Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

Market Analyst

Act as a Market Analyst to carry out:
– quantitative and qualitative research using modern and traditional methods
– analyze and interpret patterns, solutions and opportunities informed by accurate data and research
– formulate plans, strategies and opportunities for presentation to senior management
– remain informed on market trends
– evaluate market and business opportunities and make recommendations in order to identify and develop strategies to attract markets
– conduct social or economic surveys on regional, national and international markets to assess development potential and future trends

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Faculty Supervisor:

John Medcof

Student:

Partner:

FluidAI Medical

Discipline:

Business

Sector:

Health and Related Sciences & Technology

University:

McMaster University

Program:

Business Strategy Internship

Design Limits for Carbon Fibre ReinforcedPolymers

Hudson Boat Works in London, Ontario is the only company in Canada that manufactures highperformance
rowing shells. Hudson wishes to employ finite element techniques to optimize the design
of their rowing shells and associated structures using advanced engineering techniques. Optimization
of composite materials design requires a detailed understanding of their mechanical response,
including how they fail. Researchers at Western will focus on studying these failure mechanisms, and
in doing so will generate the material data required for finite element analysis. The fracture surfaces of
Hudson’s single ply materials and sandwich panels will be evaluated using optical and scanning
electron microscopy to characterize the failure mode.
The successful conclusion of this project will provide Hudson with the requisite capabilities to employ
advanced engineering techniques to optimize their composite structures. Furthermore, improved
understanding of failure mechanisms in composite materials is applicable to a wide variety of
industries with requirements for tough, lightweight materials.

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Faculty Supervisor:

Jeffrey Wood

Student:

Partner:

Hudson Boat Works

Discipline:

Earth science

Sector:

Manufacturing

University:

Western University

Program:

Accelerate

Optimisation de l’ordonnancement des activités de projet en réfection de navires.

Thales développe un logiciel pouvant gérer les activités de projet en réfection de navires militaires. En particulier, ce logiciel permet d’ordonnancer les différentes tâches à accomplir, c’est-à-dire les positionner sur une ligne du temps. L’ordonnancement produit doit tenir compte de la disponibilité des ressources (main-d’œuvre, équipements, espaces de travail) tout en minimisant les heures supplémentaires nécessaires pour respecter les échéances. La programmation par contraintes s’est déjà montrée efficace pour résoudre le problème de Thales. Cependant, lorsque le nombre de tâches devient grand, il devient impossible de le résoudre dans un temps raisonnable (quelques heures). L’objectif général du projet est donc d’accélérer le processus de résolution en intégrant une technique de recherche de solutions couramment utilisée appelée recherche à grand voisinage. Trois spécifications de cette technique ont été établies et chacune d’elles sera testée durant le stage.

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Faculty Supervisor:

Claude-Guy Quimper

Student:

Partner:

Thales Canada Inc

Discipline:

Computer science

Sector:

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

University:

Université Laval

Program:

Accelerate

Psychometric evaluation of the Show Up Questionnaire and estimation of innovation climate latent profiles

ShowUp is a new product by Dovico that provides teammates the opportunity to improve their workplace culture. The evaluation is conducted with the help of a questionnaire. Dovico aims to use the results of these questionnaires in a machine learning setting to predict innovative culture in teams and organizations.

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Faculty Supervisor:

Denis Lajoie

Student:

Partner:

Dovico

Discipline:

Sociology

Sector:

Information and cultural industries

University:

Université de Moncton

Program:

Accelerate

Sniffing Line in Mass Spectrometry for Direct Analysis

Mass spectrometry is a known for its capacity of detection of sample material with high sensitivity paired with high resolution and accuracy. Developing a “sniffing line” that would provide point-of-measurement capabilities for direct analysis of particulates on various surfaces is a necessary and novel method that will influence the mass spectrometry technique. Referred to as ‘sniffer line’, the apparatus will allow for surface contaminants to be more effectively sampled from the target surface and transported directly into the mass spectrometer. The result will be a more robust particulate analyzer providing enhanced detection ability, higher accuracy, shorter duration, decrease in cost-of-use, and real-time detection, while eliminating false-positive and false-negative errors which is an unaddressed issue in the industry. Recently, QuadroCore invented a new method to provide a more direct and sensitive detection system that detects minute traces of analytes from target materials. The goal of this project is to characterize the first “sniffing line” of this patent by researching, designing, and developing a suitable apparatus.

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Faculty Supervisor:

Qiyin Fang

Student:

Partner:

QuadroCore

Discipline:

Engineering

Sector:

Advanced Manufacturing; Life Sciences (not health)

University:

McMaster University

Program:

Accelerate

Evaluation & sensitivity study of behind-the-meter load disaggregation methods

Solar energy generation at commercial and industrial sites has been gaining popularity in recent years. The addition of batteries to existing solar installations can allow for solar to not only be used during the day when the sun is out, but also at night. There however, are various hurdles to this process specifically involving the transparency of the data coming from the solar unit. Several methods have addressed this issue at residential sites and offer promising results. However, these methods have not be tested for various geographies, climates, and operational issues that can arise at commercial and industrial sites. We will attempt to build upon residential PV disaggregation methods using both physics and statistics-based models. If successful, our method will likely allow for energy storage to be added at existing PV locations, increasing the amount of clean energy used in various industries across Canada & North America.

