Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

TypeSift Digital Marketing Internship

This particular project is designed to research, understand and validate opportunities to build upon our digital marketing practice. Due to the R&D nature of this project, there will be significant prototyping, testing and verifying of different marketing tactics and channels to learn what best drives business growth, and to then draft our strategic roadmap based on the findings. This engagement is in response to an increasing need for TypeSift to change the way it approaches marketing as the organization currently utilizes direct reach out tactics through sales staff by manually selecting and contacting potential clients that fit our deal Customer Profile (ICP). The intern will be focused on designing, testing and implementing a digital marketing strategy. In order to reach organizations who experience the pain points that TypeSift solves, we need a strong digital presence to reach them, and to reinforce the brand when moving into decisioning on client side. We have a focus on implementing new organizational practices to ensure high impact engagements with potential clients, and change the way our business pursues new engagements.

View Full Project Description
Faculty Supervisor:

Donna Smith

Student:

Partner:

TypeSift

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Business Strategy Internship

Criterium Group – Winter 2022 (Kavya & Jennifer)

Criterium Group will support the Energy Client in transforming operations and determining the most sustainable and economic decarbonization technologies to utilize at The Asset. The Asset site has important characteristics that facilitate bridging to the new technological solutions being pursued as well as beneficial infrastructure, integration, and geological attributes that could improve the feasibility and competitiveness of sequestered CO2 from the site. The intern will support Criterium Group’s team in providing project management and well as project execution (report and business case development) for The Energy Client.

View Full Project Description
Faculty Supervisor:

Martin Halek

Student:

Partner:

Criterium Group

Discipline:

Business

Sector:

Management of companies and enterprises; Professional, scientific and technical services

University:

University of Calgary

Program:

Business Strategy Internship

TMI YOUTUBE Channel Research and Development

Tyson Media is an award-winning Television Production Company based out of Vancouver, British Columbia. We have produced content for Netflix, Amazon Video, OutTV, and Discovery, among others. The company is currently looking to research, invest and create an alternative revenue stream, separate from our major television production projects, in the form of a Youtube channel. Ideally, this project will help the company test the viability and create monetizable models for content development and delivery on the Youtube ecosystem. We will set a budget to deploy a number of test-videos, the intern would help to research, structure and produce content, alongside employees of Tyson Media.

View Full Project Description
Faculty Supervisor:

Todd Newfield

Student:

Partner:

Tyson Media Productions Incorporated

Discipline:

Business

Sector:

Information and cultural industries

University:

Capilano University

Program:

Business Strategy Internship

Correlation of Coronary and Myocardial Strain Profiles for Cardiac Resynchronization Therapy

Cardia Resynchronization Therapy (CRT) is aq pacing therapy used to reduce symptoms and mortality in patients with heart failure. It delivers a specialized pacing lead to the left ventricle (LV) through the coronary veins to re-synchronize the contraction of the heart when it has become delayed or desynchronous. However its benefit has proved to be dependent on the placement of this lead to regions where mechanical delay is maximal and does not have underlying myocardial scar. Medtronic Inc. is developing a software (called CardioGUIDE) aimed at automated segmentation of the coronay veins and analysis of their corresponding strain profile from intra-procedural cine fluoroscopy. This sofgtware may provide an intuitive road-map for the placement of the LV lead to optimal targets/ The aim of this proposal is to develop a validation pipeline for the testring of CardioGUIDE against the gold standard of cardiovascular MRI. Validation will be perfmormed in 60 paitnents receiving both Cardio GUIDE analysis and comprehensive cardiovascular MRI Imaging. This research will allow for clinical validation of this novel CRT lead navigation system and greatly assist in its commercialization asnd clinical dissemination.

View Full Project Description
Faculty Supervisor:

James White

Student:

Partner:

Medtronic of Canada Ltd (Brampton, ON)

Discipline:

Life Sciences

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Calgary

Program:

Elevate

Volatility Modeling

Volatility is an important variable for liquidity management. It is used to time the submission of buy and sell orders and their aggression levels in stock markets, bond markets, and derivatives markets. Volatility is also an important variable in the pricing of derivatives. Market participants will use volatility estimates to improve the quality of their executions. The objective of the project is to further develop a methodology to predict short-term volatility. The project will use machine-learning methods (such as gated neural networks, reinforcement learning, and the like) that have shown promising results in time-series predictions in financial markets.

