Projets novateurs réalisés

Rich, Immersive AR/VR Communication

Face-to-face communication provides substantial benefits over traditional remote communication via video and voice: the expressivity of body language, spatial grounding in a common physical space, access to physical tools and objects, and much more. For many collaborative tasks, face-to-face communication is considered indispensable, yet meeting in person can be rendered infeasible by any number of factors, such as cost, time, urgency, or pandemics.
Simultaneously, the recent pandemic has forced people to explore new ways to enjoy shared experiences such as concerts and sporting events. However, video conferencing tools used for this purpose lack the interactivity and social aspects which make such experiences immersive.
The broad goal of this research is to investigate ways to bring some of the strong benefits of face-to-face communication into remote communication, via the use of augmented and virtual reality technology. AR/VR technologies have the potential to unlock far richer and more immersive communication compared with traditional video or voice calls, yet that potential has not been fully realized in today’s systems.
We propose researching novel communication technologies built atop AR/VR platforms across two streams: bridging the physical and virtual environments in mixed-reality calls, and building mixed-reality crowd experiences based on scalable immersive video delivery.

Contributions to build a theory of land value

The main objective of this research project is to contribute to construct a theory of urban land value, which accounts for the multiplicity of factors that affect the way land is valued in the city.
To achieve the main objective, the different proposed theories of value will be compared from anthropology with contemporary theories about land value, in order to base a state of the art of a new theory of land value.
With this objective, the ideas of political economy, of the classical tradition, on land value that serve as a theoretical and reference framework.
On the other hand, it is necessary to deconstruct the economist view of the value of urban land through a historical review and the reconstruction of an alternative look that allows see the gaps left by traditional economic theories of land value.
And in this way to understand, from another perspective, the urban transformations that take place currently in cities and identify other ways in which property ownership is presented land, beyond individual private property and as exchange commodity.

At-Risk Birds Critical Habitat Modeling for Strategic Planning on Port Hawkesbury Paper’s Crown License Lands

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Machine learning approach for calculating the viscosity of ternary nitrate based molten salts

The growing production of clean electricity from solar resources has led to employ molten salts as heat transfer fluids for thermal energy storage technologies. Thus, the study of thermodynamic and physicochemical properties of multi-component molten salts are critical factors for the design of such units. From one side, binary salt mixtures’ thermodynamic properties are already accessible through critically assessed data. However, the evaluation of physicochemical properties, such as viscosity, requires experimental measurements for specific molten salt compositions. Computational models based on machine learning techniques intend to accelerate the time invested in experimental procedures to simulate and, even more, predict data with high accuracy. Thus, in this work, three machine learning techniques are proposed to predict the viscosity of nitrate-based ternary molten salts. Training data for LiNO3, NaNO3, and KNO3 (unary, binary, and ternary systems) will be collected from the literature to train Decision Trees, Support Vector Machines, and Artificial Neural Networks. Then, the coefficient of determination and the root of mean square error will be calculated to evaluate and compare the performance of models.

Informative Art Simulations and Games for Improving Energy Awareness in the Home

While energy conservation in the home is an important part of reducing our ecological footprint most people do not understand or even realize how their energy consumption works and how they can manage it. In-home displays offer the opportunity to help become more aware, but often do not fit into a home’s aesthetics, typically relegated to an unobvious location after the novelty “wears off”. They also provided little opportunity for interaction and learning. We are exploring how interactive, aesthetically motivated displays, and small energy use simulations as simple games, may prove more engaging and effective in helping people learn, recognise and be more aware of energy use patterns in the home.

Eudemian Internship

Eudemian Ventures is a top-performing Silicon Valley venture capital firm that supports innovative entrepreneurs by investing in early-stage software startups. Typical focus areas are Business-to-Business Software-as-a-Service (B2B SaaS), Consumer, Fintech, Marketplaces, eCommerce, AdTech, Digital Health, and Artificial Intelligence (AI).

The firm is now strategically expanding its presence to Canada by establishing an office in Toronto with the intention of growing its associate base by tapping into the local talent pool. This aligns with Eudemian Ventures’ objective of establishing a global presence to support innovation ecosystems at scale.

Projet supervisé – Implantation d’une stratégie numérique pour rhum

Rhum est une agence de gestion des ressources humaines et d’acquisition de talents spécialisée dans le domaine de la créativité et de l’innovation. Il peut être difficile pour une petite entreprise offrant des services interentreprises de développer sa présence en ligne pour y acquérir de nouveaux clients, surtout lorsqu’elle œuvre dans un marché niche. Le but de ce projet est donc d’y mettre en place une stratégie numérique basée sur le contenu.

Reducing Barriers in New Brunswick – KargoROO

KargoROO (kargoroo.ca) is a local startup that offers an innovative solution for residents in rural and urban areas to access goods and services while reducing their carbon footprint. Our mission is to help promote sustainable and eco-friendly consumption habits while supporting local merchants and optimizing transportation efficiency with our crowdsourcing app, ROO. This project will support business optimization to further help to reduce carbon emissions and transportation costs for our users. By connecting local merchants and consumers through our app, we are able to reduce the number of individual trips required for each delivery, which helps to reduce congestion on the roads and lowers transportation costs for our users.

Enhancing Matching and Diversity in Health Research Projects through Textual Interpretation and Machine Learning

The project aims to improve the matching process in health research projects by leveraging machine learning and textual interpretation. It focuses on accurately connecting research projects, community organizations, and participants. The project addresses challenges such as diversity and inclusion by interpreting metrics, generating synthetic participant profiles, and utilizing NLP techniques for label association. By creating matching filters and relevance models, the project enhances the accuracy and relevance of pairings. The ultimate goal is to promote diversity, inclusivity, and the overall quality of health research outcomes.

Motion Planning and Control of Industrial Manipulators

Our project involves the use of robotic arms with six movable joints. Utilizing Inverse Kinematics, we will program the arm to figure out how to position each joint to reach specific points, offering flexibility in handling tasks. Through motion planning, we will design paths that the arm can follow to move from one point to another while avoiding obstacles, ensuring smooth and efficient movement. Control mechanisms will be implemented to maintain precision in the arm’s movements, making adjustments as needed to stay on course. The integration of these three components will allow our robotic arm to perform complex tasks with accuracy and agility.

Automated Data Analyzer

The objective of this project is to develop an automatic data analysis tool that allows users to query datasets using a natural language interface. The project aims to incorporate external knowledge sources via knowledge graph integration, thereby enhancing the accuracy of the analysis. The knowledge augmentation will be reference based using REALM or Toolformer inspired design.

Advanced control on an autonomous vehicle with independently actuated wheels

The proposed project will focus on the control of autonomous car, also known as a driverless car, which is an autonomous vehicle capable of fulfilling the human transportation capabilities of a traditional car. The research platform is an electric car with four wheel independent control. The findings in this project can be used in either autonomous car or intelligent vehicle control to guarantee the driving safety and stability.