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

Development of a UV-LED based surface disinfection system

Respiratory droplets of pathogens, such as SARS-CoV-2 in the current COVID-19 pandemic, spread not only from person to person via direct contact, but also indirectly via contaminated frequently touched surfaces. Ultraviolet (UV) radiation is known as the gold standard of disinfection technology, where the DNA of microorganism are damaged by high energy UV photons. The traditional method to produce UV radiation is using medium-pressure or low-pressure mercury lamps, which are bulky, high energy consuming, and not environmentally friendly. An emerging method to produce UV rays is based on semiconductors which is the method utilized in ultraviolet light-emitting diodes (UV-LEDs). These new sources of radiation have a smaller footprint and instant on-off capability, which make them suitable to be used in many disinfection applications. The goal of this project is to develop an unprecedented UV-LED based disinfection device which can be utilized for the disinfection of various frequently touched surfaces, such as doorknobs and door handles, as one of the most common sources for virus transmission through surface. The system developed in this work can be installed on most of the surfaces to kill harmful pathogens, such as SARS-CoV-2.

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Faculty Supervisor:

Fariborz Taghipour;Charles Haynes

Student:

Seyyed Arman Hejazi

Partner:

Acuva Technologies Inc

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of British Columbia

Program:

Accelerate

Computer-Aided Detection of Non-Alcoholic Fatty Liver Disease (NAFLD), Steatosis and NASH, using Raw Signals from Point-of-Care Ultrasound and Deep Learning

Fatty Liver Disease affects approximately 20% of the Canadian population [1]. Furthermore, 4% of Canadians have developed serious inflammation and damage as a result of fat build-up in the liver [2]. This can quickly progress causing liver scarring and cancer [2]. Fatty liver disease requires early diagnosis for effective treatment to be implemented but unfortunately, there are no easily recognizable symptoms. There are high costs and complicated workflows associated with current diagnostic techniques. Alternatively, there is promising evidence which suggests that simple ultrasounds can be used for tissue characterization [3-6]. The focus of this research is to utilize machine learning algorithms and ultrasound data to diagnose liver disease in its early stages. Oncoustics has an ultrasound database that can be used for the proposed research and is capable of leveraging the software into a marketable ultrasound solution. Such technology would allow for early diagnosis though simple, affordable and accessible screening.

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Faculty Supervisor:

Eran Ukwatta;Mamatha Bhat

Student:

Miriam Naim Ibrahim

Partner:

Oncoustics

Discipline:

Engineering

Sector:

Other

University:

Program:

Engineered genetic traceability solution for commercerical ale yeasts and methodology for rapid dectection and identification of diastatic yeast contamination in beer fermentation

This project will demonstrate that one or more unique DNA ID sequences (“DUID”) can be inserted into the genomes of select strains of Saccharomyces cerevisiae ale yeast and S. cerevisiae var diastaticus yeast strains without affecting the heritable traits of the host and then the DUID can be recalled upstream in the brewing process. By demonstrating the utility of the DUID for batch-level rapid detection and identification to address existing commercial challenges experienced by beer producers, we will use the data collected to expand our offering into other food system organisms (e.g. Romaine lettuce, grains, etc.). Furthermore, the results of this project will be leveraged for other use cases e.g. Introduction of trace amounts in animal feed to provide genetic traceability. The data acquired from this trial will allow for the identification of process efficiencies and design of our digital infrastructure in preparation for commercialization.

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Faculty Supervisor:

George van der Merwe

Student:

Hollie Rowlands

Partner:

Discipline:

Biochemistry / Molecular biology

Sector:

Manufacturing

University:

University of Guelph

Program:

Accelerate

Enhanced carbon capture in manipulated mine tailings

This project will study the effects of CO2 sequestration in mine waste tailings using a robotic mixing system. Mine waste tailings represent a large opportunity for carbon storage, assisting mining companies with goals to improve their carbon footprint. Robotic mixing of the surface of tailings is expected to accelerate carbon storage and mixing and measurement systems will be tested.

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Faculty Supervisor:

Gregory Dipple

Student:

Frances Jones

Partner:

Copperstone Techno

Discipline:

Geography / Geology / Earth science

Sector:

Manufacturing

University:

University of British Columbia

Program:

Accelerate

AI powered mobile application to detect plagiocephaly and craniosynostosis in infants

Technology can be a valuable tool to help physicians improve the care they provide for their patients. We set out to determine if an AI powered mobile application could help primary care physicians detect clinically significant positional plagiocephaly and/or craniosynostosis during regular well-baby visits. The intern will directly help in planning, conduction, and statistically analyze the performance of an AI software in addition to gaming hands on experience conducting a clinical pilot study. The partner organization in return will benefit by further validating the accuracy, sensitivity, and specificity of their AI software while also generating data to further improve it.

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Faculty Supervisor:

Mirko Gilardino

Student:

Ayden Watt

Partner:

Little Angel Medical

Discipline:

Other

Sector:

Health care and social assistance

University:

McGill University

Program:

Accelerate

Topologies and Linearization of High Peak-to-Average Power Amplifiers for Digital Broadcast Radio Applications

Broadcast radio is changing from an analog medium based on frequency modulation (FM) to a full digital broadcast based on orthogonal frequency division multiplexing (OFDM). The high peak-to-average power ratio of the OFDM waveform requires different power amplifier topologies and a high degree of linearity. The research in this project analyzes current amplifier performance for digital radio broadcasting in the FM band, investigates new linearization techniques and explores new amplifier topologies. Key research aspects are improving linearity to meet spectral emissions requirements and increasing power added efficiency (PAE) for amplifiers broadcasting a hybrid waveform composed of both an FM and OFDM component that is increasing in injected power with the goal of an all digital OFDM waveform.

