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

Fully Automated End to End Analysis of Non-small-cell Lung Carcinoma using Deep Learning Techniques.

Deep learning in medical imaging analysis has revolutionized the field in areas such as computer-aided detection and segmentation of clinical abnormalities. Several studies have been published on lung cancer screening using deep learning methodologies. Specific to lung cancer screening, algorithms have been trained to automatically detect and diagnose lesions in the lungs in low dose computed tomography (CT) by leveraging longitudinal imaging in combination with biopsy results. Perez et.al [3] proposed a three-dimensional (3D) CNN model to detect lung nodules and predict lung cancer using CT images. The lung is extracted from the entire volume in each patient and the extracted data is used to train the model. To increase the precision, both 2D and 3D convolutions were used. They were able to achieve best results using 3D convolutions suggesting there is information between slices that is relevant for lung cancer analysis.

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Faculty Supervisor:

Eran Ukwatta

Student:

Jenita Priya Rajamanickam Manokaran

Partner:

Altis Labs Inc.

Discipline:

Engineering

Sector:

Other

University:

University of Guelph

Program:

Accelerate

Improving Monitoring and Decision-making with Uncertain Sensor Data

Terrestrial contaminated sites – such as abandoned oilfields, chemical spill sites, or former industrial zones – are a major environmental problem in Canada and around the world. Environmental Material Science has created new environmental monitoring equipment that generates high-resolution spatially and temporally explicit data on environmental quality. The data must be visualized and then used to make decisions regarding if site remediation needs to occur, or if occurring, if site remediation should stop. Such environmental management decisions need to explicitly and transparently community data uncertainty and variability in the decision-making process. Data visualization techniques in the environmental sciences that allow non-expert stakeholders to interpret complex data streams do not exist, with existing techniques designed to be used by experts, who then report to stakeholders. The intent of this research project is to develop data visualization approaches that can be used by non-expert stakeholders to aid in their decision making process on environmental site management.

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Faculty Supervisor:

Carl Gutwin

Student:

Natanael Tome

Partner:

Environmental Material Science

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Soil, Water and Topography Maps as a Management Tool to Improve Profitability and Sustainability within the Potato Industry

The proposed research will explore opportunities in measuring spatial variability in soil, water and topography within potato fields. Addressing this variability by doing site specific application of inputs such as fertilizer, crop protectant and seed can help to increase environmental sustainability and economic viability in potato production. This research will help develop new applications for SWAT mapping in potatoes all over the world.

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Faculty Supervisor:

Aitazaz Farooque

Student:

Evan MacDonald;Kaelyn MacLeod

Partner:

Croptimistic Technology Inc

Discipline:

Engineering

Sector:

Agriculture

University:

University of Prince Edward Island

Program:

Accelerate

Generative models for controlled generation of synthetic sequence-based datasets

At a high level, the goal of this project is to create a system for producing synthetic datasets based on real data. As a large financial crime detection firm, Verafin deals with large volumes of sensitive data which must be kept private, however they are also interested in collaborating with academics to gain new insights into their data. In this project we will use recent developments from the field of generative modeling to design a system which can create synthetic datasets which are nearly indistinguishable from the true data they are mimicking, while not exposing information which must be kept private. In addition to making it easier for Verafin to collaborate with external parties, another benefit is Verafin can use the synthetic data to create more realistic product demonstrations for potential clients.

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Faculty Supervisor:

Yuanzhu Chen;Antonina Kolokolova;Ting Hu

Student:

Kyle Nickerson

Partner:

Verafin Inc.

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Memorial University of Newfoundland

Program:

Accelerate

An Integrated Software Suite for Rail Condition Analysis using Machine Learning

Rail transit and freight rail properties apply rail grinding to maintain rail condition and ensure satisfactory performance of rail infrastructure systems. The proposed research investigates and applies a variety of computationally intelligent algorithms to establish useful relationships between rail corrugation, noise generation, and vibration. These relationships will support more timely and effective rail grinding interventions. The algorithms will process real-world rail corrugation, noise, and vibration data collected from three rail transit properties in North America. The long-term research goal is the development of a generic and transferrable rail corrugation index, which will help rail maintenance practitioners determine when rail corrugation is likely to generate unacceptable noise and vibration. Consequently, the research directly supports rail and vehicle asset management programs, helps reduce noise irritation for passengers and citizens in the vicinity of rail transit lines, and improves ride quality.

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Faculty Supervisor:

Ian Jeffrey;Jonathan Regehr

Student:

Julian Carneiro

Partner:

Advanced Rail Management

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Inspiring mass stakeholder groups to self-alter their normative patterns and thrive through self-interest and self-direction

This research project seeks to explore/determine if mass-stakeholder-groups can be purposefully, and directionally, influenced to self-alter their respective normative patterns of behavior, and to then further self-sustain their new normative behaviors through their self-interests and self-direction. In other words, if we increase their awareness of tools and supports available, could we encourage those who are considered under-performing to self-identify and then divest from their potentially detrimental normative behaviors to ultimately thrive through self-interest and self-direction?

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Faculty Supervisor:

Eva Malisius

Student:

Greg Molendyk

Partner:

GGM Enterprises

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

Royal Roads University

Program:

Exploring the Reconciliatory Potential of Marketing Processes in the Book Publishing Industry

There is a growing recognition in the publishing industry that standard supply chain marketing strategies have not been effective in promoting Indigenous materials and reaching Indigenous audiences. This problem has prompted us to explore how marketing processes can be amended or augmented to ensure that Indigenous organizations and educators are introduced to the resources that are being created to support their objectives of cultural revitalization. The question we are posing is (how) can marketing be a strategy that contributes to the national project of reconciliation? Using the Six Seasons Series as a case study, this research will be undertaken with Portage & Main Press, an industry partner on the Six Seasons of the Asiniskaw ?thiniwak Partnership Project, and contribute to their goal of making visible works by and for Indigenous artists, educators, and young peoples through the development of a marketing strategy that intentionally seeks to create and strengthen relationships and networks with Indigenous organisations and educators.

