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

Advanced Security Mechanisms for Autonomous Vehicles

Autonomous vehicular applications require the distribution of high volume of information-rich and safety-critical data among heterogeneous players. Autonomous vehicles (AV) communicate with each other and the world around them in high mobility manner under poor connectivity and tough signal propagation. Attacking AVs are applicable business and cyber-attacks can affect the AV industry and cause severe damages to individuals and organizations. In this project, we propose advanced security mechanism to defend against various attacks that affect the integrity, access control, availability, and privacy of AVs. The proposed security mechanism will be implemented and integrated with recent technologies such as Information Centric Networking (ICN) and Artificial Intelligence (AI), and overcome the capacity, latency, reliability, and scalability challenges of AV communications.

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Faculty Supervisor:

Changcheng Huang

Student:

Eslam AbdAllah

Partner:

Quantropi

Discipline:

Engineering - computer / electrical

Sector:

Automotive and transportation

University:

Program:

Accelerate

Transformation of THC and CBD synthesis genes into Yeast

Cannabinoids are diverse chemical compounds that are created by the Cannabis crop. To produce and extract the necessary amounts of cannabinoids for the market is taxing on the environment due to its high energy input costs. However, through the use of synthetic biology and genetic engineering, cannabis related chemicals can be created using simple yeast which are ubiquitous and more environmentally sustainable. BioFect Innovation is proposing to create cannabinoids created through the genetic engineering of yeast. The intern will create a unique yeast strain capable of synthesizing specialized cannabinoids that are designed towards industry needs. This project will produce a research foundation which BioFect Innovations will build on

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Faculty Supervisor:

Roberto Botelho

Student:

Louis Lo

Partner:

Science Discovery Zone

Discipline:

Biology

Sector:

Life sciences

University:

Program:

Accelerate

Development of a reliable and scalable underwater acoustic modem for networked applications

The proposed project represents a critical effort towards developing the enabling communication technology for the future of subsea connectivity where conventional communications technologies such as Wi-Fi and GPS cannot be used. The intern will work to completely overhaul traditional underwater communications methodologies and advance acoustic communications towards the higher reliability and data rates needed for future underwater networked applications and deployments. This will be done by developing a new generation of innovative acoustic data communications modems for underwater applications which are affordable, scalable, and flexible to meet the many different customer application requirements presented in the ocean management, surveillance, research, protection and monitoring industry. The knowledge and skills the intern will bring to the company will allow them to design key system components that will be incorporated into the overall platform.

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Faculty Supervisor:

Jason Gu

Student:

Colin Ross

Partner:

Acoubit Communications Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

Biomechanical and Clinical Evaluation of the Levitation Knee Brace

Osteoarthritis (OA) is a debilitating musculoskeletal disease affecting approximately 1/3 of Canadians over the age of 25. Knee braces are often prescribed for OA patients to restore joint function and reduce pain in an attempt to avoid or delay knee replacement surgery. Most braces are designed to offload one side of the knee, however, more than 95% of knee OA patients have OA that affects more than one compartment of their joint. Spring Loaded Technology has designed the Levitation™ “Tri-Compartment Unloader” knee brace to reduce forces in all three compartments of the knee. This study aims to determine how effectively the brace offloads the knee joint, and how brace use affects clinical outcomes, like pain and quality of life, in patients with multi-compartmental knee OA. TO BE CONT’D

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Faculty Supervisor:

Janet Ronsky

Student:

Emily Bishop

Partner:

Spring Loaded Technology

Discipline:

Engineering - mechanical

Sector:

Life sciences

University:

Program:

Accelerate

Advanced FEA of Trawl Gear Interaction with Subsea Pipelines

This project will provide guidelines for the design of pipeline systems for deep water locations where fishing activities occur. These pipelines may be subject to loads from trawls and associated trawling equipment. While similar interaction between trawling gear and subsea pipelines has been studied for shallow water pipeline installations, it has not been studied for the deepwater scenario, offshore Newfoundland and Labrador.

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Faculty Supervisor:

Bruce Quinton

Student:

Farhad Davaripour

Partner:

Technip Canada Ltd

Discipline:

Engineering - other

Sector:

Oil and gas

University:

Program:

Accelerate

PET/MRI Imaging Development for Pre-clinical Neuroimaging Applications

The field of nuclear medicine relies on positron emission tomography (PET) and single photon emission computed tomography (SPECT) scanners to visualize molecular processes in normal and disease states in the living human. These imaging technologies have significant potential to enhance our ability to diagnose disease, develop appropriate disease-modifying treatments and for non-invasive monitoring of these therapies.
Canadian medical device company Cubresa Inc., has developed and commercialized new PET/MRI (magnetic resonance imaging) technologies for use in pre-clinical (small animal) imaging research. These high-performance scanners provide exceptional detail and permit rapid evaluation of emerging disease diagnostics and therapies that can be more readily translated to use in humans. Characterizing the performance, validation and optimizing the capabilities of this PET/MRI technology in a variety of brain imaging applications will ultimately accelerate Cubresa’s product development, generate tools/approaches that have potential to be patented/licensed and help position them as major players in the global medical device market.

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Faculty Supervisor:

Steven Beyea

Student:

Drew DeBay

Partner:

Cubresa Inc.

Discipline:

Medicine

Sector:

Medical devices

University:

Program:

Accelerate

ASD Specific Housing Supports Analysis

The proposed study will use a sequential exploratory mixed-method approach to conduct a needs assessment examining supportive housing requirements for adults diagnosed with autism spectrum disorders (ASD). The study first explore supportive housing and provincial, national and international solutions for supportive housing for adults with ASD found in policy, practice, government, and mass media publications. Later interviews and analysis will involve a deep dive into a set of research questions.

