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

Machine learning modelling of temporal enterprise data

In a few words, this is a fintech data analysis project. The idea is, given temporal data of financial nature, to build algorithms that predict its evolution over time. For instance, the data could be certain assets prices, or customer buying history. The objective would be to respectively predict this asset price in a close future, or to anticipate what the customer wants to buy next and make relevant recommendations. Such algorithms belong to the family of machine learning algorithms. In the last years, machine learning has been of keen interest to the worldwide scientific community, as a sub-branch of machine learning named deep learning has seen considerable algorithmic progress. This project would leverage recent and efficient deep learning methods.

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Faculty Supervisor:

David Duvenaud

Student:

Mathieu Ravaut

Partner:

Layer 6 AI

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

Technical and Economic Assessment of Implementing UV Treatment in Potable Reuse Process Trains

Driven by climate change induced water scarcity, further enhanced by rapid urbanization and population growth, potable water reuse initiatives are gaining interest. Potable reuse involves the indirect or direct use of highly treated municipal wastewater as a municipal drinking water source. Historically, the most commonly installed potable reuse train consisted of microfiltration, reverse osmosis (RO), and ultraviolet (UV) as treatment stages. Today, in many non-coastal geographies, non-RO based alternative advanced water treatment trains such as ozone-biological activated carbon (BAC) are being evaluated. UV plays a significant role in potable reuse trains because of its capability to inactivate pathogens up to 6-log. Thus, given the multiple reuse treatment trains where UV plays an essential role, there is a need to minimize the UV energy consumption and maximize the performance depending on the various upstream treatment trains. TO BE CONT’D

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Faculty Supervisor:

Ajay Ray

Student:

PANKAJ CHOWDHURY

Partner:

Trojan Technologies

Discipline:

Engineering - chemical / biological

Sector:

Natural resources

University:

Program:

Elevate

Optimization of astaxanthin production in large-scale cultivation of microalgae by utilizing industrial CO2 emissions

Haematococcus pluvialis is a green microalga that concentrates the compound astaxanthin, a commercial product with nutraceutical, pharmaceutical, cosmetic, aquaculture, and food applications. Astaxanthin is a carotenoid pigment with high antioxidative activity, used as a feed additive to provide a characteristic pink color to salmonids and shrimp, as well as a human nutraceutical providing protection from oxidative stress.
Maximizing large-scale biomass production rates and enhancing astaxanthin concentration in algal cells grown by capturing industrial carbon dioxide (CO2) emissions are the main objectives of this research study. TO BE CONT’D

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Faculty Supervisor:

David Allen

Student:

Nekoo Seyedhosseini

Partner:

Pond Technologies Inc

Discipline:

Engineering - chemical / biological

Sector:

Forestry

University:

Program:

Elevate

Knowledge Intensive Processes Representation and Analysis: Process-Aware Work-Graphs and Predictive Approaches

Processes are important concepts in modern society since they control and standardize the interactions between businesses, consumers, governments and other organizations. However, the rise of knowledge-based industries such as financial services, healthcare, advanced manufacturing and software development have produced unstructured and knowledge-dependent processes. These Knowledge Intensive Processes (KIPs) KIPs range from partially structured to unstructured processes and require some control and standardization while guiding but not completely constraining knowledge workers’ actions. This interplay between providing agility and control promotes the emergence of complex work-graphs, which gather cross-cutting processes, tasks, people, information, rules and supporting software systems. Current challenges include representing process abstractions and defining methods for predicting process analysis. TO BE CONT’D

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Faculty Supervisor:

Paulo Alencar

Student:

Glaucia Melo

Partner:

Centre for Community Mapping

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

CRISPR-Cas9-based screening and engineering of novel biologics to target the vulnerabilities of primary and recurrent glioblastoma

Glioblastoma (GBM) is the most common primary adult brain tumor. Even with surgery, standard chemotherapy, and radiation, tumor recurrence and patient relapse are inevitable with a median survival rate of <15 months. The overall goal of this proposal is to identify new targets for treatment by using cutting edge CRISPR technology to screen for molecular interactions in GBM. Identification of new therapeutic targets that drive GBM that is resistant to current treatment will allow us to continue our work toward developing novel immunotherapies that harness the immune system and target specific cell surface receptors on GBM cells. Our ultimate goal is to undertake preclinical evaluation of novel potential therapeutic antibodies using our unique animal model of human GBM recurrence. Promising lead targets and novel therapeutics will be translated into early clinical development at the partner organization, CCAB, and its network of industry partners and start up companies with the hope of generating novel targeted therapies to GBM

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Faculty Supervisor:

Sheila Kumari Singh

Student:

Chirayu Chokshi

Partner:

Centre for the Commercialization of Antibodies and Biologics

Discipline:

Medicine

Sector:

Medical devices

University:

Program:

Accelerate

Lateral resistance of Midply walls used as infills in Japanese Post and Beam Construction

Midply walls have higher lateral resistance than traditional light wood frame shear walls, by creating double shear in fasteners and having larger edge distance. There is also a potential to use Midply wall as infills in Japanese Post and Beam construction, in order to improve the seismic performance of the current system. Little research has been done in this area. The proposed project will investigate the effect of different fasteners, stud material, and sheathing thickness on the behavior of Midply walls. Then the Midply wall will be integrated into Post and Beam shear wall system and the new system will be tested under monotonic and reverse cyclic loading A database and a design guide will be delivered to help engineers use Midply walls in Post and Beam construction.

