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

Process and product development of NaquapureTM, a sustainable novel nanotechnology for the removal of heavy metals in industrial wastewater

NaquapureTM is a magnetic chitosan nanoparticle which removes heavy metals from wastewater using nanotechnology and a magnetic field to separate the nanoparticles with adsorbed heavy metals from the water. Although this technology has been shown to be effective there is missing information needed for NB-BM to finish product development. For instance, heavy metal removal using this technique has only been previously studied within the laboratory using distilled water. To ensure industrial success the intern will determine how other contaminants (i.e., organics, microorganisms and particulate matter) and environmental conditions (pH, temperature, ionic strength) will affect heavy metal removal. An industrial wastewater profile, developed by the intern, will be utilized to determine appropriate product modifications for a more efficient “personalized” water remediation product. The intern will then work with industrial partners to implement quality assurance standards and industrial application of the NaquapureTM product for heavy metal wastewater removal.

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Faculty Supervisor:

Huining Xiao

Student:

Kimberley Mary Clarke

Partner:

NB Biomatrix Inc.

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of New Brunswick

Program:

Elevate

Feasibility Evaluation Study of LifeguardMobile (designed for supported self-management of patients with chronic and complex conditions)

“Lifeguard Health Networks Inc. (LHN) has developed a secure Virtual Health Assistant application (app), to enhance supported self-management for patients with chronic and complex conditions, by leveraging their network of trusted family and friends, under the direction and guidance of health practitioners.We are conducting a study to evaluate the feasibility of the app and the level of user engagement with this form of supported self-management. This is a non-randomized, interventional study having both objective and self-reported outcome measures. A mixed method design will be used to collect data (in-depth interviews, group discussions, surveys, and analytics from the electronic tool) throughout the course of the study.Our hypothesis is that strengthening a patient’s social network will lead to better patient treatment adherence and better health outcomes at a lower cost to the healthcare system. The study will inform LHN of the app’s feasibility and level of adoption, and provide recommendations.”

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Faculty Supervisor:

Hannah Wong

Student:

Lora Appel

Partner:

Lifeguard Health Networks Inc.

Discipline:

Business

Sector:

Information and communications technologies

University:

York University

Program:

Elevate

Benchmarking and improving the energy efficiency of water distribution systems

Water and wastewater utilities typically represent the single largest municipal consumer of electricity. Previous studies have shown the potential to significantly reduce this use through infrastructure and operational improvements, particularly for water distribution. The proposed research seeks to validate and expand the application of energy metrics, developed by the applicant, that describe how energy is supplied, dissipated, lost, and delivered, throughout water distribution systems. Data collected from multiple water utilities, and findings from previous research conducted by HydraTek will be used to validate these metrics and build a more robust decision support tool. The performance of the systems will be compared and energy metrics benchmarked, allowing for the identification of best practices. The tool and reports developed will be available to HydraTek to extend the work in future consulting services. services.

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Faculty Supervisor:

Tamer El-Diraby

Student:

Rebecca Dziedzic

Partner:

HydraTek and Associates Inc.

Discipline:

Engineering - civil

Sector:

Environmental industry

University:

University of Toronto

Program:

Elevate

Development of Combined Building Integrated Photovoltaic/Thermal (BIPV/T) System for Net-Zero Energy Building Applications

“Building integrated photovoltaic–thermal array (BIPV/T) incorporated within a building structure is a system that combines the roof/facade, photovoltaic cells and thermal collector as an all-in-one product instead of installing each individually. BIPV/T effectively replaces conventional building materials and is more cost-effective than having several separate products, and installation of the BIPV/T system can be implemented during initial building construction. BIPV/T serves to not only produce electricity, but can also generate thermal energy, and act as protection against noise and the weather. With this in mind, BIPV/T functions as a new disruptive technology. This project will benefit the partner(s)’ understanding of BIPV/T benefits, challenges, and system design/installation improvements, which could potentially reduce costs, help advance commercial solar energy system and contribute to the economic benefits of Ontario and Canada.”