View Full Project Description
Faculty Supervisor:

Ryan Riordan

Student:

Partner:

TMX Group

Discipline:

Business

Sector:

Finance and Insurance

University:

Queen's University

Program:

Business Strategy Internship

Automated fetal anatomy identification to improve quality of obstetrical ultrasound

Abnormal fetal growth is a leading cause of perinatal mortality and morbidity in both developed and developing countries. Fetal growth is primarily assessed by ultrasound due to its low risk, low cost, and wide availability. These studies are cognitively intense for a reporting radiologist and errors can have significant long-term implications. In this study, we will train a novel deep learning algorithm to detect fetal body parts to improve quality in ultrasound reporting according to the Canadian Association of Radiology standard. We first develop a novel, large dataset for classifying obstetrical ultrasound images by body part and grading quality. Next, we develop a deep learning algorithm to detect fetal body parts present in 2D ultrasound image and grade quality. Finally, we will integrate this tool and evaluate impact on radiologist workflow.

View Full Project Description
Faculty Supervisor:

Dafna Sussman

Student:

Partner:

Trillium Health Partners

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

Toronto Metropolitan University

Program:

Accelerate

Developing a nanoparticle platform for cell-free protein engineering

This project aims at developing a nanoparticle-based technology that will allow us to engineer and screen proteins for catalytic activity in a cell-free environment. The proposed method will be faster and robust compared to conventional protein engineering techniques. This will be achieved by combining cell-free protein systems (CFPS) and magnetic nanoparticle (MNP) to make screening of protein activity easier. Finally, we aim to develop a method that can be adapted for various protein activities. Galenvs aims at commercialising this technique and make it readily available for various applications. The research exchange will result in a PhD thesis project and impart essential skills required in biotechnology industry. The intern will receive training in an industry setting and will learn k y techniques such as MNP synthesis and characterisation, CFPS, development of assays, and next-gen sequencing.

View Full Project Description
Faculty Supervisor:

David Kwan

Student:

Partner:

Galenvs

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Portrait de l’Avena fatua L. au Québec : moyens de lutte et proposition de changement de pratiques chez les producteurs de blé de printemps (Triticum aestivium L.)

La présence de folle avoine dans les cultures de blé entraine des pertes de rendements, de qualité de la farine, des coûts et des difficultés pour le battage et le criblage. Pour lutter contre la folle avoine, les agriculteurs en agriculture conventionnelle utilisent des herbicides, d’autres en agriculture biologique, n’en utilisent pas. Des pressions sociales s’exercent sur les agriculteurs en agriculture pour utiliser moins d’herbicide. Malgré les guides agricoles et les pressions sociales, l’usage des herbicides augmente. Le problème est que de simplement informer les agriculteurs sur les pratiques agricoles à faible usage d’herbicide ne suffit pas, car le choix de pratiques agricoles reposerait aussi sur des interactions sociales et des valeurs. L’objectif général du projet est d’évaluer des méthodes de lutte contre la folle avoine en grandes cultures conventionnelles et biologiques de blé de printemps en cohérence avec les engagements sociaux et les valeurs des agriculteurs.

View Full Project Description
Faculty Supervisor:

Yosra Menchari;Marie-Josée Simard

Student:

Partner:

La Meunerie La Milanaise;Les Moulins de Soulanges inc

Discipline:

Earth science

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

A deep learning time-series approach for liana and tree classification from terrestrial LiDAR point clouds

