Innovative Projects Realized

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

31914 Completed Projects

3006
AB
5256
BC
878
MB
703
NL
913
SK
9488
ON
9949
QC
98
PE
629
NB
1215
NS

Projects by Category

Optimisation de l’aquaculture multitrophique en milieu tropical par l’intégration de la macroalgue Ulva lactuca dans la moulée du poisson marin Pompano de Floride (Trachinotus carolinus)

Les protéines dans les farines et huiles de poissons représentent l’élément le plus dispendieux des moulées commerciales. Son remplacement par une protéine végétale provenant de macroalgues produites dans les eaux de rejets piscicoles diminuerait les coûts associés à la production aquacole tout en réduisant les impacts environnementaux. Les Ulves, comme Ulva lactuca, ont été largement évaluées comme substitut alimentaire. Dans ce projet, nous remplacerons la farine de poissons par de l’Ulva (substitution de 25 %) et évaluerons les effets sur le rendement reproductif du Pompano de Floride, un poisson marin tropical commercialement prometteur. Les géniteurs seront nourris avec la moulée à base d’Ulva, produite dans le système AMTI (Aquaculture Multitrophique Intégrée), puis avec une moulée commerciale (Vitalis), pour comparer la qualité des œufs, à la base d’un bon développement larvaire, entre les 2 régimes. L’ajout d’Ulva dans la moulée du Pompano se refléterait par un rendement similaire ou supérieur à la moulée Vitalis.

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Faculty Supervisor:

Réjean Tremblay

Student:

Partner:

Florida Atlantic University

Discipline:

Life Sciences

Sector:

Technology; Aquaculture and Fishing; Sustainability & the Environment

University:

Université du Québec à Rimouski

Program:

Globalink Research Award

Performance of Fiber-Reinforced Lightweight Self-Consolidating Concrete Columns Reinforced with Glass Fiber-Reinforced Polymer Bars and Spirals under Axial and Eccentric Loads

One of the main interests of the construction industry is the use of innovative materials to facilitate construction, extend service life and minimize maintenance and rehabilitation costs. Lightweight aggregate self-consolidating concrete (LWSCC) can be of great interest for reducing dead loads, section dimensions and project costs, especially for precast elements. Integrating GFRP reinforcement into LWSCC would effectively contribute to producing lighter and more durable concrete members for precast applications. Lightweight concrete is more brittle than normal-weight concrete (NWC). Furthermore, the brittleness of concrete may affect not only the failure mode but also the axial capacity of concrete columns. Adding fiber into LWSCC is an effective way to solve the brittleness of concrete and improve the tensile strength and crack resistance of concrete. This research project aims to develop fiber-reinforced lightweight aggregate self-consolidating concrete (FR-LWSCC) mixes for precast applications
and to provide an experimental work as well as extensive theoretical analysis and design recommendations of RC columns reinforced with FRP bars. The experimental results will be discussed in terms of moment–deflection behavior, flexural capacity, mode of failure, crack patterns, and crack widths.

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Faculty Supervisor:

Brahim Benmokrane

Student:

Partner:

Sym-Tech Béton Préfabriqué Inc.

Discipline:

Engineering

Sector:

Manufacturing and Construction; Advanced Manufacturing; Sustainability & the Environment

University:

Université de Sherbrooke

Program:

Accelerate

Cloud platform of machine learning

Surgical Safety Technologies Inc. is expanding upon its existing OR Black Box® platform, which will allow users of the platform to build a personalized, user-created library of surgical videos in the cloud. There are many people and groups around the world who will use this video library to make sure that performance evaluations are fair and can be done quickly and easily. Among the methodologies used in this project are research on human-computer interaction, video relevance ranking, and business intelligence based on meta-data that comes from the cloud platform. The main goal of the project is to work with existing teams at SST to make prototypes and products that can be used on the cloud, and to make sure that the cloud solution can be used more widely.

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Faculty Supervisor:

Igor Jurisica

Student:

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Neural Networks for Observable Market Data Validation

Observable Market Data is critical for effective valuation of trades for risk management purposes within the investment bank. The valuation process requires the existence of good quality data day by day, and dating back into the mid-2000’s. Not all assets have highly liquid data available either historically or at present, and there is significant interest within the industry in building models to both predict missing data and qualify available data. Historically this process has been highly manual, and due to the volume of data statistical methods are used to identify potentially suspect data. The use of these simplistic methods to gate incoming data results in known blind spots and false positives. This project seeks to use deep neural networks to tackle these two tasks : 1) flagging suspect data efficiently, 2) generating quality data that can be used to improve modeling where real data is unavailable.

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Faculty Supervisor:

Kirill Serkh;Vardan Papyan

Student:

Partner:

CIBC

Discipline:

Computer science

Sector:

Finance and Insurance

University:

University of Toronto

Program:

Accelerate

Assessment and modelling of salmon streams in western Newfoundland

The approach to assessing Atlantic salmon in Newfoundland is based on patterns of salmon production and habitat that were established for populations in rivers much further south. The physical and biological characteristics of watersheds and rivers in Newfoundland are different from the southern rivers and the bases for conservation decisions are likely inappropriate. Establishing relationships between stream physical and biological characteristics that are unique to Newfoundland is prudent for better management of Newfoundland salmon populations.

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Faculty Supervisor:

Robert Scott

Student:

Partner:

Atlantic Salmon Conservation Foundation

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

Memorial University of Newfoundland

Program:

Accelerate

Advancing Gender Equality for Women in Venture Capital – Part 2

Women are vastly underrepresented in venture capital (VC) firms. There is also a lack of women entering the field of venture capital due to systemic barriers and a lack of momentum to shift existing barriers for women to enter the venture capital world. This research aims to understand the current status of women in VC firms, identify structural barriers facing them, and promote gender parity in VC firms and the investing community. The methods include a literature review, in-depth interviews with VC capitalists or senior leaders from VC firms, as well as the creation of an action plan for the partner organizations to drive changes in the investing community.