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Faculty Supervisor:

Jean-Francois Bousquet

Student:

Ibrahim Fatungase

Partner:

Nautel Limited

Discipline:

Engineering - computer / electrical

Sector:

University:

Dalhousie University

Program:

Accelerate

Pilot Plant for Lithium Extraction from Saskatchewan Brine Deposits

With the growth in demand for electric vehicles and mobile devices powered by rechargeable lithium batteries, demand for lithium is expected to increase by over 200% in the next decade. Current lithium production comes primarily from Australia, South America and China. There are significant lithium reserves in the same Saskatchewan aquifers currently being exploited for their concomitant oil reserves. Although the lithium concentration in these aquifers is lower than in brines being mined elsewhere, new lithium selective extraction technologies show great promise for making extraction of lithium from these aquifers economical. Prairie Lithium has previously identified a lithium selective ion exchange material that can extract more than 99% of the lithium in a brine sample in only 4 minutes. The project described here involves the modification, deployment, and optimization of a commercial pilot unit to demonstrate the viability of using this extraction methodology to develop the first lithium brine mine in Saskatchewan using produced water from oil and gas production.

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Faculty Supervisor:

Shafiq Alam

Student:

Valan Namq;Mohamed Ayman Mohamed Aly Abdallah

Partner:

Prairie Lithium Inc.

Discipline:

Engineering - chemical / biological

Sector:

University:

University of Saskatchewan

Program:

Accelerate

Responsive polymer-based sensing system for COVID-19 infection

Monitoring hormone levels in saliva can be used to assess female reproductive health, which can yield many benefits to individuals. For example, those that have fertility issues can use hormone levels in saliva to improve their chances of conception, while the monitoring hormone levels over time could also be used to track and help treat disease. The project proposed here will yield a simple, and inexpensive tool that can be used at home (not in a clinic) to allow one to monitor hormone levels in saliva over time, e.g., daily. The development of this technology will provide a unique experience for the interns as it is at the intersection of technology development and human health.

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Faculty Supervisor:

Michael Serpe

Student:

Nicholas Balasuriya;Krista Fruehauf

Partner:

Eli Science Inc

Discipline:

Chemistry

Sector:

Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

Building Standards for Online Voting: Safeguarding the Industry

This goal of this project is to develop a Standards Proposal and initial framework to guide the use of online voting in municipal elections in Ontario. Elections in municipalities in Ontario are among the most digital in the world, yet there are no guidelines to shepherd use of the technology. Working with our partners we will develop a Standards Proposal to co-create online voting standards with stakeholders (i.e., municipalities, vendors, local associations). The project will focus on Ontario as a case study to establish proof of concept with the eventual objective of building a national framework.

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Faculty Supervisor:

Nicole Goodman;Anna M. Agathangelou;Aleksander Essex

Student:

Adam Churchard

Partner:

Neuvote

Discipline:

Political science

Sector:

Information and cultural industries

University:

Program:

Accelerate

Towards an Elastic and Reliable Cloud Resource Management

This work is a holistic automatic methodology for cloud resource management system, which is a corner stone to build any cloud system. Cloud players rely on this to reduce management effort and cloud running cost, by enabling dynamic service access to cloud clients with cheapest price for customer, and high revenue for cloud providers. Customer requirements must be achieved based on their service level agreement like availability of the service. Now a days with new lifestyle conditions due to the pandemic (covid19), accessing online resources and performing tasks virtually increase the demands on cloud resources and services in different levels. These requirements must be dynamically handled by cloud management system, the way to provision resources keeping safe access to data, service availability and service performance under user expectations.

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Faculty Supervisor:

Anjali Agarwal

Student:

Mustafa Daraghmeh;Tariq Daradkeh;Mohammad Altahat;Yanal Alahmad

Partner:

Cistech Limited

Discipline:

Engineering - computer / electrical

Sector:

Other

University:

Concordia University

Program:

Accelerate

Integrated Optimal CLT Building Design Considering Energy Performance and Structural Performance

This research proposed a method to conduct optimal CLT building design, which has minimum CLT usage and minimum operating energy consumption. This is a multidisciplinary research pushing the boundary of current definition of optimal design for each disciplinary to another level. With the developing of Building information modeling and automized simulation-optimization technology, the design of building will evolve to an interdisciplinary design in this decade, and this research demonstrate the benefit and application of integrated design. This research will also be the first research applied structural optimization to CLT design in Canada. Demonstrating the outcomes of proposed methodology, the partner organization can establish its position in the industry.

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Faculty Supervisor:

Bruno Lee

Student:

Yin Li

Partner:

CWT Consultants

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Concordia University

Program:

Accelerate

Small molecule agonists of SHIP1 for treatment of inflammatory disease

Activation of the immune system is necessary for defense against pathogens and injury, but just as important are the processes to turn this inflammatory response once the infection or injury has been resolved. Inappropriate prolongation of immune cell activation results in inflammatory diseases such as inflammatory bowel disease, asthma and arthritis. The University of British Columbia (UBC) partners in this project have previously shown that activating the intrinsic braking system in cells, a protein called SHIP1, using small molecule compounds can reverse inflammation. We propose to optimize the chemical and biological property of these compounds so that they can be tested in humans for treatment of inflammatory disease. ZebraPeutics Inc has license these compounds from UBC to support their development and subsequent testing in human clinical trials. The work proposed in this application will support this goal.

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Faculty Supervisor:

Raymond Andersen;Alice Mui

Student:

Santhi Jampani;Benjamin Yeremy;Jeff Yoon

Partner:

ZebraPeutics Inc

Discipline:

Biochemistry / Molecular biology

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

Accelerate

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