Innovative Projects Realized

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

30508 Completed Projects

2882
AB
5105
BC
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projects by Category

Energy Efficient 360 Video Processing for Portable VR-Technologies

This project focuses on the energy consumption of modern virtual reality applications. The target devices are virtual-reality-glasses that can be worn on the head and that simulate a virtual 3D environment to users. Most modern devices are still rather heavy, uncomfortable to wear, and attached to a powerline such that the user experience can still be enhanced. In this project, the goal is to make the glasses require less power and energy during operation such that the operating time and battery requirements can be minimized. For the partner organization, being able to provide such a solution to users would be a unique selling point for their products as the glasses can be made lighter, more comfortable, and do not need a power cable.

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Faculty Supervisor:

Stéphane Coulombe;André Kaup

Student:

Partner:

Summit Tech

Discipline:

Engineering

Sector:

Information and Communications Technology; Entertainment and Media; Energy and Utilities

University:

École de technologie supérieure

Program:

Accelerate

Crystallization and mechanism of action studies of antibody NB0940 binding to Poliovirus receptor

Significant advances in technologies related to antibody discovery and development have allowed therapeutic antibodies to become the fastest growing class of biopharmaceuticals over the last 20 years. Northern Biologics is a biotechnology company that seeks to develop therapeutic antibodies for the treatment of cancer and fibrosis. Together with Dr. Jean-Philippe Julien at SickKids (University of Toronto), the intern will work with Northern Biologics to develop and characterize antibodies against cellular receptors that show aberrant signaling in several diseases including cancer. Integrative structural biology and biophysical technologies will be used to inform lead selection with the goal of progressing therapeutic candidates for clinical trials.

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Faculty Supervisor:

Jean-Philippe Julien

Student:

Partner:

Northern Biologics Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Tagging and Auto-Captioning of Histopathology Scans for Diagnosis Assistance

Digital pathology uses modern scanners to capture high-resolution images from biopsy samples. Computer algorithms, especially artificial intelligence, can help in automatic searching for similar cases in the archive of hospitals and laboratories. Displaying similar images form the past patients, that have already been diagnosed and treated, can provide useful information to the pathologist to solidify the final diagnosis. These images, however, are very large such that their processing requires smart algorithm to distinguish between relevant and irrelevant information. In this project, we develop novel methods for identification and auto-captioning of the pathology scans to assist clinicians in their daily work. Tagging technologies using AI will be developed to index and smartly archive the images. This enables fast and accurate search for similar cases. Besides, the identification of already diagnosed cases (which are accompanied by pathology report) enables the algorithm to generate a caption for the new scans. This should help shorten the processing times by drawing attention to the critical cases.

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Faculty Supervisor:

Hamid R Tizhoosh

Student:

Partner:

Huron Digital Pathology

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

University of Waterloo

Program:

Accelerate

Deep Generative Modeling of Character Animation

The goal of this research project is to develop novel techniques to solve different tasks for character animation using deep neural networks and generative modeling. Namely, we wish propose a novel approach for transitions generation, in which clips of character animation can be linked together with a novel clip. This transition will be generated by a specifically designed recurrent neural network that should make use of recent advances in adversarial learning in order to produce realistic animations. We also want to tackle the problem of key-frame interpolation, where we want to improve the current techniques of motion smoothing and interpolations by learning a dense pose manifold that takes into account complete character configurations in order to only produce valid poses while interpolating.

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Faculty Supervisor:

Christopher Pal

Student:

Partner:

Ubisoft Toronto

Discipline:

Computer science

Sector:

Entertainment and Media; Technology; Other

University:

École Polytechnique de Montréal

Program:

Accelerate

Exploring various approaches for investigating the mechanism of native diphtheriae toxin production by a C. diphtheriae strain: From –omics to nutritional to process approaches

Diphtheria is still a disease causing significant morbidity and mortality in people worldwide that did not received vaccination or suffer from incomplete immunization. The disease is due to a powerful toxin produced by the pathogenic bacterium Corynebacterium diphtheria. A good vaccine already exists but its production is rather complex and involves several steps: cultivation of the microorganism, extraction, concentration and inactivation of the toxin followed by extensive purification of the inactivated toxin (toxoid). Much research is still needed in order to increase the vaccine yield, this, to permit a significant reduction in production costs and to deliver a more reproducible and robust production process. Success will translate into a more affordable vaccine for people, especially people in underdeveloped countries. TO BE CONT’D

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Faculty Supervisor:

Denis Groleau

Student:

Partner:

Sanofi

Discipline:

Life Sciences

Sector:

Pharmaceuticals; Biotechnology; Technology

University:

Université de Sherbrooke

Program:

Accelerate

Validation of salivary heme oxygenase-1 as a biomarker of idiopathic Parkinson disease

The diagnosis of Parkinson disease (PD), the second most common neurodegenerative disorder in the developed world, is based entirely on clinical criteria which are labour-intensive to apply and often inconclusive. Based on promising initial data from our laboratory, we will determine whether biochemical measurement of the enzyme, heme oxygenase-1 (HO-1) in saliva samples distinguishes PD from normal control subjects and persons with other neurological disorders. Positive results would address an unmet clinical need by allowing rapid and accurate diagnosis of this condition and possibly monitoring of effective disease-modifying medications as they become available. A saliva-based test would be commercially competitive and offer important advantages over other bodily fluid samples (blood, cerebrospinal fluid, etc.) and brain imaging techniques because collection and analysis of saliva is non-invasive, relatively inexpensive, and would not require advanced training of personnel.