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Faculty Supervisor:

Mavis Reimer;Linda DeRiviere

Student:

Tara Myran

Partner:

Portage & Main Press Ltd.

Discipline:

Other

Sector:

Information and cultural industries

University:

University of Winnipeg

Program:

Accelerate

Solving the integration problem for loyalty programs

Paying with a mobile phone within brick and mortar retailers is becoming increasingly popular, as it adds convenience as well as security to the payment process. Many retailers that use interac terminals with tap technology allow mobile phone payments in this way but are unable to integrate loyalty points into the mobile payment process. This is called the mobile loyalty payment integration problem, as most retailers who offer loyalty programs, have to scan the mobile loyalty application but are unable to have the process take place while the consumer is paying with the purchase through the mobile application. This issue can potentially be solved through could based technology, which would allow the mobile phone user to collect rewards while simply using the tap technology on the interac payment terminal, while paying for their purchase.

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Faculty Supervisor:

Israat Haque

Student:

Fergus Dearden

Partner:

Bluethumb Technologies

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Simeio: Anomaly Detection for Building Automation System – Year two

Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis. Real-time monitoring and analysis of data can reveal insights about the performance of the building helping to reduce operating costs, lower utility bills, increase equipment life, improve tenant comfort, retention, and leasing rates; all while lowering carbon emissions. Simeio (A Cloud based software application developed by UCtriX team) is leveraging powerful artificial intelligence (AI) analytics to automatically detect anomalies and faults in the HVAC system and pinpoint any abnormalities or failures in a building. Simeio is a platform used by building owners, building managers, or higher authorities to ensure the sustainability and efficient operation of buildings.

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Faculty Supervisor:

Fariborz Haghighat

Student:

Milad Ashouri

Partner:

EnerZam

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Elevate

Simulation of nitrogen and phosphorus losses from native pasture at large spatial scales

Detailed assessments of water and nutrient dynamics in grasslands and its relationship to land management are scarce in the Canadian Prairies. The impact of climate change on these dynamics is even more uncertain. The purpose of this project is to address this knowledge gap by estimating the impact of climate change on water cycling, nutrient dynamics, and management practices in pasture landscapes in Manitoba. The intern in this project will use desktop custom models and state-of-the-art hydrological models to address this research question. This project will generate critical information for beef industry in Manitoba to increase its profitability and sustainability. Besides enabling producers to reduce the financial risks in light of climate change, the outcomes of this project will equip the industry with science-based information to minimize their water and nutrient footprints. Such information is critical to improve environmental sustainability and to garner consumer trust.

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Faculty Supervisor:

Marcos Cunha-Cordeir

Student:

Baiyan Zhou

Partner:

Manitoba Cattle Producers Association

Discipline:

Animal science

Sector:

Agriculture

University:

University of Manitoba

Program:

Multi-Season Assessment of Indoor Microbiome and infectious agents to Manual Shading and Dynamic Glass in a Healthcare Environment

Humans innately understand the concept of comfort. Depending on where you are reading this, in a bright ventilated room with a nice view or a dark office without windows, what you are wearing and how stressful your day has been, you surely have an answer to the question, “Are you comfortable?”. Physical spaces can have meaningful effects on how we feel, how we interact with others, and how we perceive our experiences. Comfort in physical spaces encompasses different facets including thermal comfort, visual comfort, noise nuisance, as well as indoor air quality. Combination of these make a built environment a healthy environment for its occupant. Recently, glass facades have gained popularity not only due to their aesthetic appearance but also because of more day light and connecting the occupants with outdoor environment. In contrast, ordinary windows are often far from optimized, unable to effectively reduce glare and heat, leading to rapid change in indoor thermal environment near the glass façade. A growing body of recent research has been conducted on optimizing design of building envelopes using dynamic (smart) windows, to ensure a trade-off between energy consumption and occupants’ thermal and visual comfort.

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Faculty Supervisor:

Sepideh Pakpour

Student:

Man In Lam

Partner:

View Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of British Columbia Okanagan

Program:

SmartBody, SmartMind: Exploring the effectiveness of an online interoceptive training program on physical and emotional well-being.

SmartBody, SmartMind (SBSM) is a 12-week online intervention combining elements of movement, mindfulness, education, and psychologically-informed coping strategies. SBSM’s philosophy is that there are physical, emotional, and psychological dimensions to all disorders. Accordingly, SBSM offers a variety of therapeutic techniques through a variety of modalities, so that each individual may tailor their own healing. While SBSM’s approach aligns closely with leading edge research on trauma, chronic pain, and other conditions, it has never been formally evaluated. We intend to undertake a clinical trial of SBSM to determine how well it achieves its goals, whether specific individuals benefit more, and whether the program would benefit from any changes. Following completion of the study, the SBSM developers will be provided a report to help them optimize their reach and effectiveness for various disorders and individuals.

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Faculty Supervisor:

Colette Smart

Student:

Jordan Ali

Partner:

Scientuitive Fitness & Wellness Education Inc

Discipline:

Psychology

Sector:

Education

University:

University of Victoria

Program:

Accelerate

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