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

The influence of cloud-technologies and other technological advance on the print industry

Cloud-based technologies are being used more and more in industry to benefit from the large data-sets that are being created so these data-sets can be analyzed to get a better overview on the effectiveness of processes and how to optimize current processes. The print industry is starting to see the benefits of cloud-based technologies. Since the print industry is just starting to use cloud-based technologies this project will analyze what is currently offered and assist with developing further cloud-based solutions that will enable the print industry to become more efficient in the utilization of their equipment, analysis their workflow systems, and leveraging automation through the computing power of cloud-based technologies.

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Faculty Supervisor:

Martin Habekost;Jason Lisi

Student:

Aditya Saxena

Partner:

Kodak Graphic Communications Canada Company

Discipline:

Other

Sector:

Manufacturing

University:

Program:

Accelerate

Compressed Air Energy Storage in Cased Wells

The project will adapt Compressed Air Energy Storage (CAES) to a cased well. CAES is a mature and proven energy storage technology, however it traditionally uses large salt caverns. By understanding the deformation of a wellbore due to pressure and hot air injection, one may be able to determine the operating range of the system. Cased wells are easy to deploy and decommission. They may be installed wherever is advantageous. They involve drilling a well and installing a high-grade steel casing into the wellbore. The depth of a single well can be anywhere from 500-1500 meters. By injecting air, one stores energy in the form of compressed air inside the well. When it is time to produce power, the air is sent through an expander which produces electricity.

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Faculty Supervisor:

Maurice Dusseault;Yuri Leonenko

Student:

Eric Tharumalingam

Partner:

CleanTech Geomechanics

Discipline:

Engineering - civil

Sector:

Mining and quarrying

University:

Program:

Accelerate

Human Body Capture and Prediction from Rehearsed Live Performances

We address the problem of 3D human body motion capture and prediction to be used in the context of a live music concert performances. The difficulty of capturing the motion of a performer in this context comes from the harsh environment in which it takes place that includes strong and varying lighting, smoke generators, and other visual pollution. The intern will develop novel technique for the capture and prediction of the motion of the performer, knowing that the performance has been rehearsed beforehand. The partner organization benefits from the expertise in computer animation research that has been conducted over the years at McGill University. This collaboration is also beneficial for the the intern and the university in that the partner has a great experience developing cutting-edge computer vision algorithms that are used in music concerts all over the world. They also provide all the necessary equipment to conduct this research.

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Faculty Supervisor:

Paul Kry

Student:

Emma Gouné

Partner:

VYV Corporation

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

Validation of Novel, Tumor Microenvironment-based Targets for Biological Therapeutics

ImmunoBiochem is developing novel anti-cancer therapeutics to address unmet need in intractable solid tumors. Because solid tumors are highly heterogeneous and evasive, recognizing cancerous cells, while avoiding damage to normal tissue, is a challenge. As a result, many targeted therapies quickly come up against resistance, resulting in patient relapses. ImmunoBiochem is solving the issue of tumor versus normal recognition by exploiting cancer targets in the tumor environment – a collection of features that are uniquely present in tumors and absent in the environment of normal cells. This provides for an ability for broader targeting and opportunity to avoid many common resistance mechanisms. The interns will help advance the validation of novel drug candidates in models of various cancer types and subtypes, to understand efficacy and how to ultimately translate the findings to initiate clinical trials in human patients.