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Faculty Supervisor:

Sharon Penney

Student:

Robyn Cossitt

Partner:

Autism Society of Newfoundland and Labrador

Discipline:

Education

Sector:

Management of companies and enterprises

University:

Program:

Accelerate

Operating Strategy for Electromagnetic-based Thermal Recovery Method

Canada has the third largest oil reserves in the world, mostly in oil sands located in the northern Alberta, which is estimated to be 166 billion barrels. Steam Assisted Gravity Drainage (SAGD) has been the only commercially viable in-situ recovery method available to date. Application of SAGD is known to be energy intensive and has associated environmental impacts. Electromagnetic heating (EMH) has been the focus of ever-increasing theoretical and experimental studies to examine if it can be used to heat up the geomaterials in field scale. Bitumen recovery using EMH technique assisted by solvent injection such as ESEIEH pilot in currently being conducted in the Athabasca oil sands, utilizes radio frequency waves to generate a moderate amount of heat. In this study, the development of a robust operating procedure based on the geological heterogeneity and interstitial water mobility is sought. TO BE CONT’D

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Faculty Supervisor:

Hassan Hassanzadeh

Student:

Asghar Sadeghi

Partner:

CNOOC Petroleum North America ULC

Discipline:

Engineering - chemical / biological

Sector:

Oil and gas

University:

Program:

Accelerate

Guidance and Control of Hybrid Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) with Thrust Vectoring Capabilities

Quadrotors are one of the most popular choices for unmanned aerial vehicles (UAVs) in situations where fast disturbance rejection, vertical takeoff and landing (VTOL) capabilities, and maneuverability are required. However, the quadrotor is inherently underactuated, and as a result, it is impossible to independently control the orientation and position of the vehicle. One solution to this problem involves rotors that can rotate relative to the vehicle frame, allowing for the angle of each rotor relative to the main vehicle frame to be independently controlled. This type of thrust vectoring in a quadrotor allows it to track both attitude and position trajectories. One other disadvantage with quadcopters is that they often fly at slower speeds and have shorter flight ranges compared to traditional fixed wing UAVs. TO BE CONT’D

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Faculty Supervisor:

James Forbes

Student:

Mitchell Cohen

Partner:

ARA Robotique

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

Program:

Accelerate

Forensic Manufacturing: Development of Innovative Materials Solutions in Emerging Electronics Technology Sectors

The world we live in is becoming increasingly dependent on electronic devices. With emerging technologies such as autonomous vehicles and smart cities, these devices will strongly influence the way we work, live, and play. In many applications, high reliability is desired, and the understanding of how and why a device should fail is essential in preventing future, potentially catastrophic events from occurring. This project, in conjunction with Celestica Inc., employs state of the art materials characterization techniques to study the properties of materials in electronic devices, such as solder joints. The outputs from this project will allow for the development of novel materials to be implemented in actual devices in the future, which are more rugged and durable in demanding applications. The project will allow Celestica to leverage its expertise in aerospace into other high reliability industries to differentiate as a global leader in electronics manufacturing solutions.

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Faculty Supervisor:

Doug Perovic

Student:

Andre Delhaise

Partner:

Celestica

Discipline:

Engineering - other

Sector:

Aerospace and defense

University:

Program:

Accelerate

Automatic Approach to Design Efficient Deep Neural Networks

Deep neural networks have demonstrated state-of-the-art modeling accuracy on a wide range of real-life problems, with some cases surpassing human performance. Despite the promise of deep neural networks as an enabling technology for a large number of industries and fields, there are two particular key challenges in the design of deep neural networks in real-world, operational scenarios. First, the design of deep neural networks is a very time consuming process for a machine learning expert, and often results in complex, non-optimal deep neural networks. Secondly, many of the deep neural networks designed in recent years, while achieving high accuracy, are often very complex with high millions to billions of parameters, making such networks intractable for real-time scenarios on mobile device, IoT devices, and other embedded devices. TO BE CONT’D

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Faculty Supervisor:

David Clausi

Student:

Seyed Mahmoud Famouri

Partner:

DarwinAI

Discipline:

Engineering - other

Sector:

Information and communications technologies

University:

Program:

Accelerate

Development of Dynamic Feature Extraction Techniques for Industrial Process Data Analysis with Application to Optimization of Steam Assisted Gravity Drainage (SAGD) Process

The Operational Excellence (OpEx) team at Spartan Controls is actively involved in several initiatives for developing advanced process control (APC) solutions to the oil sands industry. The OpEx team collaborates with Professor Biao Huang’s research group through the NSERC Industrial Research Chair (IRC) in the Control of Oil Sands Processes program for solutions that require extensive research and development. This proposed project will complement the on-going joint research efforts with the development of new data analysis techniques to address the APC problems in the steam assisted gravity drainage (SAGD) process facilities. SAGD is an in-situ thermal oil sands recovery technique, which finds widespread application in the province of Alberta for bitumen production. The proposed project has two components, (i) theoretical research for the development of data analysis techniques to study the SAGD process data, and (ii) translation of the research results into applicable solutions in the industry. TO BE CONT’D

View Full Project Description
Faculty Supervisor:

Biao Huang

Student:

Rahul Raveendran

Partner:

Spartan Controls

Discipline:

Engineering - chemical / biological

Sector:

Oil and gas

University:

Program:

Accelerate

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