Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

2811
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4990
BC
801
MB
663
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825
SK
8841
ON
9197
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95
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568
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1088
NS

Projects by Category

Big Data Processing and Analysis

Addictive Mobility is a leading (Big Data) online advertising company in Canada. They use real-time bidding (RTB) platform for online display advertising in mobile devices, where multiple companies compete to show a certain Ad to a specific user at a certain time. The goal is to optimize the system such that they minimize the cost over the campaign period but also send targeted ads to maximize return on investment such as number of clicks or purchases. Massive number of data, which they collect as a result of Ad exchanges, calls for tools such as data visualization, data mining and machine learning methods, which can help to make sense of Big Data. Maximization of return on investment requires learning user behavior from the massive collected data to show the Ad that will maximize the probability of user interaction, and that’s a pure machine learning and optimization problem. Enhancing this process is at the core of the business, and will highly affect the company’s reputation and return.

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Faculty Supervisor:

Anthony Bonner

Student:

Partner:

Addictive Mobility

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Software Tools for Discovering Quantum Computing Applications (Differential Equations Focus)

A lot of industries rely on solving complex mathematical problems to improve their processes and design their products. Non-linear differential equations are often essential for making advancements. However, solving these equations with traditional computers is extremely challenging and resource intensive. Current computing methods struggle with these complex equations, leading to high energy use, long development times, and suboptimal design.
One promising avenue for solving these problems is quantum computing which might eventually be able to solve these complex math problems far more efficiently. The challenge is that the development of quantum algorithms and software to support this development is lacking. Solving non-linear differential equations. has received far less attention than applications like quantum simulation. This project aims to build software to develop quantum algorithms for non-linear differential equations. The outcome of this work will be the capability to assess the promise of quantum computing for differential equations solving.

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Faculty Supervisor:

Nathan Wiebe;Artur Izmaylov

Student:

Partner:

Zapata Canada

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

An Update on Stigmatizing Language within the Substance Use Spectrum

Our project addresses a critical issue within the realm of substance use: the pervasive stigma that extends across the entire spectrum of use. By expanding our focus beyond the severe range, which is often the primary focus in research and policy, we aim to identify and understand the stigmatizing language and experiences faced by individuals at various points in the substance use spectrum— including those with no use, beneficial use, and at-risk use. In collaboration with CAPSA, we will conduct inclusive focus groups to gain insights into the stigma individuals encounter and explore actionable strategies for reducing it. By examining the origins of stigma beyond the severe range of substance use, we aspire to uncover its roots and, in turn, support individuals across the entire spectrum of substance use.

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Faculty Supervisor:

Kim Hellemans

Student:

Partner:

CAPSA

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

Carleton University

Program:

Accelerate

Multiphysics Modelling of Low Temperature Urea Injection in Selective Catalytic Reduction Reactor

Based on a thorough literature review in the related research areas, the student will create a 3D COMSOL model to simulate the SCR system for the partner organization. The simulation will be combined with experimental testing on the SCR system, with the goal of optimizing the low exhaust temperature operations of the SCR reactor specifically in reducing the urea deposits formation and the load input from the engine. The partner organization is expected to have benefits including significant savings in experimentation costs, a comprehensive simulation model of the SCR reactors with time-dependent chemical reactions and multiphase flow, and potential product optimization suggestions based on the findings of the project.

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Faculty Supervisor:

Pierre Sullivan

Student:

Partner:

Safety Power Inc.

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Communications intern working within cross-functional teams to develop and commercialize AI-powered solutions in the Public Services sector