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Faculty Supervisor:

Eldad Zacksenhaus;Robert Rottapel

Student:

Maruisz Shrestha

Partner:

Discipline:

Medicine

Sector:

University:

Program:

Accelerate

Enabling next generation cardiac therapeutics with genetic engineering and novel in vivo models for cardiomyocyte transplantation

The development of cellular therapeutics is acutely dependent on the ability to evaluate the functional characteristics of the cells in predictive animal models. This forms the basis of key pre-clinical data packages that are key for regulatory submissions preceding human clinical trials. The development of appropriate model systems, the execution of the surgical techniques to deliver cells to the target tissue, and the techniques to functionally analyze these cells in situ are technically challenging. Michael Laflamme’s laboratory is focussed on the development of protocols for making and testing human stem cell derived cardiomyocytes in animal models and is the world leader in this field. BlueRock Therapeutics (BRT) is actively developing a clinical and commercial pipeline of cell therapies for cardiac indications. This proposal bridges development work being done in the Laflamme lab and at BRT. The data that will be generated in the project will be instrumental in shaping BRT’s development pipeline. Further, the project will provide Wahiba, the proposed trainee, with an opportunity to work with BRT staff to propose a business case and implementation plan for the internalization of this highly specialized skill set within the company.

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Faculty Supervisor:

Michael Alan Laflamme

Student:

Wahiba Dhahri

Partner:

BlueRock Therapeutics ULC

Discipline:

Biology

Sector:

University:

Program:

Elevate

Advanced Characterization of Zirconium Hydrides in Zr-2.5Nb Pressure Tube in CANDU Reactors

In the operation of CANDU reactors, the Zr-2.5Nb pressure tubes holding the cooling water and fuel bundles are susceptible to hydride cracking-induced crack initiation mechanisms, known as delayed hydride cracking and overload crack initiation. For structural integrity evaluation of CANDU pressure tubes, of fracture toughness and hydride crack initiation models were developed. However, the hydride morphology input for the model is still based on microstructures taken decades ago. By applying more advanced electron microscopes and establishing corresponding sample preparation procedures on hydrided pressure tube samples with similar thermo-mechanical history of real in-reactor components, better data input will be generated for the models to ensure more success tube integrity evaluation. Findings from this project will also benefit the industry partner with established sample preparation method for imaging hydrides at different length scales.

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Faculty Supervisor:

Zhongwen Yao;Mark Daymond

Student:

Fei Long

Partner:

Kinectrics Inc

Discipline:

Engineering - other

Sector:

Manufacturing

University:

Program:

Accelerate

Clinical Implementation of Contralateral Inhibition OAE Testing

The proposed research project seeks to develop protocols that will enable one to measure the functionality of the auditory brainstem in a way that is clinically viable and time efficient. This project aims to minimize the time necessary to conduct an inclusive otoacoustic emissions (OAE) test using contralateral acoustic stimulation. By setting threshold signal to noise ratios, outputs from the ear in response to specified pure tones centered around frequency levels imperative for understanding speech will be analysed. The analysis will look to highlight OAE responses above threshold to indicate efferent system functionality. The project will be a collaboration between Western and Vivosonic Inc., a reputable company focused on auditory diagnostics. Through this collaboration, it is expected that the partner will be able to develop software protocols that will allow them to conduct more objective testing using their system, thus increasing the usability and value of their technologies

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Faculty Supervisor:

Prudence Allen

Student:

Maximilian Tran-Luong

Partner:

Vivosonic Inc

Discipline:

Engineering - other

Sector:

Manufacturing

University:

Program:

Accelerate

Safe and Smooth Path Planning for Autonomous Robot Navigation

Clearpath Robotics has developed an accurate GPS navigation system that enables autonomous robots to move in outdoor environments. However, to move toward a target location and avoid obstacles along the path, a path planner is required. The objective of this project is to develop, tune and modify an efficient path planner for the robot in order to make it capable of moving in outdoor environments, then, the performance of the path planner and GPS navigation system will be checked by extensive real-world experiments. The outcome of this project is a well-tested autonomous robot which can move in an environment smoothly and safely. Therefore, it can replace humans in the dangerous working areas and can be used for remote sensing. Also, the partner organization will get a presentation proving the robot’s performance for marketing purposes.