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Faculty Supervisor:

Ana Velly

Student:

Partner:

HemOx Biotechnologies Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Freshwater Oil Spill Remediation Study at the IISD-Experimental Lakes Area: (The FOReSt Project)

The Freshwater Oil Spill Remediation Study (FOReST) project will use small contained oil spills in enclosed environments within a lake to study examine the effectiveness of shoreline cleanup procedures and potential ecological impacts of oil spills. The resilience of freshwater aquatic ecosystems to recover from a spill will also be examined. We will examine the ability of bacterial communities to respond to the introduction of oil and biodegrade petroleum compounds. Results from the proposed project will be used to develop scientifically-defensible cleanup procedures and to direct monitoring for potential effects.

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Faculty Supervisor:

Gregg Tomy;Valerie Langlois;Mark Hanson

Student:

Partner:

IISD Experimental Lakes Area Inc

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

Université du Québec : Institut national de la recherche scientifique; University of Manitoba

Program:

Accelerate

Apprentissage profond pour la reconnaissance de marques et de types de véhicules

On assiste ces dernières années à des performances de calcul des processeurs graphiques permettant le traitement en temps réel d’images et de vidéos. Ce projet exploite ce type de technologie afin de développer un module embarqué pour des applications d’apprentissage profond et de vision par ordinateur.
Un des objectifs principaux du projet consiste à développer des algorithmes d’intelligence artificielle pour la reconnaissance automatique de marques et types de véhicules en temps réel à partir de vidéos routières. Cet objectif nécessite deux phases : (a) de constituer une base d’apprentissage de véhicules suffisamment large et variée pour une prédiction optimale; (b) de développer des algorithmes d’apprentissage profond spécifiques à la reconnaissance de marques et types de véhicules.

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Faculty Supervisor:

Eric Hervet

Student:

Partner:

ELUMICATE

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Moncton

Program:

Accelerate

Intraday Trading and Analysis and Monitoring Trader Behavior

Electronic exchanges are venues that provide immediacy for those who need to find a counterparty to their trades. Orders of various types arrive in the market at ever increasing speeds, and in this era of high-frequency trading (HFT), institutional investors are often disadvantaged because of their high-latency relative to faster traders. To level the playing field somewhat, this proposal seeks to understand what features are present in the market when there is normal and abnormal trading activity, and to provide a tool for TMX and its clients to detect when the trading environment is “toxic”. In addition, the proposed project aims to classify brokers/traders (into hedgers, speculators or HFT arbitrageurs), predict traders’ behavior and assess whether traders are colluding.

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Faculty Supervisor:

Sebastian Jaimungal;Matt Davison

Student:

Partner:

TMX Group Limited

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

University of Toronto; Western University

Program:

Accelerate

Effective Remediation in Porous Systems with Fractures and Heterogeneities: Experimental and Modelling Study

Dispersion of various solutes in porous media has been investigated experimentally and theoretically for different scientific purposes. The study of this phenomenon can provide fundamental knowledge of solvent (or gas) flooding in enhanced oil recovery, groundwater contamination, and catalyst-based chemical processes.

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Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

Advanced CERT Canada

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Research into the Design and Development of Inclusive Digital Media Technologies

This project, a collaboration between Ryerson University and Pear Square, will be researching what would enable businesses and organizations to provide resources efficiently to students with disabilities. The outstanding issue is mainly a lack of standardized work flow methodologies that promote accessible development from the beginning stages of any project for large institutions. The research proposed for this project will be to formulate, test, and acquire feedback on experimental workflows that accommodate a variety of accessible digital media systems. The research conducted for this project will provide Pear Square with a comprehensive insight of how accessible systems can be used as a resource for assisting students with disabilities to reach their goals.

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Faculty Supervisor:

Alex Ferworn

Student:

Partner:

Pear Square

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Accelerate

Predictive Control Approach for Converted Multi Zone Residential Buildings with Central HVAC Systems

The current project aims to study a novel energy management system for residential heating ventilating and air conditioning (HVAC) system. Independently controlled wireless air damping vents will adjust the air flow in different zones of the building allowing independent control of the temperature which results in enhanced thermal comfort and energy savings. The intern will collaborate with the partner organization on studying a unique state-of-the-art predictive model to control the damping factor of the vents within fully closed to fully open range. The partner organization will benefit from the expertise of both the supervisor and the intern in HVAC and thermo-fluids to achieve a more effective control strategy for the system.

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Faculty Supervisor:

Carey Simonson

Student:

Partner:

SenergyK Innovative Creations

Discipline:

Engineering

Sector:

Other services (except public administration)

University:

University of Saskatchewan

Program:

Accelerate

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