AltaML builds artificial intelligence (AI)-enabled solutions to business problems. We work with organisations, bringing together their data and domain expertise with our AI expertise, to develop AI solutions that are deployed in their operations. We also commercialize AI-enabled products business via industry-specific ventures, yielding scalability from our investment in the first solution.
Competition for tech talent is fierce, and our talent strategy includes a talent accelerator program, designed to rapidly equip highly qualified individuals with hands-on work experience in applied AI while providing partners with continuous and cost-effective development of AI solutions. AltaML’s AI Lab for Government, also known as GovLab, is a talent accelerator for public service professionals, post-secondary students and recent graduates. GovLab.ai’s mission is to set a global example of how to transform the public sector through applied AI, and is designed to encourage the growth of technical and business AI skill sets that are in high demand across Alberta and around the world.
The communications intern will be primarily engaged in developing and executing a comprehensive social media strategy plan aimed at showcasing the AltaML team culture, fostering engagement, and highlighting key projects and achievements. They will also take the lead in graphic development and production design initiatives to enhance the visual identity and brand recognition of AltaML & Ventures across various platforms. Additionally, the intern will be responsible for creating compelling and informative content to be disseminated through various channels, including blog posts, newsletters, and social media updates, to effectively communicate the organization’s mission, values, and initiatives. In addressing these activities, the intern aims to tackle challenges such as enhancing brand visibility and recognition in a competitive market, cultivating a cohesive team culture in a distributed work environment, and ensuring consistent engagement and interaction on social media platforms. By executing these tasks, the intern anticipates benefits such as increased brand awareness and recognition among target audiences, strengthened team cohesion and morale, enhanced visual identity and brand consistency, and improved communication and storytelling capabilities, all of which will contribute to the overall success and growth of the partner organization(s). Finally, the intern will play a key role in the planning and development of our event planning as we look to regularly host a series of Innovation Showcase events moving forward. Unlike previous Communications associates (IT 34306) who mainly focused on the development of internal communications, this intern will have a unique opportunity to work with both AltaML and our newly revamped Venture Studio, and will work to both enhance current strategies and develop new ones, depending on the stage of the business/specific internal client they are working with. These newly developed strategies centered around brand awareness, technological innovation, effective storytelling, will play an integral role in the future success and on-going development of our business, especially those on the Venture Studio side as many of them have little to no strategy in terms of Marketing & Communications. For this upcoming term/project, the intern will be focused moreso on the execution and continuous improvement of various larger-scale Marketing and Communications initiatives (GovLab Impact Report, Innovation Showcase, etc), that we anticipate will improve our recognition and awareness in the industry while ensuring we are actively and regularly engaging with the tech ecosystem as a whole.

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Faculty Supervisor:

Michael Maier

Student:

Partner:

AltaML

Discipline:

Business

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program:

Business Strategy Internship

Design and Implementation of a Type System for Enhanced Mathematical Operations in Rings

The project “Design and Implementation of a Type System for Enhanced Mathematical Operations in Rings” aims to develop a Java library with a straightforward application programming interface (API) that simplifies complex mathematical computations within rings, including solving matrix equations.
While this library is designed as a part for the bigger research project called “Symmetric system for message exchange protocol based on the ring surjection”, its utility extends beyond, serving as a versatile tool for any application requiring efficient, accurate, and memory-effective mathematical computations in rings. The library stands out by providing streamlined error handling and performance optimizations, enabling developers across various fields to integrate sophisticated mathematical functionality into their projects without delving into the complexities of the underlying operations.

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Faculty Supervisor:

Werner Dietl

Student:

Partner:

Taras Shevchenko National University of Kyiv

Discipline:

Computer science

Sector:

Cyber Security; Other

University:

University of Waterloo

Program:

Globalink Research Award

Assay and Portable Device for the Assessment of an ALS Biomarker

A PhD student from the IMDEA Nanoscience research institute in Spain will travel to Canada for an internship at the University of British Columbia. This internship will initiate a new collaboration to develop materials, methods, and devices for detecting a protein malfunction in white blood cells that reflects the emergence of the neurodegenerative disease, amyotrophic lateral sclerosis (ALS). This disease affects hundreds of thousands of people, has a poorly understood cause, and no cure. The proposed research will create a way of imaging the protein malfunction within blood cells, as a mirror for what is occurring in brain cells during ALS onset, using a smartphone and brightly fluorescent nanoparticles. The internship will enable an effective exchange of knowledge between one group with the resources and expertise for studying ALS biology (Spain) and one group with the tools and expertise for creating the nanoparticles and imaging device (Canada), enabling advances that would not be possible with the collaboration. The technology developed as an outcome of this internship and collaboration will be an important step toward an accessible, effective, and earlier diagnosis of ALS, and will be a valuable tool for searching for and evaluating potential therapies and drugs for ALS.

