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
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8841
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9197
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95
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568
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1088
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Projects by Category

Longitudinal Weak Labeling for Lung Cancer Prognosis and Treatment Response Prediction

This project aims at evaluating whether recent results in deep learning models, trained to exploit weak labels (Hwang, 2016) can serve to extract meaningful lesion localizations from image-level labels, either from individual scans or given a (longitudinal) sequence thereof. To this end, we will scale up existing models that have been shown to work on 2D images to a 3D context, studying labeling performance as the dataset size grows. If successful, this work will assert the usefulness of DCNNs to provide a general modeling framework to integrate imaging with other clinical patient data into a predictive system that could help support clinical decisions and ultimately improve patient care.
TO BE CONT’D

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Faculty Supervisor:

Yoshua Bengio;Pascal Vincent

Student:

Partner:

Imagia

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Biotechnology

University:

Université de Montréal

Program:

Accelerate

Retirement Income and Wealth Management Analytics

The Research Group at CANNEX (formerly known as the QWeMA Group) develops solutions for the financial and insurance industry of North America. Our analytics play an important role in determining the value proposition of investment products. Our solutions help the financial community and public through their financial advisors to be able to make informed decisions.
We work at the intersection of finance, mathematics, actuarial science, and computer science. Our main objective of the proposed internship is to use our knowledge of mathematics, optimization, financial modeling, and statistics to discover new investment strategies for retirement as well as address ongoing challenges and difficulties in the industry. Interns will receive an opportunity to put their knowledge to solve a real world problem.

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Faculty Supervisor:

Huaxiong Huang;Alexey Kuznetsov;Thomas Salisbury

Student:

Partner:

CANNEX Financial Exchanges Limited

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Stateful Intrusion Detection using Algebraic State-Transition Diagrams

Increasingly, cyber threats evolve targeting companies, industries and governments. As defense systems are strengthening, threat actors developed new tactics, strategies and techniques to break down security perimeters. Generally, the security of the perimeters are enforced by multiples intrusion prevention and detection tools responsible to provide proactive insights, real-time insights and operational insights for the detection, prevention and mitigation of eventual threatening activities on the monitored system. The performance of such tools depends of the different criteria including detection technique, state awareness, usage frequency and structure. Tools like Snort offer a real-time detection based on rules (or signatures) to detect threatening behaviours from its knowledge base. Snort signatures are expressed in a low-level language that limits the expression of more complex attacks such as advanced persistent threats, distributed and multi-step attacks. They offer basic options for dynamic or stateful analysis, which is necessary to detect aforementioned attacks. TO BE CONt’D

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Faculty Supervisor:

Marc Frappier

Student:

Partner:

Nokia Canada Inc (ON)

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Intelligent Vision Based Navigation Systems

Utilizing geomatics sensors such as laser scanners, GNSS, Inertial Navigation Systems (INS), and photogrammetry cameras to provide mobile mapping solutions has been studied and utilized extensively in the past three decades. The data fusion between high-end mobile mapping systems such as laser scanning and imagery-based systems, and low-cost camera systems are still a fertile field in digital transformation. The anticipated outcome of this project is a software development kit (SDK) that enables data fusion between high-end mobile mapping systems and low-cost camera systems. This SDK will provide multidimensional digital infrastructure information for use in vision-based navigation (VBN) systems. The research could have significant impacts on the fields of LCMM, VBN for indoor navigation/mapping, and self-driving car navigation.

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Faculty Supervisor:

Aboelmagd Noureldin

Student:

Partner:

Micro Engineering Tech Inc.

Discipline:

Engineering

Sector:

Information and Communications Technology; Transportation (excluding aerospace); Automotive

University:

Queen's University

Program:

Accelerate

A Care Management Use Case: Correlation Detection between Dental Claiming Patterns and Overall Cost of Care by Participant

Green Shield Canada (GSC) is going to achieve the capability of data analytics in order to make data-driven decisions in various care management use case scenarios. One of these use cases is to detect specific patterns and associations between dental hygiene and health care costs of the individuals covered by them, predict points of intervention and deliver operational recommendations for its own organization as well as other related ones, such as the patients, health professionals and policy makers, in the form of cost-benefits analysis and other required prescriptions. For this purpose, we use their big datasets including claimants’ information, apply data mining and machine learning methods to find hidden patterns and correlations, predict individuals’ costs related to this specific use case in the future, and provide useful recommendations to GSC.

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Faculty Supervisor:

Saeed Samet

Student:

Partner:

Green Shield Canada

Discipline:

Computer science

Sector:

Finance and Insurance

University:

University of Windsor

Program:

Accelerate

Detection of Fights in Crowd Video

Detection of fights and anomalous behavior of individuals in a crowd is a common problem in computer vision. Some tools that currently exist rely on optical flow of tracked features is a sequence of video frames. These motion algorithms are sensitive to independently moving objects in the frame. What constitutes an “anomaly” is context (eg. location) specific, thereby adding to the complexity. We aim to expand on existing work to create a baseline algorithm which can be used in a general use case, while in parallel investigate the state of the art; and if time permits, tune the algorithm to a specific use case

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Faculty Supervisor:

Viqar Husain;Hong Gu

Student:

Partner:

EhEye

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Dalhousie University; University of New Brunswick

Program:

