Innovative Projects Realized

Mely.ai

L’objectif principal du projet est de développer la stratégie marketing de l’organisation. Tout d’abord, puisque c’est une compagnie qui n’a pas encore rentrée officiellement sur le marché, elle aura besoin d’un énorme soutien marketing afin de développer sa notoriété. Le développement de cet organisme permet également au Canada d’avoir une jeune entreprise québécoise, compétente et qui se différencie face aux compétiteurs. La réussite de ce projet permet également d’aider les autres entreprises dans leurs projets. Un défi majeur est surtout l’intégration et l’acception sur le marché de cette compagnie. Elle doit se créer un nom et se faire connaître. En revanche, c’est un secteur innovant et en pleine expansion. Les modèles Agiles font de plus en plus partis des devises des entreprises et c’est une nécessité de développer un logiciel tel que celui de Mely ai.

FutureVault Business Strategy Internship

This student will join the FutureVault marketing and strategy team. This team has a number of key mandates for the organization. The team supports and influences the strategic direction and design of the overall product and solution with a focus on driving product-market fit to ensure that the products and services being developed have the appropriate forecasted demand and are competitive in the market. This is accomplished by executing on a go to market strategy and marketing plan with a focus on efficient digital marketing campaigns and account-based marketing initiatives. These activities are planned based on marketplace research and market data. The intern will also support the design, layout, and messaging for corporate and investor relations materials, including presentations and investor packages. The planned research and implementation work of this project will ultimately help FutureVault tailor a secure and collaborative data-management platform to meet the unique needs of different organizations throughout Canada.

Research Coordinator

The South Island Prosperity Partnership (SIPP) is a non-profit organization that serves as Greater Victoria’s economic development agency. As a public/private alliance with over 65 members, SIPP’s governance structure is very unique in Canada. 11 municipal governments, nine First Nations, three post-secondary institutions, several business and industry associations, NGOs, and over 30 of the region’s major employers collaborate towards making the region an even better place to live and work. The COVID19 pandemic has impacted the Greater Victoria region disproportionately due to the region’s high percentages of tourism-related jobs. In response, SIPP has created a 40 member taskforce to develop a regional recovery strategy (to be launched this fall). SIPP is proud to work with the Mitacs program to engage a research and strategy intern who will work with our team on analyzing data, developing research reports and recommendations from over 100 stakeholder organizations, and helping the team develop the final report.

Bacon Financial Technologies Inc. – Hardbacon

Hardbacon s’apprête à lancer un nouveau produit afin de répondre au contexte d’incertitude économique créé par la pandémie du Covid-19.

Non seulement les Canadiens sont plus soucieux que jamais de payer moins de frais sur leurs services financiers, mais la plupart des entreprises offrant des comparateurs ont mis fin à leurs programmes d’affiliation en raison de la pandémie.

Hardbacon lancera donc au courant des prochaines semaines un comparateur de comptes de banque, de robots-conseillers, de courtiers en ligne, et de CPG.

Le produit devrait être lancé au courant de l’été et certains d’entre eux sont deja lancés sur Hardbacon.ca (soft launch).

Le candidat retenu pour le poste de stagiaire en développement d’affaires et gestion de projet agira en quelque sorte à titre de pdg de cette start-up à l’intérieur d’une autre start-up.

Développement de solutions pour l’utilisation de l’impression 3D pour la production de composants de machines d’emballage alimentaire

Les machines d’emballage alimentaire sont produites en fonction des besoins du client et, par conséquent, chaque projet a ses propres exigences. Pour cette raison, l’étude de nouveaux procédés et matériaux est importante pour l’innovation et la concurrence sur le marché. D’autre part, les technologies de fabrication additive sont de plus en plus accessibles et réalisables pour la production à l’échelle industrielle. Le but de projet est de proposer la fabrication de composants mécaniques qui entrent en contact direct avec les aliments à travers la fabrication additive. Afin de comprendre les besoins de l’industrie, une vaste étude de cas sera réalisée sur les processus de nettoyage et le choix d’une pièce à remplacer. Ce projet permettra à l’entreprise de maitriser de bénéficier d’une première approche structurée pour appliquer l’innovation technologique à la production de pièces alimentaires à partir de l’impression 3D.

Seq2Hypergraph: Link prediction on knowledge graphs using relation conditioned Transformer Networks

Learning from relational data is crucial for modeling the processes found in many application domains ranging from computational biology to social networks. In this project, we propose to work on developing new modeling techniques that combine the advantages of the approaches found in two fields of study: Machine Learning (through graph neural networks and transformer networks) and Statistical Learning (through statistical relational learning methods). By combining the advantages of both approaches, we aim to obtain better prediction results for an array of problems such as classification and link prediction in relational data.

Research into an Implementation Framework for National Inquiry into Missing and Murdered Indigenous Women and Girls (MMIWG) in NL

On June 3, 2019, the National Inquiry into Missing and Murdered Indigenous Women and Girls (MMIWG) released its Final Report. Among its 231 recommendations, Calls for Justice 5.7 and 9.2(iii) urge the federal, provincial, and territorial governments to take specific steps to strengthen civilian oversight of police services by ensuring stronger Indigenous participation in police boards and other oversight authorities.
Frameworks for civilian oversight of police services exist in many Canadian and other common law jurisdictions. Yet the current framework in use in Newfoundland and Labrador is comparatively weak. The purpose of this study is to work with Indigenous community stakeholders in order to determine ways of strengthening civilian oversight of police services in the province. It will do so with a view toward reducing the prevalence of gender-based violence while also recognizing the province’s unique legal context and history. The study will seek to identify effective models and best practices that are already in use in other Canadian and common law jurisdictions, propose possible innovations and/or improvements upon such models and practices, and develop a set of detailed recommendations for implementing stronger civilian oversight of police services in Newfoundland and Labrador.

Improved Unsteady Aerodynamic InfluenceCoefficients

Currently Bombardier Aerospace uses the Doublet Lattice Method (DLM), incorporated into a
structural solver, to perform aeroelastic calculations such as flutter. This method is able to provide
very good results in the subsonic regime, but looses accuracy in the transonic regime due to the high
non linearity of the flow. A methodology was developed where the aerodynamic data produced by
DLM is replaced by high fidelity CFD data. This project is aimed at producing unsteady aerodynamic
data in the transonic regime to be used in Bombardier’s new methodology to perform more accurate
aeroelastic calculations.

Accelerating Technical and Market Readiness of Solid-State Nanopores

Solid-state nanopores—small holes in thin membranes comparable in size to individual molecules—are promising candidates as sensors with which to revolutionize DNA sequencing, personalized medicine, point-of-care diagnostics, and next-generation information storage methods. A method by which these nanopores can be fabricated on an industrial scale was recently invented, but challenges remain, particularly in quality-controlling source materials with which to make them and in analyzing and interpreting the signals generated. This project seeks to both develop generalized analysis methods and software for nanopore applications, as well as optimize the manufacturing processes upstream of sensor fabrication, providing a recipe for reliable and consistent materials to be used in scaling up fabrication of solid-state nanopores going forward, greatly increasing the pace of academic research and making these critical sensors viable on an industrial scale.

A Novel Passive Wireless Printed Circuit Board Cavity Sensor for the Measurement of Electric and Magnetic Fields

Increasing demand for more reliable electric power requires advanced monitoring systems that prevent equipment failure and outages. The existing technologies used for monitoring the voltage and the electric field in the vicinity of the high voltage devices are bulky and expensive. On the other hand, maintenance of the monitoring devices requires specific safety precautions. In this research project, a small and inexpensive electric/magnetic field sensor is proposed. They are passive and require no source of power. This eliminates the need of changing the batteries and direct contact to the high voltage apparatus. The interrogation system that will be designed and employed is wireless that makes the distant measurement possible. This will increase the safety of the personnel and facilitate distributed measurements at different distances from the high voltage device.

Multilingual Semantic Similarity of Unstructured Enterprise Content

To communicate with their end users, businesses regularly produce written documents such as letters, notices, statements, etc. in various languages. A set of rules are usually used to ensure that information in these documents is ‘correct’ and consistent across languages and communication channels. However, with the increasing volume and variety of information being sent out to clients, it becomes difficult to preserve the semantics of client messages across vocabulary and language variations. State of the art algorithms that solve this problem involve a translation algorithm which creates an additional overhead and makes the entire pipeline less practical to use.
This project aims at creating algorithms capable of measuring semantic similarity between unstructured enterprise contents with less overhead regardless of the natural language being used for each document. The set of similarity algorithms must scale with the size of the corpus being used.

Intelligence Artificielle et Apprentissage Machine pour la Cybersécurité

Ce projet consiste à extraire la nature des accès informatiques des employés d’une organisation et les consolider afin de permettre au gestionnaire de l’employer ou à un auditeur d’avoir une vue d’ensemble des accès informatiques de ses employés. Les employés qui arrivent ou quittent l’organisation, ou changent d’emploi dans la même organisation exigent une révision périodique de ces accès.
Ce projet vise à :
• Extraire les accès de tous les employés et dans toutes les plateformes et applications sélectionnées ;
• Présenter ces accès au gestionnaire responsable pour les certifier via un workflow
• Intégrer dans ce processus des mécanismes d’apprentissage automatisé permettant de gérer les risques et les accès sensibles et détecter des anomalies
Plusieurs défis sont connus à savoir l’extraction des données qui nécessitent de développer de connecteurs spécifiques, la nature très hétérogène de données et la mise en place de solution d’intelligence artificielle efficaces dans ce domaine. L’objectif du projet est de réaliser un outil efficace aidant les organisations à mieux protéger leurs applications et infrastructures informatiques contre la fraude, fuite de données et les accès non autorisés.