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Faculty Supervisor:

Russ Algar

Student:

Partner:

IMDEA Nanociencia Institute

Discipline:

Physics

Sector:

Education

University:

The University of British Columbia

Program:

Globalink Research Award

Planifier des interventions des espèces végétales exotiques envahissantes du mont Saint-Bruno

Les espèces végétales exotiques envahissantes (EVEE) ont été identifiées comme étant une menace majeure à la biodiversité du mont Saint-Bruno, une colline montérégienne abritant des milieux naturels d’importance pour la communauté métropolitaine de Montréal. Depuis 2019, la Sépaq, gestionnaire du parc national du Mont-Saint-Bruno qui protège la moitié de ces milieux naturels, a initié des mesures de contrôle d’EVEE. Cependant, aucune donnée ou plan d’intervention d’EVEE est prévu pour la zone périphérique qui comprend des terres publiques et privées, compromettant l’éventuel succès des efforts en cours. Notre projet vise à combler cette lacune en effectuant une cartographie détaillée de l’occurrence de sept EVEE ciblées et en effectuant une revue de littérature et une consultation avec personnes expertes pour identifier les meilleures techniques de contrôle selon l’espèce et le niveau de menace établi. Ces connaissances serviront à produire un plan d’intervention et son plan d’action 2025-2027 pour mobiliser tous les acteurs du milieu à contrôler les EVEE du mont Saint-Bruno avec une vision concertée.

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Faculty Supervisor:

Ira Tanya Handa;Daniel Kneeshaw

Student:

Partner:

Fondation du Mont-Saint-Bruno

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Université du Québec à Montréal

Program:

Accelerate

Big Data Processing and Analysis

Addictive Mobility is a leading online advertising company in Canada. The success of ad campaigns drives the majority of the company revenue. Exploring advanced machine-learning techniques to efficiently control an ad’s performance is crucial to the company strategy. The objective of the proposed project is to optimize the real-time bidding system in the sense that delivery has been carried out in real-time and within a time-interval of 100 ms. As we mentioned, this problem is highly complex and we can break it into several subproblems each of which can be a major area in machine learning.

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Faculty Supervisor:

Anthony Bonner

Student:

Partner:

Addictive Mobility

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

The Columbia Valley Community Renewable Energy Project

The proposed research will review and evaluate the renewable energy options available for both energy production and carbon dioxide mitigation in the Columbia Valley and how to implement the preferred solution at the community level. The research aims to review relevant academic literature and Canadian case studies, consult with local stakeholders, provide quantitative analysis (e.g., levelized-cost-of-energy, cost-effectiveness analysis) of options, provide qualitative analysis of options where quantitative analysis is not possible, and make
recommendations regarding the options

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Faculty Supervisor:

Walter Merida

Student:

Partner:

Economic Trust of the Southern Interior;Columbia Valley Community Economic Development

Discipline:

Engineering

Sector:

Sustainability & the Environment; Energy and Utilities; Clean Technology

University:

The University of British Columbia

Program:

Accelerate

Machine Learning developer and Product interns working within cross-functional teams to develop and commercialize AI-powered solutions in the Public Services sector (1)

“THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW”

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Faculty Supervisor:

Norah McRae

Student:

Partner:

AltaML

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Waterloo

Program:

Business Strategy Internship

Advancing Gene Expression Microarray Analysis: Assessing and Enhancing the Linear Combination Test Through Integration with Machine Learning Tools

Understanding which genes are involved in diseases is incredibly important because it helps us develop better treatments. By identifying these genes, scientists can better understand how diseases operate in our bodies and create more effective treatments. This also allows for the creation of personalized treatments based on a person’s unique genes, increasing their chances of recovery. However, finding these genes is a difficult task as there are thousands of genes in the human body and vast amounts of genetic data to sift through. This project aims to enhance a method called the Linear Combination Test (LCT) and use machine learning tools to optimize further its ability to identify disease-related genes, such as those responsible for COVID-19 and cancer. In the second step of this project, the improved LCT will be tested on real-world data to gauge its effectiveness. Additionally, user-friendly software tools will be designed to make it simple for other scientists to use. Our ultimate goal is to help find cures and improve the lives of those who suffer from diseases.

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Faculty Supervisor:

Irina Dinu

Student:

Partner:

INSA Lyon

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

University of Alberta

Program:

Globalink Research Award