that have reduced behavioural effects while maintaining useful properties that will be valuable in treating diseases such as multiple sclerosis, epilepsy and cancer.

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Faculty Supervisor:

Bryan Crawford

Student:

Emily Moore

Partner:

Ethicann Pharmaceuticals Inc.

Discipline:

Biology

Sector:

Pharmaceuticals

University:

University of New Brunswick

Program:

Accelerate

OFDM radio receiver with Deep Learning

This project involves research in applied artificial intelligence in the field of communications. Using AI, complex building blocks in communication systems are to be simplified and designed in a highly cost-effective manner. The use of AI will allow communications systems become more cognitive in nature and give access to affordable software defined radios. This program would provide the means for the intern to innovate and execute a technology that would not have been possible otherwise. The technology developed and its direct commercialization impact will enrich the PhD research of the intern. Aarish Technologies is advancing in next generation AI processor on chip design. The advancement of an application in the field of AI based communication will help Aarish Technologies showcase its core AI processor technology. This will not only generate additional demand for its AI processors, but will also help develop a long-term strategy that will helps Aarish technologies remain in the forefront of innovation.

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Faculty Supervisor:

Ioannis Psaromiligkos

Student:

Pavel Sinha

Partner:

Aarish Technologies

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

McGill University

Program:

Accelerate

Machine Learning to Predict Temporomandibular Disorders Risk from Genotypes

The goal of this project is to develop new machine learning methods and computational strategies to mega-analyze data from well-characterized datasets on chronic pain conditions to develop a genetic predictive tool. This tool will be implemented in an online interactive dashboard and used by the Quebec Pain Research Network (QPRN) community. This collaboration with Plotly will make the developed machine learning models more accessible to applied researchers by: 1) visualizing the genetic effects which drive the predictions, 2) allowing users to interactively generate new predictions over a range of parameters and visually compare the outputs, and, 3) producing different graphics of the data to reveal details that might be hidden by summary statistics.

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Faculty Supervisor:

Sahir Bhatnagar

Student:

Kai Yang;Jesse Islam;Julien St-Pierre

Partner:

Plotly Inc

Discipline:

Epidemiology / Public health and policy

Sector:

Information and communications technologies

University:

McGill University

Program:

Accelerate

Learning non-local features for 3D reconstruction of buildings

The goal of this project is to help automate the process of scanning buildings with consumer digital cameras. Currently, fully automated scanning with a commercial camera produces inaccurate scans, while accurate scans require significant manual effort on each individual photograph (of which there are many) of the building to be scanned. We plan to use modern machine learning techniques to reduce the human labor required to create very accurate 3D scans of buildings. The partner organisation, Butterwick Projects Ltd., will use the solution we develop to scan buildings with poor insulation, then manufacture insulated panels offsite that attach to the outside of the old buildings’ walls and roofs. Since this will be done in a factory, it will be very efficient, and won’t significantly disturb the current occupants. This is also why high accuracy is important – the panels need to fit the building very accurately despite being built offsite.

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Faculty Supervisor:

Eleni Stroulia

Student:

Logan Gilmour

Partner:

Butterwick Projects Ltd.

Discipline:

Computer science

Sector:

Construction and infrastructure

University:

University of Alberta

Program:

Accelerate

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