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

Applying Machine Learning to Human Motion & Musculoskeletal Health: Predicting ACL Injury & Recovery from Monocular Video

Active people, and young athletes in particular, are at high risk of tearing the anterior cruciate ligament (ACL) with 200,000/year occurring in the United States. However, current effective methods to assess functional test performance are onerous, lengthy (~1hr), complex and costly. Curv Labs is a Canadian start-up that leverages computer vision and artificial intelligence to help assess, identify, and manage musculoskeletal performance and problems, and does so, using only simple video, such as that taken from a mobile device. Curv Labs transforms the camera on any mobile device into a diagnostic tool to accurately assessment movement-related metrics. The gap in the literature this research will address, is whether a system, such as Curv labs, can accurately and viably conduct musculoskeletal assessments via simple video.

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Faculty Supervisor:

Cheryl Kozey

Student:

Shea Balish

Partner:

Curv Labs Inc

Discipline:

Engineering - biomedical

Sector:

Medical devices

University:

Program:

Accelerate

Blood product demand forecast modeling using clinical predictors

Blood transfusion is one of the most crucial and commonly-administrated therapeutics worldwide. The need for more accurate and efficient ways to manage blood demand and supply is an increasing concern in many countries. Building a technology-based robust blood demand and supply system that can achieve the goal of reducing the costs of wastage and shortage, while maintaining the safety of blood usage, is essential in modern healthcare organizations. Many countries have recognized the importance of applying technology and mathematical models into blood inventory planning and management. There are a number of studies addressing blood inventory, blood allocation policies and simulation studies for blood supply networks, but to-date few forecasting models incorporating patient clinically-related indicators have been developed. In collaboration with Canadian Blood Services (CBS) and McMaster, we will use patient clinical data and inventory data to develop a comprehensive demand forecasting model for blood products and plasma derivatives in Canada.

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Faculty Supervisor:

Douglas Down

Student:

Na Li

Partner:

Canadian Blood Services

Discipline:

Computer science

Sector:

Medical devices

University:

Program:

Accelerate

Mammal Densities in a Restored Landscape, the Algar Habitat Restoration Program

Species-at-risk conservation is complex and multi-faceted. However, mitigation strategies are typically narrow in scope, an artefact of conservation research that is often limited to a single species or stressor. The ability to research an entire community of strongly interacting species would greatly enhance our ability to forge more comprehensive and effective conservation decisions. Seismic line restoration is a key management strategy for caribou conservation but little is known about the response of this restoration on boreal mammals generally, or caribou, specifically. This project will capitalize on an ongoing camera trap survey monitoring wildlife responses to seismic line restoration in Alberta’s boreal forest, which overlaps with critical caribou habitat. The objectives of this project are to use advanced spatial capture-recapture models (spatial count and spatial mark-resight) to estimate the densities of 7 focal boreal mammal species: caribou, black bear, coyote, lynx, moose, white-tailed deer, and wolves. Estimating the densities of the broader boreal mammal community will provide insight into potential predation risks of carnivores, beyond merely wolves, to caribou, and the influence of apparent competition with moose and white-tailed deer. Densities provide a common currency with which to compare the status of boreal mammals in the restored landscape to boreal mammals

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Faculty Supervisor:

Cole Burton

Student:

Joanna Burgar

Partner:

InnoTech Alberta Inc

Discipline:

Forestry

Sector:

Environmental industry

University:

Program:

Accelerate

Experimental Evaluation of Surface and Deep Filtration Sand Control Solution

Sand production during extraction of bitumen in oil sand industry is the most significant challenge which results in many operational problems such as erosion of downhole and surface equipment, collapse of the formation, and subsequently a dramatic increase in capital and operating costs of the production plant. Mesh weaves are currently used to reject sand during production and mitigate these effects. The proposed research project will investigate the flow, and solid retention capacity of different mesh weaves in various test cells. The feed characteristics and the morphology and roughness of some commercial meshes will be first investigated. The performance of selected mesh screens will then be evaluated in sand retention using dead-end and cross-flow filtration systems and the flow rate and sand retention efficiency will be evaluated. The final product will be the optimum mesh screen in terms of both production rate and sand retention efficiency. Another important deliverable will be development of a strategy for the testing and qualification for the mesh weaves will be provided.

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Faculty Supervisor:

Mohtada Sadrzadeh

Student:

Seyedabolhassan Hosseini

Partner:

RGL Reservoir Management Inc.