Lianas are woody climber plants with a relatively thicker stem that use trees as structural support to reach the forest canopy. They compete with trees for above and below ground resources, and they also occupy gaps and illuminated areas on the upper part of the canopy more efficiently. Therefore, their increases can suppress tree generation, promote tree mortality, and decrease tree growth, thereby affecting the whole forest carbon sequestration. Terrestrial Laser Scanning (TLS), also named terrestrial Light Detection and Ranging (LiDAR) is an active remote sensing method than can generate clouds with million points to describe three-dimensional structure of vegetations in high accuracy. Also, recent advances in deep learning algorithms provides us an excellent oppotunity to understand forest structure, since the performance of deep learning algorithm is always better than traditional machine learning algorithm, when it comes to data-intensive programs. This project aims to explore the utilization of deep learning for liana and tree classification based on TLS data. We want to develop an automatic deep learning algorithm to separate liana from its host tree, with high accuracy. The presented approach can facilitate more studies to investigate the impact of lianas on the structure and dynamics of forests.

View Full Project Description
Faculty Supervisor:

Gerardo Arturo Sanchez-Azofeifa

Student:

Partner:

Ghent University

Discipline:

Earth science

Sector:

Education

University:

University of Alberta

Program:

Globalink Research Award

Graph representations for aggregate insurance risk modeling and prediction

As a reinsurer, the partner organization backs risky and/or high face-value policies that are otherwise detrimental to insurance companies to underwrite. However, currently the available information on the policyholder is based on prior information stored in the company databases and on previous policies held or claims administered and/or what is presented on the forms provided to the partner organization underwriters. As such, the risk visibility to underwriters is minimal and does not allow underwriters to accurately gauge on how incoming policies can be priced. Underwriters, in general, view risks in different settings: family, occupation, physical activities, demographical and geographical. For instance, if members of a family are applying for high-value life insurance policies, underwriters would like to know that as a family, what is the accumulated risk of life insurance payout should anything happen? How are the different policyholders linked to each other (relationships, living at the same address, working at the same company, company risk profile, etc.)? Is a particular applicant engaging in risky physical activities (e.g., skydiving, parkour, etc.) that is otherwise not stated in the applications? Is the policyholder living in an area of high crime statistics?

View Full Project Description
Faculty Supervisor:

Carson Leung;Lorenzo Livi

Student:

Partner:

Munich Re

Discipline:

Computer science

Sector:

Finance and Insurance

University:

University of Manitoba

Program:

Accelerate

Jacques Cartier Bridge Forged Pin Testing and Analysis

Fatigue damage and corrosion are of significant concern in bridge structures and can have grave consequences on public safety. In addition, bridge structures, such as the Jacques Cartier Bridge, that were built in the early 20th century can be more susceptible to damage as the bridge structures were not designed for current traffic load and fatigue considerations. The Jacques Cartier Bridge is a transportations infrastructure of Canada with more than 90 years of age and is exposed to deicing salt, moisture, and extremely cold weather. For these reasons, a comprehensive inspection and maintenance program is of great benefit to ensure the safety of the JC Bridge and Canadians. In this regard, the present study aims to improve the safety of the bridge by estimating the risk of failure by brittle fracture or significant fatigue crack growth and determining the critical defect (i.e., crack) size to be used in suitable non-destructive evaluation (NDE) techniques. This project contains detailed metallurgical analysis, materials, and fatigue tests combined with finite element (FE) analysis and advanced fracture mechanics methods to ease and improve the existing inspection methods of the Jacques Cartier Bridge.

View Full Project Description
Faculty Supervisor:

Scott Walbridge

Student:

Partner:

JCCBI

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Waterloo

Program:

Accelerate

Deep Breathe: Developing and integrating deep learning strategies to automate and augment the interpretation of lung ultrasound images

Project Deep Breathe seeks to develop computer vision solutions that will aid in the use of lung ultrasound technology to accurately and easily diagnose lung conditions anywhere these portable machines can be brought. This will be done using large amount of lung ultrasound data at Western University and by employing artificial intelligence students from the University of Waterloo. The partnering organization – Alveolai Data Fuel – stands to benefit through possible commercialization of the resultant intellectual property from these research efforts.

View Full Project Description
Faculty Supervisor:

Alexander Wong;Robert Arntfield

Student:

Partner:

Deep Breathe

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Previous
1…1,4071,4081,4091,4101,4111,4121,413…2,473
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe