Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

29 670 projets achevés

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4990
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801
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663
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825
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95
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568
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Projets par catégorie

L’intelligence artificielle au service de la cybersécurité : conception et développement de services pour des organisations plus autonomes

Avec la pénurie croissante d’experts en cybersécurité et l’imprévisibilité des attaques informatiques, les organisations canadiennes font face à des défis majeurs pour protéger leurs actifs informationnels. L’objectif dece projet est de concevoir et développer un portail comprenant des services en cybersécurité que ces organisations peuvent utiliser de manière autonome ou semi-autonomes pour évaluer leur sécurité et les gérer les risques qu’elles encourent. Les stagiaires qui participeront à ce projet utiliseront des démarches scientifiques et puiseront dans les techniques d’intelligence artificielle pour développer le portail.
En plus de contribuer à l’avancement des connaissances dans le domaine de la cybersécurité, ce projet permettra à l’organisme partenaire d’être avant-gardiste dans l’offre de services en cybersécurité en permettant aux organisations canadiennes d’utiliser des services de cybersécurité informatisés et personnalisables.

Voir la description complète du projet
Superviseur du corps professoral :

Hager Khechine

Étudiant :

Partenaire :

La Société conseil Lambda inc.

Discipline :

Business

Secteur :

Administrative and support, waste management and remediation services

Université :

Université Laval

Programme :

Accelerate

A Feature Discovery System for Data Science Across the Enterprise

Existing data lake systems lack the support for storing or discovery features that could be used with different ML projects.
These limitations negatively affect the process of decision-taking. Data scientists spend most of their time finding, preparing,
and integrating relevant data sets to finish analytics tasks. Feature discovery systems are needed to ease the process of building
data science pipelines to drive significant insights efficiently, effectively and fairly. To meet these needs, we should overcome
challenges, such as: (a) discovering links and similarities among data items at different granularities, such as table and column,
and (b) developing mechanisms to make the features searchable not only searching the relevant data (c) processing complex
queries that extract the relevant features efficiently, (d) tracking vast amount of features used in different ML projects and
accuracy of the models used these features, and (e) detecting feature bias used throughout a data science pipeline.

Voir la description complète du projet
Superviseur du corps professoral :

Essam Mansour

Étudiant :

Partenaire :

Royal Bank of Canada (Borealis)

Discipline :

Computer science

Secteur :

Information and Communications Technology; Technology

Université :

Concordia University

Programme :

Accelerate

Dynamic actor tracking for Augmented Reality-based filmmaking guidance

Augmented Reality can help in simplifying the filmmaking process by intelligently suggesting shot composition angles for amateur filmmakers to take better shots. In partnership with Rubber Match Productions, researchers will investigate how actors within an AR filmmaking environment can be dynamically tracked to provide real-time guidance to the filmmaker for shot composition. The project will utilize latest advances in artificial intelligence and computer vision to track actors in real-time through videos. Multiple actors will be tracked simultaneously, and Rubber Match’s proprietary “smallest angle principle” will be applied on the actors’ positions for accurate shot composition. The developed technology and accompanying app will provide amateur filmmakers with professional filmmaking guidance at their fingertips. The proposed research will also be expected to make significant contributions in the fields of augmented reality and artificial intelligence. The intersection of these two fields is becoming increasingly important for providing production-level software tools and techniques in digital media and video production

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Superviseur du corps professoral :

Naimul Khan

Étudiant :

Partenaire :

Rubber Match Productions Inc.

Discipline :

Engineering

Secteur :

Information and cultural industries

Université :

Toronto Metropolitan University

Programme :

Accelerate

Restorative Action Student Support Analytics

In partnership with schools and community partners, the Restorative Action Program deals with bullying, physical violence, crime, mental health, substance abuse, suicide and self-harm – with programming delivered to over 8000 youth in Saskatoon schools. They work with youth to develop and practice conflict management, relationship management, and leadership skills – focusing on prevention, intervention and reconnection.
Over the course of two years, RAP along with Saskatchewan Polytechnic, has developed a prototype progressive web application capturing an identified set of data elements that were not possible to capture using previous technology. Now that the prototype has made visible a rich topology of varying data elements and many interrelationships, it is time to investigate and analyze semantic context and further enhance the insight and knowledge being discovered within the data and relationships. This, in turn, will improve the efficacy of the services provided to youth in distress or difficult situations within the Saskatoon school systems.

Voir la description complète du projet
Superviseur du corps professoral :

Cyril Coupal

Étudiant :

Partenaire :

Restorative Action Program

Discipline :

Computer science

Secteur :

Education

Université :

Saskatchewan Polytechnic

Programme :

Accelerate

Modélisation de la corrélation des pertes pures par chapitre pour l’assurance-auto au Québec.

Les modèles de tarification actuels en assurance-automobile traitent les chapitres (responsabilité civile, collision responsable, bris de vitre, vol, etc.) comme étant complètement indépendants les uns des autres; la fréquence et le coût moyen des réclamations sont aussi généralement considérés comme indépendants! Notre objectif est d’explorer de nouveaux modèles de tarification qui tiennent compte du fait que ces différents chapitres, ainsi que les fréquences et coûts d’accident, ont des facteurs en commun (style de conduite, par exemple). L’objectif est d’en arriver à un modèle de tarification plus robuste et plus précis, pour fournir des primes d’assurance plus justes.

Voir la description complète du projet
Superviseur du corps professoral :

Jean-Philippe Boucher

Étudiant :

Partenaire :

La Capitale Assurance et Services Financiers (Montreal, QC)

Discipline :

Mathematics

Secteur :

Finance and Insurance

Université :

Université du Québec à Montréal

Programme :

Accelerate

Genome-scale metabolic models for the characterization of genetically modified microalgae for cannabinoid production

Algae-C is a company specialized in algal biomass production. It enables on-site production of algae for a wide variety of sectors (aquaculture, nutraceutical, cosmetic and biofuel). To date, many fuels, pharmaceuticals and cosmetic products are extracted from plants. These valuable plant natural products (PNPs) are often produced in low quantities in plants and extraction methods can be long and expensive. Thus, there is much interest in metabolic engineering for developing microbial platforms to produce specific PNPs. Microalgae are well-known systems for plant biology and metabolic engineering and are interesting and suitable hosts for the reconstitution of complex plant pathways. Algae-C wishes to translate metabolic engineering research into industrial processes. This project aims to optimized microalgae platforms for the production of valuable PNPs. This project focuses on PNPs produced by cannabis, i.e. cannabinoids. These ventures are motivated by consumer demand for products that are environmentally friendly, less expensive, and possess properties similar or superior with those generated by PNPs.

Voir la description complète du projet
Superviseur du corps professoral :

Isabel Desgagné-Penix

Étudiant :

Partenaire :

Algae-C

Discipline :

Life Sciences

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université du Québec à Trois-Rivières

Programme :

Accelerate

Evaluating Quantum Search Applicability to NP-Hard Problems in Industry

Quantum computers, that is, computers that exploit quantum mechanical phenomena to process information, have been shown to theoretically perform some computations faster than the best available methods on traditional computers. One widely applicable quantum computing technique is quantum search which offers an improvement to the problem of finding a needle in a digital haystack. Despite its wide applicability, the usefulness of quantum search to performing any single computational task must often be evaluated on a case-by-case basis. As a result, the full applicability of quantum search is unknown. We analyze computational tasks important in industry and aim to determine if and when quantum search could offer improvements to these computations. Developing this knowledge is directly aligned with the Quantum Algorithm Institute’s goal of bringing together industry and academia to harness the power of quantum computing.

Voir la description complète du projet
Superviseur du corps professoral :

Barry Sanders

Étudiant :

Partenaire :

Quantum Algorithms Institute

Discipline :

Computer science

Secteur :

Education; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Accelerate

A Neural Investigation of Trust in Digital Influencers

Virtual agents based on artificial intelligence have become increasingly popular on social media. Examples of Lil Miquela or
Shudu Gram show how completely artificial agents can have a significant influence on our social lives, and especially social
media marketing. However, it stands to question how these virtual influencers are actually perceived by consumers, whether they
trust them more than live influencers, and whether there are unconscious processes that are driving their ability to influence.
Since trust and social processes are routed in brain regions, a neuroimaging experiment using both EEG and fNIRS is to be
conducted to receive deeper insights. There are brain signals that have already been established to correlate with interesting
measures, such as trustworthiness, attention, and emotional valence. Results will show how differently virtual influencers are
perceived and processed when compared to human influencers. From this, findings inform both theory and practice and help to
more effectively plan and design virtual influencers.