Discipline:

Engineering - mechanical

Sector:

Oil and gas

University:

Program:

Accelerate

Image-based Feature Engineering in Age Related Macular Degeneration (AMD): bridging the biology of ophthalmic imaging with advanced computer analytics for enhanced clinical trial design and personalized medicine in blinding eye disease.

This project allows a PDF to take on a “feature engineer” role in which she will work closely with a biomedical engineer to identify novel features based on Tracery’s proprietary imaging method for Age-related Macular Degeneration (AMD). The PDF will serve as a vital link between clinical disease and computing, interacting with both academic and industry partners for automated feature extraction and ultimately machine learning and artificial intelligence. As there are no treatments for the 85% of patients with a diagnosis of “dry” AMD, the benefit the PDF will provide to the academic partner is a diagnostic tool to aid in patient care and the benefit to the industry partner is a novel tool to aid in the development of treatments for dry AMD.

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Faculty Supervisor:

Filiberto Altomare

Student:

Emily Mathieu

Partner:

Tracery Ophthalmics Inc

Discipline:

Visual arts

Sector:

Medical devices

University:

Program:

Accelerate

Formulation scale-up and characterization for a manganese-based contrast agent

To design effective and patient-specific cancer therapy, sensitive detection of relapse and distant metastases by non-invasive medical imaging is essential, for which MRI offers tremendous potential due to wide availability of the equipment in clinic and avoidance of ionizing radiation. Although gadolinium-based contrast agents are the most frequently used for MRI, they are associated with nephrogenic systemic fibrosis and brain deposition. Thus, less toxic manganese ions (Mn2+) are exploited as an alternative for tumor detection using MRI. Yet, the current formulations of Mn2+ cannot provide desirable results due to low tumor uptake after systemic administration. To address the need, Nanology Labs offers a novel manganese-based MRI contrast agent which is able to detect solid tumors and brain metastasis at early stages. In this project we aim at scaling-up the formulation prototyping for scale up industry manufacturing.

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Faculty Supervisor:

Jeffrey Henderson

Student:

Mohammad Amini

Partner:

Nanology Labs Inc.

Discipline:

Pharmacy / Pharmacology

Sector:

Pharmaceuticals

University:

Program:

Accelerate

Applying Traditional Chinese Medicine to Osteoporosis

Herbal medicines are mainly used to maintain health, prevent diseases and treat chronic conditions. Although many Canadians have taken or are regularly take herbal products, there still are concerns about the safety and quality of these products. Osteoporosis is a chronic disease called silent thief since there are no symptoms until bone fractures happened. The fractures from osteoporosis are more common than heart attack, stroke and breast cancer combined. Especially for women approaching or being in menopause, lose 2-3% of their bone mass each year. Hence, this project aims to develop the manufacturing and quality control protocol for a herbal product with specific tests acceptable to Health Canada. The project will also investigate the efficacy of the product to support the future clinical use in the treatment of osteoporosis. Finally, a safe, effective, and quality assurance herbal product will be produced in Canada.

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Faculty Supervisor:

Michael Doschak

Student:

Jieyu Zuo

Partner:

JRC Pharmaceuticals Inc.

Discipline:

Pharmacy / Pharmacology

Sector:

Pharmaceuticals

University:

Program:

Accelerate

Device-free healthcare approaches for human activity monitoring and positioning by using Wi-Fi signals

As the world aging process quickened, the need for healthcare solutions to support seniors living on their own is recognized as a serious medical and social problem. Though an extensive amount of research has been carried out to investigate human activity based on a range of device-oriented (e.g., wearable) and device-free (e.g., vision based) sensing technologies. Monitoring activities of clinical relevance for senior well-being (e.g., eating, sleeping and falls) is still very challenging. Since the elderly people may not like to carry/wear sensors and they also have privacy concerns about non-wearable devices (e.g., in-home cameras). Moving along this direction, this project aims to provide a non-intrusive device-free approach for elderly activity monitoring and positioning by using the already deployed commodity Wi-Fi infrastructures. We focus on analyzing the specific motion of the elderly people (e.g., slowed movements, unstable transfers) to identify different events by leveraging the Wi-Fi Channel State Information (CSI) measurements, which is less discussed in the existing work. Moreover, both classical machine learning algorithms (e.g., SVM and KNN) and deep models (e.g., CNN, LSTM and attention model) will be deployed to enhance the system performance (…)