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Faculty Supervisor:

Nasser Lashgarian Azad

Student:

Sina Alighanbari

Partner:

Clearpath Robotics

Discipline:

Engineering - other

Sector:

University:

Program:

Accelerate

Mobilizing Ulukhaktok Traditional Knowledge of the Dolphin and Union Caribou Herd

The Dolphin and Union caribou herd is integral to Inuit culture, subsistence and identity. Preliminary local and scientific knowledge both indicate that this caribou herd is declining and in poorer health than before. We need to bring everyone together and use everything we know about Dolphin and Union caribou, the environment and the other animals to help protect and care for these animals. This project interweaves the experiential knowledge of many people, and is a collaborative effort between Thorpe Consulting Services, the University of Calgary, the Wildlife Management Advisory Council, Government of the Northwest Territories, and the Olokhaktomiut Hunters and Trappers Committee. Our goal is to analyze, summarize and report on a set of interviews conducted with the community of Ulukhaktok in 2011/12 to make this knowledge for management decisions and to facilitate its return to the community.

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Faculty Supervisor:

Susan Kutz

Student:

Andrea Hanke

Partner:

Thorpe Consulting Services

Discipline:

Animal science

Sector:

Other

University:

Program:

Accelerate

Hoy Creek Shared Equity Home Ownership Project: Models, Applicability, and Administration

The Hoy Creek Shared Equity Home Ownership Project aims to provide a site-specific example of how a shared equity home ownership project can succeed in Canada. As few Canadian examples exist of scalable affordable home ownership models, more research is required to identify options for implementation and strategies for long-term administration. This research project aims to identify strategies for shared equity home ownership implementation and administration while determining best practices for Community Land Trust execution. This project is intended to specifically support the development of the Hoy Creek lands in Coquitlam, BC while contributing to a growing body of research regarding options for alternative tenure models across B.C. and Canada.

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Faculty Supervisor:

Penelope Gurstein

Student:

Sean Reisman

Partner:

Community Land Trust

Discipline:

Business

Sector:

Real estate and rental and leasing

University:

Program:

Accelerate

Forecasting Profitability of Real Estate Assets using Machine Learning

This research project aims at applying machine learning over the existing financial forecasting methods currently employed in the commercial real estate industry. Businesses are actively collecting more data than what can be analyzed effectively using the standard spreadsheet models which have become industry standard over the past few decades. Machine learning algorithms are known to be able to extract complex relationship between many variables in data which make them perfect for an application geared towards forecasting the financial performance of commercial real estate assets. This task involves aggregating large amounts of data specific to the asset in question such as revenue, expense and leasing information as well as relevant economic data including rent growth and employment figures. This project will evaluate the performance of some of the most common machine learning algorithms and their relevance to predicting the performance of commercial real estate. Much of the research that currently exists at the intersection of finance and machine learning revolves around the public financial markets or the mass appraisal of residential real estate.

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Faculty Supervisor:

Elkafi Hassini;Kai Huang

Student:

Andrew Foresi

Partner:

One Cornerstone Solutions Corp

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

Health Data Extraction Review Analysis Learning Device in Nephrology (HERALD-RENO)

Data has become a central part of any organization’s day-to-day operation. Organizations are looking to turn this information into actionable insight. The Dialysis Measurement, Analysis and Reporting System (DMAR) is designed to track healthcare quality indicators where changing practice will have high impact. The DMAR system applies rigorous methods to measure key health care performance measures and efficiently implement and measure change. By developing and implementing an engine like the Health Data Extraction, Review and Analysis Learning Device (HERALD), information could be automatically programmed directly within DMAR. OMM will benefit from research using HERALD because DMAR software would be perceived as more innovative and better able to scale since many of the organizations struggling with data quality do so because of high data volumes and manual preparation. Furthermore, using machine learning would ensure that data is coded and validated consistently.

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Faculty Supervisor:

Helen Chen;Catherine Burns

Student:

Anis Sharafoddini

Partner:

Oliver Medical Management Inc

Discipline:

Engineering - other

Sector:

University:

Program:

Accelerate

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