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Faculty Supervisor:

Andrea Scott

Student:

Partner:

Energy Toolbase

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Application of machine learning techniques to control surface quality of as-printed wire arc additive manufactured components

Nowadays, the wire arc additive manufacturing is making its path toward providing benefits to aerospace, defense, and oil and gas sectors, ascribed to the process capacity to fabricate components with minimum waste of material and lead time. However, the main challenges associated with the WAAM that have hindered the wide-spread application of the technology include the irregular and random quality of the WAAM fabricated surfaces. The mission of this project is to control aforementioned irregularities in fabrication by implementing machine learning-based algorithms and modify the process parameters to achieve a defect-free part with high surface quality. The anticipated trained machine learning method in this project will foster the progress toward completion of an autonomous in-situ defect recognition and correction (AIDRAC) system, which is the primary goal of the intern.

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Faculty Supervisor:

Ali Nasiri

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Technology; Manufacturing and Construction; Advanced Manufacturing

University:

Memorial University of Newfoundland

Program:

Accelerate

Discover anomaly signatures from time series data of telecommunication networks

Failures in a telecommunication network harm the communication quality. Once happened, if the system cannot solve it by self-healing, such anomaly may even result in serious problem and result in massive economic loss. In this project, we will design and develop a system to predict these failures in advance using the status values of the hardware facilities. Our goal is to build a completed data processing, model building and training system to predict facility failures automatically for production-level deployment with strict evaluation criteria (precision > 80%, which means for all the positive prediction our model gives, at least 80% of them is correct; recall > 10%, which means for all real failures in the network, our model could predict at least 10% of them). The success of this project will expand Ciena’s capability to develop superior products for anomaly prediction services.

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Faculty Supervisor:

Yan Liu

Student:

Partner:

Ciena Corporation (Ottawa, ON)

Discipline:

Computer science

Sector:

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

University:

Concordia University

Program:

Accelerate

Élaboration d’un modèle théorique valide à la base d’un moteur intelligent pour le développement professionnel en formation.

Le projet vise à développer un dispositif intelligent permettant l’autodiagnostic et l’auto-orientation de personnes formatrices qui souhaitent développer leurs compétences professionnelles et plus spécifiquement leurs compétences dans l’usage du numérique pour enseigner et apprendre. Ce dispositif innovant s’appuyera sur un moteur intelligent rigoureux fondé sur un cadre théorique en éducation validé. La stagière contribuera à la validation scientifique du modèle théorique ainsi qu’à sa mise en application dans un contexte d’autoformation. Ce projet permettra de donner une force théorique et scientifique aux développements informatiques en cours, de consolider les interactions à la base d’un robot intelligent ainsi que d’augmenter la valeur commerciale des développements et des produits de l’entreprise.

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Faculty Supervisor:

Florian Meyer

Student:

Partner:

Optania Solutions Inc

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Mechanistic study of tellurium/carbon cathode in liquid and solid-state lithium-tellurium batteries

Lithium-tellurium (Li-Te) batteries provide higher volumetric energy density than current lithium-ion batteries and are considered as one of the most promising energy storage technology for emerging applications in electric vehicles, implantable medical devices, and Internet of things. The development of stable tellurium/carbon (Te/C) cathodes is the key towards durable Li-Te batteries. However, the reaction mechanism of Te/C with Li ions remain unknown due to complexity involved from the porous carbon, pore size, and the type of electrolytes, limiting the design of practical Li-Te batteries with high energy and power densities. This collaborative project between the University of British Columbia (Canada) and National Cheng Kung University (Taiwan) will fill this knowledge gap by using advanced in-situ characterization techniques to track real-time reactions between Te/ C and Li ions. The new knowledge obtained in this project will not only advance fundamental understanding on solid-state chemistry, but also accelerate the development and commercialization of Li-Te batteries for practical applications .

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Faculty Supervisor:

Jian Liu

Student:

Partner:

National Cheng Kung University

Discipline:

Engineering

Sector:

Clean Technology; Nanotechnology; Green/Alternative Energy

University:

The University of British Columbia - Okanagan

Program:

Globalink Research Award

Investigation of Water-in-Oil Emulsion on CSI Solvent Dissolution and Ex-solution Performance for Heavy Oil

This research work will establish a systematic workflow for analyzing transient equilibrium foamy oil phase behavior by coupling the CCEC tests, depletion rate and presence of water-in-oil emulsion which are seldom performed for heavy oil. It will provide a strong connection and comparison with previously studies which was conducted in the absence of water-in-oil emulsion. It will create a strong connection between phase behavior with fluid properties, operating conditions and kinetics. A concrete database which contains large amount of laboratory transient equilibrium data for selected heavy oil reservoirs can be established. The effects of different content of water-in-oil emulsion on the heavy oil production performance will be evaluated.

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Faculty Supervisor:

Na Jenna Jia

Student:

Partner:

Petroleum Technology Research Centre

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

Promoting Gender Equality through Social Innovation

From women-only taxi companies in New Delhi to smokeless stoves in Uganda, innovation can transform the lives of women and girls around the globe. While it is well known that social innovation and women’s empowerment are each processes that drive change, there is little research to date connecting social innovation to the empowerment of women and girls. This project will identify how social innovation connects to women’s empowerment through a partnership with MATCH International. This project will support MATCH through the launch, development and growth of the Women’s Fund for Social Innovation. As the first of its kind in Canada, the fund will invest in innovation projects proposed by women and girls in the global South.

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Faculty Supervisor:

Bipasha Baruah

Student:

Partner:

Match International

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

Western University

Program:

Accelerate