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Faculty Supervisor:

Xue (Steve) Liu

Student:

Landu Jiang

Partner:

Aerial Technologies Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

Pipe Acoustical Characterization of Packaged Screw Compressors

The gas processing industry is fielding screw compressors of increasingly larger size. These machines are usually packaged together with process piping and equipment by several local packaging companies that regularly hire consultants (such as AP Dynamics) to conduct design reviews geared to mitigate potential issues with pulsations and mechanical vibrations. Budgets and timeline constraints of typical projects do not allow for full fledge CFD analysis of these installations, thus AP Dynamics would like to develop computational methods and tools that address the particular issues of tracking pressure pulsations and the induced mechanical vibrations in the frequency range of 300 to 3000 Hz. The successful completion of the stated objectives will be of fundamental importance to AP Dynamics. It will improve the company’s ability to seek new projects in the area of refrigeration and gas processing where screw compressors are most commonly used. It will enhance the reputation for accurate prediction of outcomes.

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Faculty Supervisor:

Qiao Sun

Student:

Neysa Gunness

Partner:

AP Dynamics Inc

Discipline:

Engineering - mechanical

Sector:

Energy

University:

Program:

Accelerate

Developing novel varieties of canola, rice and alfalfa with improved cell wall characteristics

Biobased products, mostly derived from plant biomass, have the potential to improve the sustainability of Canada’s natural resources and environmental quality while competing economically. Plant biomass, composed primarily of cell walls and modification of cell wall properties has the potential to improve biomass conversion to biobased products such as biofuels as well as improve feedstock quality in forage crops. Progress towards achieving this goal is currently impeded by a lack of knowledge of how cell walls are assembled and how their structure affects the processing of biomass. The scope of the proposed research is to identify new varieties of crops (rice, canola, and alfalfa) having improved plant biomass properties. These will be identified using a multipronged approach that utilizes state of the art plant molecular biology techniques and novel screening methods.

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Faculty Supervisor:

Dario Bonetta

Student:

Muhammad Jamshed

Partner:

Frontier Agri-Science Inc.

Discipline:

Biology

Sector:

Life sciences

University:

Program:

Accelerate

Optimization of new hydrophobic pulp on conventional pulp moulding machines

Moulded pulp, is a packaging material, made from recycled papers. It is used for protective packaging such as egg packaging, fruit trays and coffee cup carriers. For many applications moulded pulp is less expensive and environmentally friendly than plastics and styrofoams, however, due to their high water absorption and low strength, these products are limited to only few packaging products. Biobinder, a biobased binder, has been developed from University of Toronto to imparts water repellency and improves the strength of moulded pulp products. By using biobinder for manufacturing moulded pulp products, it is not only making fully biobased waterproof packaging products but also savings in materials cost. The proposed research will create jobs at forest-based sectors and will result in overall economic growth by expending the advantage of the new products in packaging industry including horticultural industry, food packaging and hospital disposable containers.

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Faculty Supervisor:

Mohini Sain

Student:

Javad Sameni

Partner:

Pulp Moulded Products

Discipline:

Engineering - other

Sector:

Advanced manufacturing

University:

Program:

Accelerate

Development of Rapid Inverse Kinematics (IK) Modules for Integrated Robot Simulator

Industrial robotics (i.e. using robots for manufacturing processes) is one of the fastest growing industry sectors today. Traditionally, the process to program industrial robots has been laborious and time-consuming, with each robot having to be taken off-line for setup. Offline programming allows the robot users to program, simulate and generate code for multiple robots at the same time without disrupting the manufacturing process. To gain competitive edge in the global market for such specialized robot simulation programs, the industry partner is collaborating with researchers at University of Waterloo to develop rapid inverse kinematics (IK) code that will improve the ability to solve robotics problems on behalf of the user and make industrial robotic programming easier and faster. Users of offline programming solutions are not robotics experts. They are manufacturing trades people (e.g. Welders). Computationally efficient IK codes to be developed through this project will allow for algorithm development that can iteratively find optimized error free robot paths without user intervention.

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Faculty Supervisor:

Soo Jeon

Student:

Mostafa Osman

Partner:

OCTOPUZ Inc.

Discipline:

Engineering - mechanical

Sector:

Advanced manufacturing

University:

Program:

Accelerate

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