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Faculty Supervisor:

Wendy Cukier

Student:

Partner:

Ethical Digital;National Angel Capital Organization

Discipline:

Sociology

Sector:

Other services (except public administration); Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Accelerate

Cross-Modal Recipe Retrieval

The goal of cross-modal recipe retrieval is to design systems that are able to find a digital recipe, given the user’s image of the food, or find its image, given its ingredients or cooking instructions. For such a cross- modal retrieval task, a common image-text representation space is needed to embed the semantic information of each modality along with the cross-modal mutual information. With the advent of large- scale datasets, such as Recipe1M, the scalability-accuracy tradeoff of the cross-modal embedding methods has increasingly gained more attention in the last few years. The main goal of this project is to use (and improve) the SOTA cross-modal embedding methods to efficiently retrieve a recipe in a large dataset of recipes with low latency and computational demand, and recommend similar recipes based on the queried recipe.

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Faculty Supervisor:

Scott Sanner

Student:

Partner:

LG Electronics Canada, Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Lifelong learning for service robots

Traditionally, software for home products could not be changed once they were shipped. Furthermore, they could not run complex machine learning (ML) models because their computing and storage capacities are limited due to budget constraints. Recent advancements of cloud infrastructure, however, may allow such products to collect a large amount of data and continuously update the software system throughout their lifetime. Lifelong learning can potentially improve the user experience by making the software system more intelligent and adaptive to specific user preferences. On the other hand, we need to solve problems such as incremental learning, data representation, and catastrophic forgetting. There may also be security and privacy issues associated with processing user data on the cloud.

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Faculty Supervisor:

Animesh Garg

Student:

Partner:

Bosch

Discipline:

Computer science

Sector:

Wholesale trade

University:

University of Toronto

Program:

Accelerate

Multimodal Procedure Understanding

Procedural content (text and video) is abundant on the internet, and is regularly used in our daily lives, e.g., when we follow a cooking recipe to make a dish, or watch an instructional furniture assembly video. Automatically understanding such content allows for the development of various types of AI assistants, including those that can provide answers to our questions (e.g., asking a cooking assistant how much milk we needed in the recipe), and those that can guide users follow through a procedure (e.g., if the user forgets an important step). This project focuses on various aspects of automatically understanding procedural content.

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Faculty Supervisor:

Frank Rudzicz

Student:

Partner:

Samsung Electronics Canada

Discipline:

Computer science

Sector:

Technology; Information and Communications Technology; New and Digital Media

University:

University of Toronto

Program:

Accelerate

Rapid photocatalytic determination of soil organic carbon content: development and validation of protocols

Global warming is a well-known global phenomenon that has been in the headlines for the past few decades. Greenhouse gases (Carbon Dioxide, Methane, Carbon Monoxide, etc.) are the major contributors to global warming and several governments have been working towards limiting such emissions by introducing emission guidelines. Carbon Dioxide is the gas of interest in this research project as recent studies show that Canadian agricultural soils could remove 11.9 million tonnes of CO2 from the atmosphere annually. The intern will be conducting research to investigate analysis techniques for organic carbon in soil through optimizing previous common analysis methods and under multiple real-life conditions to ensure the reliability of the project’s outcome that would enable the readers to explore a new approach for the analysis of organic carbon in the soil, carbon credits, and providing a green sustainable future for the coming generations.

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Faculty Supervisor:

Rafael M. Santos

Student:

Partner:

Mantech

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Guelph

Program:

Accelerate

University of Guelph and IndigenousTech.ai Mentorship Program for Indigenous Youth

IndigenousTech.ai Corporation (IndigenousTech.ai) is is one of the corporations inside of the Forrest Green Group of Companies. All Forrest Green corporations perform web development, solution development, project management and professional services in the technology industry. IndigenousTech.ai has become certified in Ontario and to our knowledge is Canada’s first Indigenous-owned consumer credit reporting agency. IndigenousTech.ai’s mission is to train and hire Indigenous youth on-reserve to increase self-sufficiency, own-source revenue and economic development. To this end, IndigenousTech.ai conducts summer mentorship programs for Indigenous youth focused on financial, digital and accounting literacy. This summer mentorship program is designed to achieve IndigenousTech’s mission described above. Success of the mentorship program requires the contribution from knowledgeable personnel in the fields of technology, business, finance and accounting. This collaboration with the University of Guelph will enable IndigenousTech.ai to conduct a successful Indigenous mentorship program and grow further.

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Faculty Supervisor:

Sara Wick

Student:

Partner:

IndigenousTech.ai Corporation

Discipline:

Business

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Guelph

Program:

Business Strategy Internship

Seleste Western

Seleste is developing an app to integrate with our smart glasses hardware. For this project the intern will help us develop this app which includes two major components. The focus will mainly be the React Native app where the intern will add features to our app and setup our in-house volunteer network for users to call and adding edge ML to our app. Our interface is going to be unique from most since our users are visually impaired and it is incredibly important to create an interface that is simple, accessible and easy-to-use with a screen reader. The second part of the app is adding the ability for guides to remotely take a photo from the glasses. This involves computer networking and sending data from the glasses to the guide using both Wi-Fi and LTE. Both parts of this project will be a core part of Seleste’s IP and value proposition. Successful completion of both parts of this project will allow us to start shipping out our initial pre-order of glasses and run a successful pilot.

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Faculty Supervisor:

Roy Eagleson

Student:

Partner:

Seleste

Discipline:

Computer science

Sector:

Manufacturing

University:

The University of Western Ontario

Program:

Business Strategy Internship

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.