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Faculty Supervisor:

Alan Fung

Student:

Raghad Kamel

Partner:

Toronto and Region Conservation Authority

Discipline:

Engineering - mechanical

Sector:

Alternative energy

University:

Ryerson University

Program:

Elevate

Linking microbiome to eco-industrial function: the in silico and metagenomic exploration of microbial dark matter and taxonomic blind spots

“A large majority of microbes cannot be cultured. Recently, microbiome sequencing has begun to identify the genetic potential of these lineages, often referred to as microbial “dark matter”. By integrating my taxonomic profiling methods with function profiling developed by the academic supervisor, I aim to develop and apply a comprehensive pipeline for microbial dark matter characterization, placing unclassified taxa into both a taxonomic and functional context. This data intensive approach will characterize novel gene families, pathways, and taxa at an unprecedented scale.Poorly characterized data can severely blunt microbiome analysis, limiting its scientific and industrial utility. My role at Metagenom Bio will be to analyze client microbiome and metagenomic data for specific industrial applications. Development of taxonomic and metagenomic functional profiling methods that incorporate microbial dark matter leverage custom computational techniques, and will enable high-resolution characterization of proprietary Metagenom Bio metagenomic libraries, substantially increasing their value.”

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Faculty Supervisor:

Andrew Doxey

Student:

Michael Lynch

Partner:

Metagenom Bio Inc.

Discipline:

Biology

Sector:

Environmental industry

University:

University of Waterloo

Program:

Elevate

Social and Environmental Impact of Co-operatives

The intern will work with the project supervisors to develop an online tool to capture 15 key performance indicators (KPIs) that reflect social and environment performance of co-operatives in Canada. The intern will attend focus meeting with the supervisors in order to identify the co-operative participants’ requirements. The intern will complete a systems mock-up and detailed user requirements document that will be approved by CEARC. An online web-based system will be developed to gather submitted data, produce benchmarks and functionality to create on-demand reports. The Web-based tool is a key component of CEARC’s social and environmental reporting index project. While the tool will be designed to capture 15 KPIs for this project, it will have the capability to enable the CEARC systems administrator to add many other categories over time. This system will provide significant benefits for CEARC as a mechanism to identify and report KPIs that reflect a way array of co-operative performance elements.

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Faculty Supervisor:

Pawan Lingras

Student:

Gilroy Gordon

Partner:

Duguid Consulting

Discipline:

Computer science

Sector:

Education

University:

Saint Mary's University

Program:

Accelerate

Expanding the capabilities of a neurosurgery software platform to provide clinical solutions for advanced spinal cord imaging and intra-operative guidance

Pathologic changes that occur in the cervical spinal cord as a result of injury and disease are not well characterized with current clinical imaging techniques. Synaptive Medical has recently developed a suite of innovative medical imaging products focused on the brain and image-guided neurosurgery. They are interested in investigating the potential application of these technologies beyond the brain. Leveraging the expertise in spine imaging analysis, 3D visualization and surgical simulation at Sunnybrook Research Institute and the University of Toronto Spine Program, the objective of this project will be to use Synaptive’s magnetic resonance imaging (MRI) technologies to better characterize pathologic changes of the spinal cord and guide complex cervical spine interventions. For Synaptive, this represents an opportunity to extend use of their specialized imaging and navigation techniques into a new clinical area focused on the cervical spine.

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Faculty Supervisor:

Cari Whyne

Student:

Stewart McLachlin

Partner:

Synaptive Medical Inc.

Discipline:

Medicine

Sector:

Life sciences

University:

University of Toronto

Program:

Elevate

Modeling and Analytics for Big Data Applications

It has always been challenging to manage data at large-scale as there are no standards and best practices currently available for modeling and analysis of data. Currently available solutions rely on limited information and are confined to manual processing which makes the process of data handling and management slow, inefficient and hard. This makes modeling and analysis crucial to be able to track, monitor and manage applications that are complex, critical in nature and produce intensive data. In this research, the applicant will develop techniques, algorithms and tools for effective modeling and analysis of Big Data applications. These outcomes will help in automating the process of handling and management of large-scale data and make best use of formalism of data with analytics for the purposes of fault detection and prediction. Impact and usefulness of the proposed research will be demonstrated by applying it on real-life application from the industrial partner.