Voir la description complète du projet
Superviseur du corps professoral :

Colin Conrad

Étudiant :

Partenaire :

Universität Duisburg-Essen

Discipline :

Business

Secteur :

Entertainment and Media; Information and Communications Technology; Technology

Université :

Dalhousie University

Programme :

Globalink Research Award

Factors that Encourage and Impede Missing Middle housing on Vancouver Island

Missing Middle Housing (MMH) encompasses several moderate density housing types which offer similar features to a single detached home, while reducing costs to the buyer, reducing the environmental footprint and reducing the amount of land used. Although many Municipalities on Vancouver Island are beginning to encourage MMH, there are still relatively few of these homes being built. The proposed research will identify factors that encourage and impeded the development of MMH on Vancouver Island. The outcome of this research will be a technical report and a list of recommendations that will help facilitate the partner organization in the development of MMH. A publishable research paper will also be completed.

Voir la description complète du projet
Superviseur du corps professoral :

Mark Holland

Étudiant :

Partenaire :

Wiser Projects

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

Vancouver Island University

Programme :

Accelerate

Optimization of Large-Scale Power Systems with Electromagnetic Transient Simulators

Design of modern electric power systems in which renewable energy resources are included is a challenging task. This is because these power systems employ a large number of sophisticated power converters and control methods that need to be accurately tuned. The task of tuning and optimizing these converters and their controls is tedious, repetitive, and time-consuming. This research aims to tackle this problem by developing novel computerized methods for simulation-based optimization of large systems. By doing so, it will significantly enhance our ability to design more responsive and more efficient power system rapidly and with much less effort.

Voir la description complète du projet
Superviseur du corps professoral :

Shaahin Filizadeh

Étudiant :

Partenaire :

Manitoba Hydro International Ltd

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

University of Manitoba

Programme :

Accelerate

Developpement d’appiication mobile pour la carboneutralite

Le projet de recherche consite en Ie developpement d’une application mobile permettant la quantification carbone de differents projets. L’etudiant devra developper la methodologie de quantification carbone visant les evenements, les voyages, et les petites entreprise. De plus, etant donne que Ie projet s’enligne dans une perspective dedeweloppement durable, Ie stagiaire devra et approfondir ses connaissances en la matiere afin de transferer Ie savoir dans I’entreprise. L’entreprise partenaire benificiera du developpement d’une nouvelle pratique et d’un nouveau produit qui favorisera sa visibilite dans ce secteur d’activite.

Voir la description complète du projet
Superviseur du corps professoral :

Michel Denault

Étudiant :

Partenaire :

LANDRY et associés

Discipline :

Business

Secteur :

Information and Communications Technology

Université :

HEC Montréal

Programme :

Accelerate

Mapping Artificial Intelligence (AI) on K – 12 curriculum, learning theory, Indigenous ways of knowing, and the Cortic Technology Software

The objective of this research partnership is to map Artificial Intelligence (AI) to elementary curriculum and Indigenous ways of knowing using Cortic Technology’s software. We hope to build a theoretical framework and instructional approach for AI education for children at an elementary level. A review of current research will set the context for AI and digital fluency in elementary classrooms and will map the skills, concepts and perspectives relevant to elementary aged children. Working with teachers and students in elementary classrooms with the Cortic Technology software in a French Language and Indigenous context will provide the opportunity to evaluate the impact of AI education on learning outcomes and inform the future development of tools and resources for AI education. Cortic Technology will be able to improve and grow their AI software based on the findings to be used in K-12 schools across Canada.

Voir la description complète du projet
Superviseur du corps professoral :

Julie Mueller

Étudiant :

Partenaire :

Cortic Technology Corp.

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

Wilfrid Laurier University

Programme :

Accelerate

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