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Faculty Supervisor:

Frank Lam

Student:

Zhen Liang

Partner:

Norbord Inc

Discipline:

Forestry

Sector:

Manufacturing

University:

Program:

Accelerate

Leaching of chemical elements from Canadian Natural Oceanic Clay

This objective of this research is to investigate the properties of Oceanic Natural Oceanic Clay harvested by the Iron wood Clay Company in British Columbia, Canada. When the clay is applied to the skin, various cations and positively charged impurities on the skin can be removed by ion exchange mechanism. However, the clay materials can be both collectors and donors. It is likely that various elements are leached out from the clay material surfaces under different conditions that may interact with skin surfaces and cause irritation. For the subsequent fully understanding of the interactions of the clay with skin surfaces, it is critical to firstly assess what elements can be leached out and under what conditions they can be leached out, which is the focus of the current study.

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Faculty Supervisor:

Wenying Liu

Student:

Mohsen Hashemzadeh

Partner:

Ironwood Clay Company Inc

Discipline:

Engineering - other

Sector:

Natural resources

University:

Program:

Accelerate

Using commitment to reduce plastics waste in the marine environment

Given that plastic pollution in the marine environment has been a critical issue in Canada and in the rest of the world in recent decades, our project aims to provide a possible solution to mitigate plastic waste in the ocean. Previous findings have shown that asking people to make a commitment can effectively change their behaviours. In the current, we will ask people to make a commitment by signing a pledge to reduce their plastic waste. We hypothesize that people who signed the pledge will show a reduction in their plastic waste disposal, compared to those who did not sign. Thus, by reducing plastic consumption can eventually lead to a reduction of plastic waste in the ocean.

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Faculty Supervisor:

Jiaying Zhao

Student:

Yu Luo

Partner:

Ocean Wise

Discipline:

Psychology

Sector:

Environmental industry

University:

Program:

Accelerate

The Opportunity Equation

The Opportunity Equation is a multi-year research project that explores trends, dynamics and causes of income inequality in the Greater Toronto Area (GTA). The project aims to produce a comprehensive portrait of the changing income distribution and income gaps among key socio-demographic groups in the City of Toronto, York Region and the Region of Peel between 1980 and 2015. It looks beneath aggregated measures on inequality to investigate how much of an income gap exists among various socio-demographic groups and how these gaps change over time. Examining the income trajectories of different socio-demographic groups provides insights into the social factors structuring income distributions and in turn the basis of income inequality. This report will provide the most in-depth and up-to-date analysis of income gaps among different socio-economic groups in the GTA, using the most reliable data currently available.

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Faculty Supervisor:

Gabrielle Slowey

Student:

Benjamin Johnson

Partner:

United Way of Toronto & York Region

Discipline:

Political science

Sector:

Management of companies and enterprises

University:

Program:

Accelerate

Investigating wildlife-road interactions in the Chignecto Isthmus Region

Roads threaten wildlife throughout the world when animals experience increased collisions with vehicles and decreased access to important habitat and resources. This research will investigate where animals are crossing roads in the Chignecto Isthmus of Nova Scotia, a region highly impacted by human development. The results will provide evidence for hotspots of negative wildlife-road interactions, with the goal of recommending effective changes to road infrastructure for the benefit of both animals and humans. The results will also help the Nature Conservancy Canada to better understand where wildlife are moving through the isthmus as they disperse between Nova Scotia and New Brunswick.

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Faculty Supervisor:

Karen Beazley

Student:

Amelia Barnes

Partner:

Nature Conservancy Canada

Discipline:

Environmental sciences

Sector:

Environmental industry

University:

Program:

Accelerate

Flexible Data Reader on Distributed File Systems for Training Deep Learning Algorithms

With the fast-growing size of machine learning datasets, it has become increasingly important to store them in a reliable and distributed manner. Large scale distributed file systems such as GFS, HDFS and Amazon S3 have the capability to store large scale of data reliably. However, these distributed file systems have an intrinsic shortcoming: they provide good read/write access guarantees only for large size files, and therefore cannot efficiently handle frequent read/write operations for large number of small files. In machine learning training protocols, the ability to shuffle data points within a dataset is crucial to avoid local minima and overfitting, which requires the data points to be accessed in a random manner, preferable efficiently. The main focus of this project is to find a way to store machine learning datasets on distributed file systems while maintaining a competitive randomly reading performance for shuffling data points. TO BE CONT’D

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Faculty Supervisor:

Yashar Ganjali

Student:

Hongbo Fan

Partner:

Uber Advanced Technologies Group

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

Modification of Sludge Based Activated Carbon for nutrient removal in stormwater runoff through rain garden growing medium

Pollutants in stormwater runoff and municipal wastewater are grave concerns to the receiving environment of lakes and streams, as nutrients (Phosphorus (P), Nitrogen (N)) contribute to eutrophication. While rain gardens are effective to retain and retard stormwater runoff and removal of certain organic pollutants, limited studies have been conducted on nutrient capture.
This research focuses on waste-to-resource for nutrient removal from aqueous environments. While other sorbents are available, activated carbon produced from sewage sludge (sludge-based activated carbon (SBAC)) has the potential to be a more sustainable option as the negative environmental impact from its disposal process will be eliminated. In this proposed work, the chemical activation condition of production of SBAC will be optimized from previous research, including the selection of chemicals and chemical concentration. TO BE CONT’D

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Faculty Supervisor:

Loretta Li

Student:

Dijia Wu

Partner:

Kerr Wood Leidal Associates Ltd.

Discipline:

Engineering - civil

Sector:

Environmental industry

University:

Program:

Accelerate

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