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Faculty Supervisor:

Hans-Arno Jacobsen

Student:

Omair Shafiq

Partner:

Digital Science Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto

Program:

Elevate

Collaborative BIM for Change Management in Architectural, Engineering & Construction (AEC) Industry

“In this project, a new digital platform will be created through which social interactions among the actors involved in the design & construction projects are detected and correlated to the IFC model of the facility. The created system will form the social network of actors involved in the process of design change, and also will semantically understand and archive the change instances in different phases of a project. By matching the two, the knowledge-base of the system will support the change management in BIM-based projects. Moreover, the system will perform a value-based analysis through the stored data to quantify and compare the benefits of BIM for change management in different projects.Creating the conceptual frameworks, as well as designing the system architecture, developing the platform, creating the analysis engine, data collection and processing in a set of pilot test projects will be the main components of this research project. “

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Faculty Supervisor:

Tamer El-Diraby

Student:

MAZDAK NIK BAKHT

Partner:

Turner Fleischer Architects

Discipline:

Engineering - civil

Sector:

Digital media

University:

University of Toronto

Program:

Elevate

User Centric Resource Management for Coordinated Multi-point, with Heterogeneous Back-haul Links

In the evolution of any industry, there are certain turning points which are crucial for the industry to be prepared for them, in advanced. Wireless sector is close to a number of turning points, from technological aspects, emerging operator’s business models, and customer’s diverse demands. From wireless technical point-of- view, in this proposal, we aim at devising novel algorithms/architecture to cover three significant research gaps, namely, lack of network-wide joint interference and quality-of-service (QoS) managements, lack of proper algorithms to realize the gains of coordinated multi-point (CoMP), and lack of accounting for heterogeneous back-haul links. We aim at designing autonomous RRM algorithms that can leverage the potential of CoMP, accounting for user’s experience, operator’s interests, and the interference limitations, in heterogeneous networks (HetNet)s. The results of this research will enable cheaper, faster, and more reliable wireless services, relevant to TELUS mobility, transitioning from 4G to 5G.

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Faculty Supervisor:

Raviraj Adve

Student:

Alireza Sharifian

Partner:

Telus

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto

Program:

Elevate

Design and validation of a novel peptide immunotherapeutic for the treatment of dog allergies

Adiga Life Sciences Inc. developed a novel immunotherapeutic platform in which small components (peptides) of allergen proteins are identified and administered in a regimen that causes immune cells to become non-responsive towards the allergens. In a phase II clinical trial, the cat allergy treatment developed by Adiga using this platform reduced allergic symptoms in allergic subjects. However, the mechanism of action of the peptide treatment is still not fully understood. During this project, relevant peptides from dog allergens will be identified and assessed for the ability to ameliorate dog allergy. In addition, samples collected from the clinical trials will be assessed to identify how the treatment works and affects immune cells. This project will therefore lead to the production of a new allergen immunotherapeutic and identify a mechanism(s) of action. This will increase our understanding of immunotherapy and potentially identify new targets and biomarkers for the treatment of allergic diseases.

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Faculty Supervisor:

Mark Larche

Student:

Rebekah Sherburn

Partner:

Adiga Life Science Inc.

Discipline:

Medicine

Sector:

Life sciences

University:

McMaster University

Program:

Elevate

High Bandwidth Biometrics Data Hosting and Analytics in Cloud-based Storage Systems

Cloud hosting environments include large scale distributed storage systems. With the advent of Big Data, especially newer biomedical and biometrics data, collected from wearable monitoring devices, there is a high need for Cloud-based solutions for large scale storage and high bandwidth on-the-fly data analysis for such data. A key problem for IT companies that collect large amounts of biometrics data on-the-fly is their need for real-time solutions for anomaly detection in the collected data. This work focuses on (a) on-the-fly biometric data analysis and anomaly detection and (b) on-the-fly analysis of computer system data for anomaly detection of system behavior. The proposed solution will minimize the data analysis search space of the stored data. We will evaluate our solutions in collaboration with the partner organization for types of human and system biometrics data on various distributed storage systems.

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Faculty Supervisor:

Cristiana Amza

Student:

Stelios Sotiriadis

Partner:

Avertus Epilepsy Technologies Inc.

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto

Program:

Elevate

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