Accelerate

Advanced Anode Materials for Next-Generation All-Solid-State Lithium Batteries

Advanced batteries are critical for achieving high-performance electric vehicles (EVs) and supporting goals to reduce greenhouse gas emissions. The prevailing rechargeable Lithium-ion batteries (LIBs) using liquid electrolytes, are the major choice for current EVs. However, these LIBs still suffer from safety, lifespan, and energy density issues. Solid-state lithium batteries (SSLBs) have recently emerged as alternative energy storage devices for next-generation EVs due to their ability to overcome intrinsic disadvantages presented by flammable liquid electrolytes, thus solving a major safety issue. SSLBs can achieve greater volumetric energy density and last longer without compromising safety or power, thanks to solid-state electrolytes (SSEs) to replace traditional liquid electrolytes in LIBs. This proposal aims to develop high-performance anodes for next-generation SSLBs that offer improved safety and performance. Metallic lithium and graphite/silicon high-capacity anodes will be applied and optimized for SSLBs. Meanwhile, various novel surface modification methods will be used to address anode/SSE interfaces challenges.

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Faculty Supervisor:

Xueliang Andy Sun

Student:

Partner:

Glabat Solid-State Battery Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of Western Ontario; Western University

Program:

Accelerate

In Vitro Screening and Validation of Phyto-Cannabinoids in Glaucoma

Glaucoma is the second leading cause of blindness in the world, mainly induced by increased pressure in the eye. Marijuana has been shown to reduce such pressure, thus benefit glaucoma patients. In this project, we test several components from marijuana extracts that are unlikely to cause psychoactive symptoms, for their therapeutic effects on glaucoma. This project is likely to be the solid base of a future drug that could help lots of glaucoma patients and meet the need of the market.

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Faculty Supervisor:

Ujendra Kumar

Student:

Partner:

InMed Pharmaceuticals Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Modélisation numérique de l’érosion éolienne sur le parc à résidus de la mine Éléonore et dispersion atmosphérique des poussières

La mine Éléonore est une mine souterraine en cours d’exploitation par Goldcorp Inc. (Baie James, Québec). Cette dernière produit d’importantes quantités de résidus miniers filtrés, en partie stockés en surface dans des parcs à résidus. L’érosion éolienne est un phénomène naturel entrainant le déplacement de particules, fines et grossières, et donc la perte de sol sur un terrain. L’action de vents forts entraine ce phénomène sur les parcs à résidus miniers, peut provoquer l’émission de particules contaminées hors des aires d’entreposage et engendrer des conséquences environnementales et sanitaires majeures. L’objectif de ce stage est de quantifier l’érosion éolienne sur le parc à résidus de la mine Éléonore au cours d’une année. La modélisation numérique du phénomène sera réalisée, après calibration du modèle SWEEP, et permettra d’estimer les particules en suspension, notamment les PM10, pour des évènements venteux journaliers. TO BE CONT’D

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Faculty Supervisor:

Mamert MBONIMPA

Student:

Partner:

GoldCorp Inc (Rouyn-Noranda, QC)

Discipline:

Earth science

Sector:

Mining

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Accelerate

Research for analysis of optical properties of nanohybrid plasmonic devices and their applications

My research has focused on optical nanoantenna-based plasmonics for achieving improved performance in optical applications. Recently, I have researched on energy transfer through nanoantenna waveguides and nanopixel color presenting with nanostructures. I have also systemized the optical setups including EOT/SPR biosensor, plasmonic lithography, and I have working on multichannel imaging system. During the visit, I would like to develop and expand my research to hybrid plasmonics for achieving low-noise and high efficiency plasmon excitation scheme. With the enhanced performance in plasmonics, the designed structures can be applied for advanced optical sensor system such as SERS, efficient energy transfer through nanostructure-waveguide or color presentation in nanopixel. During the visit, my main tasks will be performing the simulation and setting up the optical system for research. I expect to successfully set up the framework for the about 2 research papers under supervision of Prof. Mojahedi even after I come back to Korea.

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Faculty Supervisor:

Mohammad Mojahedi

Student:

Partner:

Pusan National University

Discipline:

Engineering

Sector:

Nanotechnology; Biotechnology; Other

University:

University of Toronto

Program:

Globalink Research Award

Effets des pratiques d’organisation spatiale de la récolte forestière sur la performance financière via une approche de benchmarking

Ce projet de recherche vise à identifier et documenter les meilleurs pratiques de gestion et d’exploitation de la ressource forestière par le biais d’une approche de benchmarking (approche de performance comparé) afin d’améliorer la compétitivité de certains Unités d’aménagement (UA) forestières et de contribuer à assurer la pérennité de l’industrie forestière. Le projet vise à faire une analyse comparée entre les pratiques forestières développés plus au nord de la province en pessière (présence d’épinette noire) avec les pratiques plus su sud de la province sapinière bouleau jaune et érablière. Le but étant d’identifier les opportunités d’implantation des pratiques forestières permettant de diminuer les coûts d’approvisionnement forestier.

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Faculty Supervisor:

Osvaldo Valeria

Student:

Partner:

Rayonier A.M. Canada S.E.N.C.

Discipline:

Earth science

Sector:

Forestry; Natural Resources; Environmental Science and Technology

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Accelerate

LED Radiation Pattern Modelling

Display technology is ever improving; a current display technology being researched and created includes the use of LED arrays. One array could be used to produce a low quality image with minimal energy, while another more energy intensive array would be used for the sharper aspects of the image. Knowing exactly how these LED’s behave and their output on a screen would be most beneficial in furthering this type of display.

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Faculty Supervisor:

Adrian Kitai

Student:

Partner:

Superposition

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

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