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

Effect of Music on Interbrain Synchrony: A Close Look at Triad of Disabled Children, Parents and Music Therapist

Kids with one, two or three or more disabilities require special care and rehabilitation services. Specifically, for children with severe disabilities who are non-speaking, the opportunities for social interaction and participation are often limited. However, it is believed that these children continue to form relationships with those around them and that the brain encodes these interpersonal connections. One way to study these interpersonal brain connections is to examine the interbrain coordination between children, parents and a therapist. To this goal, we will compare the brain states of children, one of their parents and an attending therapist, in two activity settings: a music session and a story-telling session. These data are being collected at Holland Bloorview Kids Rehabilitation Hospital. This post-doctoral fellowship will focus on developing advanced machine learning and data mining algorithms to dissect these data. These data are not easily analyzed with conventional methods as they are non-stationary, multi-channel, spatially correlated within-individual, and originating from multiple individuals. The findings from this research will advance the care of children and youth with disabilities globally.

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Faculty Supervisor:

Tom Chau

Student:

Javad Rahimipour Anaraki

Partner:

Holland Bloorview Kids Rehabilitation Hospital Foundation

Discipline:

Engineering - biomedical

Sector:

University:

Program:

Elevate

Nutrition, Genetics and Athletic Performance

This project will result in the expansion of an athlete-focused genetic test to include additional genetic markers and algorithms for the purpose of personalized caffeine advice for endurance and other forms of exercise (strength, power, anaerobic-power) through continued analysis of 23 caffeine-associated genes that affect an athlete’s response to caffeine (positive, negative or no effect). The intern has already collected all necessary data, from over 100 athletes, from her previous doctoral research. She has already published some of her caffeine-associated findings. Other genes associated to body composition, dietary intakes and muscle physiology will also be investigated. Additional research in this area will directly benefit the partnering company, Nutrigenomix Inc., as developer of genetic tests for personalized sports nutrition available in 35 countries. The mission of Nutrigenomix is to maintain its position as one of the world’s leading providers and most trusted source of DNA-based nutrition information in a competitive marketplace. To achieve this goal, it is imperative that the company continues novel high-quality research to strength the quality of breadth of its products and services. TO BE CONT’D

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Faculty Supervisor:

John L Sievenpiper

Student:

Nanci Guest

Partner:

Nutrigenomix Inc.

Discipline:

Food science

Sector:

University:

Program:

Elevate

Development of Input and Evaluation Criteria for a Video-Based Occupational Risk Assessment Tool

Workplace injury prevalence and cost have created an immediate need for ergonomics risk assessment tools that require minimal ergonomics training, rooted in a foundation of experimental research, and provide comprehensive outputs that give some indication of risk and required action. Observation-based tools have been widely implemented in practice due to their simplicity, accessibility, and cost- and time-efficiency, but they typically require specialized training, present inconsistent risk categories, and depend on user interpretation of a specific set of static posture and load parameters. MyAbilities Technologies Inc. has developed a video-based risk assessment tool (PDAi: Physical Demands Artificial Intelligence) that addresses these issues by using a task video recorded on a mobile phone and overlaying a set of digital joint locations to estimate physical demands and injury risk. The effect of video recording angle needs to be evaluated to guide users to record video that can maximize the accuracy of assessments results. Further, despite reaching being a prominent aspect of most occupational tasks, the effects of key task parameters – such as sitting vs. standing and one- vs two-handed reaching – are unknown, and need to be evaluated to provide accurate risk estimates related to reaching tasks for both practitioners and researchers.

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Faculty Supervisor:

Peter Keir

Student:

Colin McKinnon

Partner:

MyAbilities

Discipline:

Kinesiology

Sector:

University:

Program:

Elevate

Translation of recent evidence on the effect of sugars on cardiometabolic health

The proposed project includes 2 objectives: (1) provision of high quality evidence on the effect of specific food sources of sugars on cardiometabolic risk factors by conducting multiple systematic reviews and meta-analyses (SRMAs), to address the effect of replacing sugar-sweetened beverages with either diet pop or water in a randomized controlled clinical trial, and to analyze and report national data from StatsCan on current sugars consumption, and (2) efforts to translate the evidence from these studies both directly to the public and indirectly through communications to clinicians and public policy makers, in addition to developing training programs on how to conduct high quality SRMAs in nutrition research. The partnership will focus on the development of better translation strategies which are greatly needed to convey important messages directly from the scientific literature and not to allow misinterpreted results from the media to be a central avenue of information for the public. A main goal of the Canadian Sugar Institute (CSI) is to provide science-based Nutrition Information. Through this partnership, CSI will benefit from the tremendous expertise of the intern in conducting SRMAs, allowing CSI to provide more accurate and clear information on the role of sugars in the diet to health.

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Faculty Supervisor:

John L Sievenpiper

Student:

Laura Chiavaroli

Partner:

Canadian Sugar Institute

Discipline:

Food science

Sector:

University:

Program:

Elevate

Development and Implementation of An Omic-Level Distributed Ledger Data Management Architecture

This Phase I proposal is intended to undertake a requirements-gathering and an initial system design for a system that exploits the integrity guarantees of blockchain technology and the high throughput capability of commercial/open source transactional database management systems (DBMS). Although current approaches will be a part of the solution, innovation is required to allow for increased user control over the information stored about them, including the ability to verify its veracity, revoke access as required/desired, delete data when desired, and ensure availability of verifiable access histories to ensure that systems are in regulatory compliance. Blockchain technologies (sometime referred to as distributed ledgers) will provide an important piece of the overall infrastructure necessary to meet the data protection demands mentioned above. Blockchains provide an immutable means of recording information relating to patient preferences about how, by whom, and when their data might be legitimately accessed for a given purpose. Once patient preferences are stored on the blockchain, access rights can be verified against those presets, thereby guaranteeing compliance and transparency. TBC

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Faculty Supervisor:

Ken Barker;Michael John Jacobson

Student:

Michael M. Kwakye

Partner:

Tunote Oncogenomics

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

Non-convex learning with stochastic algorithms

In recent years, deep learning has led to unprecedented advances in a wide range of applications including natural language processing, reinforcement learning, and speech recognition. Despite the abundance of empirical evidence highlighting the success of neural networks, the theoretical properties of deep learning remain poorly understood and have been a subject of active investigation. One foundational aspect of deep learning that has garnered great intrigue in recent years is the generalization behavior of neural networks, that is, the ability of a neural network to perform on unseen data. Furthermore, understanding better this generalization behavior has significant practical importance as it can provide guidance and intuition on how to design more effective and powerful deep learning algorithms in the future. Our proposal has two primary objectives: (1) develop an algorithm to address the “generalization gap” problem in deep learning: how to decrease the decay in generalization performance when using large-batches in training. (2) Investigate non-vacuous generalization bounds in deep learning through the PAC-Bayes and uniform stability frameworks

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Faculty Supervisor:

Daniel Roy;Murat Erdogdu

Student:

Mufan Bill Li

Partner:

Borealis AI

Discipline:

Statistics / Actuarial sciences

Sector:

University:

Program:

Accelerate

Understanding Relationships between the BC Forest industry and Indigenous entities in BC

The for the health and well being of the BC forest industry and First Nations communities in BC, it is important to know how these two groups are interacting with each other. The goal of this research is to better understand what kind of relationships forestry companies and First Nations communities have. This research would use a survey that was given to members of the largest representative group of the forest industry in BC. By using all of the answers to the survey and combining that with some interviews of important people that work with forestry and First Nations, it would give us a good idea of what’s going on in forestry and how First Nations are getting involved.

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Faculty Supervisor:

Harry Nelson

Student:

Khoi Mai

Partner:

BC Council of Forest Industries

Discipline:

Forestry

Sector:

Agriculture

University:

Program:

Accelerate

Archival Research and Accessioning for the CSCE National History Committee

The proposed research project will determine the significance of and catalog historic papers and documents held by the National History Committee (NHC: established 1983) of the Canadian Society for Civil Engineering (CSCE: established as the Canadian Society of Civil Engineers in 1887). These records have been rather haphazardly stored by various Chairs of the NHC since its inception and, if properly organized, will provide a valuable archive for historical researchers that will be housed at the University Ontario Institute of Technology Library. The research will also augment available information to develop succinct, accurate and consistent descriptions of the 78 existing CSCE National and International Historic Sites for dissemination through the CSCE Website and other media. The research will develop guidelines to allow oral histories of prominent Canadian civil engineers to be obtained by interviews that include procedures to obtain necessary ethical approvals, interviewee agreement forms, and guidance for the interviewer.

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Faculty Supervisor:

Michelle Hamilton;Michael Dove

Student:

Louisa Orford

Partner:

Canadian Society for Civil Engineering

Discipline:

History

Sector:

University:

Program:

Accelerate

Economic impact and feasibility analysis of public investments in broadband connectivity, and in other sectors

Interns will perform research leading to the design or the implementation of new economic strategies that can be utilized in the design, financing, monitoring and evaluation of projects at different stages. Specifically, interns will work on an analysis of equitable access to broadband connectivity in Kingston, ON, as part of the City’s plan to expand broadband access. By analyzing the benefits of broadband access and where gaps currently exist, the research will result in policy recommendations. A second area of research involves looking at innovative financing mechanisms for projects in the international development and domestic social sectors. Interns will research how to use these tools to maximize project impact, and determine how lessons learned from similar financing arrangements in infrastructure projects might apply to the social sector.

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Faculty Supervisor:

Huw Lloyd-Ellis;Warren Mabee

Student:

Ardyn Nordstrom;Emma Kinakin;Katerina Gribben;Neal Mckegney

Partner:

Limestone Analytics Inc

Discipline:

Economics

Sector:

University:

Program:

Accelerate

Development of a new Electronic Fetal Heart Rate Monitoring for use in the Clinical Setting

Fetal Heart Rate Monitoring prior to and during labor and delivery is a common clinical practice, that guides therapy and decision making. A non-stress test (NST), also known as fetal heart rate (fHR) monitoring, is a common prenatal test used to check on a baby’s health. The maternal electrocardiogram (mECG) is generally the most prominent signal present in abdominal NST recordings. Therefore, the mECG needs to be removed to enable reliable and accurate fHR detection. While the NST is non-invasive, current techniques of data acquisition use a limited sampling frequency (as low as 4Hz) which limits the quality of the information available, and prevents the use of mathematical techniques to process the data for better interpretation and to differentiate between the fHR and mECG signals. TO BE CONT’D

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Faculty Supervisor:

Reed Ferber

Student:

Hamidreza Namazi

Partner:

Biotricity Inc

Discipline:

Kinesiology

Sector:

Health care and social assistance

University:

Program:

Accelerate

Characterizing the sources of methane, CO2, and hydrogen sulphide presence during thermal oil recovery operations

Greenhouse gas (GHG) emissions contribute to a global warming trend associated with climate change. Methane is a potent GHG with a global warming potential 25 times that of Carbon Dioxide over a 100-year period. Gas migration /Surface casing vent flows from subsurface to surface is a well-known issue; however, characterizing the source zone(s) for stray gases from production, injection, and observation wells is an ongoing challenge in the oil/gas industry. Accurate identification of source zone is critical to ensure well repairs or other mitigative actions are effective in preventing release of such gases to the atmosphere. Geochemical approaches based on gas compositions and stable isotope ratios are widely used in conventional operations; however, high temperatures associated with thermal operations complicate identifying the origin of stray gases. This project will develop advanced geochemical tools to definitively identify sources of gases produced from steam-assisted gravity drainage operations, reducing GHG emissions.

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Faculty Supervisor:

Scott Mundle

Student:

Karlynne Dominato;Neda Mashhadi;Kelsey Friesen

Partner:

Devon Canada Corporation

Discipline:

Biochemistry / Molecular biology

Sector:

Mining and quarrying

University:

Program:

Accelerate

Securing elastic radio access networks

G networks have emerged as a promising solution for Mobile Network Operators (MNOs) to offer ultra-fast mobile broadband and ultra-low latency services with exceptional reliability for consumers. By leveraging softwarization, Software-Defined Networking (SDN) and Network Function Virtualization (NFV), MNOs can offset the high capital and operational expenditures incurred due the additional deployment of legacy equipment. Cloud Radio Access Network (C-RAN) is a novel mobile network architecture that offers centralized operation of BaseBand Units (BBUs), and scalable deployment of lightweight Remote Radio Heads (RRHs). Elastic-RAN (E-RAN), Ericsson’s implementation of C-RAN, leverages SDN and NFV to offer flexible and elastic 5G network slicing to meet the different end-users QoS. Though virtualization facilitates flexible coordination between BBUs and RRHs, it introduces new security vulnerabilities in E-RAN. For instance, a Distributed Denial of Service (DDoS) attack can cause severe degradation of the QoS/QoE by compromising the availability of resources and the integrity of data. In this proposal, we: 1) employ Machine Learning (ML) to develop novel techniques for anomaly-based DDOS detection, 2) devise mitigation measures to protect against DDoS attacks and zero-day threats using ML, and leverage the flexibility offered by NFV and SDN to automatically reconfigure network slices across the multi-tenant E-RAN infrastructure.

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Faculty Supervisor:

Raouf Boutaba

Student:

Hyame Alameddine

Partner:

Ericsson Canada

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Program:

Elevate

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