Innovative Projects Realized

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.

FluidPlanet Digital Twins

FluidPlanet.org produces and publishes digital twins (virtual versions of real places) for academic, educational and enterprise use. By combining the latest technologies in mapping (GIS), sensors (IoT) and visualization (gaming), we create realistic looking and behaving simulations of real locations. These can then be populated with virtual people, animals and buildings to tell stories that teach and entertain.

Dynamic Simulation for Data-Driven Logistical Control of Iron Ore Material Streams

The Canadian iron industry will benefit from increasingly streamlined data to support operational decisions, particularly as their steelmaking clientele is transitioning toward carbon-neutral steel production. The iron ore required for carbon-neutral steelmaking is especially high grade, in accordance with the DRI-EAF steelmaking route. Key operational decisions include the formation and depletion of stockpiles for different categories of ore, as the resulting ore blends are processed into a variable mix of iron ore products. Moreover, the rebalancing of conventional iron ore products versus DRI-EAF grade products is complex, requiring dynamic mineralogical and operational information. The proposed interdisciplinary project adjoins geological analysis and algorithm development within state-of-the-art operational simulations, which will support system-wide control of the iron ore value chain.

Development and implementation of a genomic sequencing workflow to enhance laboratory diagnostics and routine reporting of respiratory viruses

Respiratory diseases caused by viruses that are frequently evolving have placed significant strains on Canadian healthcare systems. Traditional methods of diagnostics can detect the presence of viruses in clinical specimens
but do not always distinguish them at the variant level. Next Generation Sequencing (NGS) is a high throughput technique that is used to determine the genetic sequence of viruses. Many laboratories in Ontario do not
perform ongoing NGS for viruses other than SARS-CoV-2. Furthermore, analyzing NGS results may be complicated or inaccessible. Therefore, our goal is to develop a validated NGS workflow for common respiratory
viruses such as RSV that will allow for accessible analyses, interpretation, and reporting of key molecular epidemiological information such as virus evolution, variant prevalence, treatment effectiveness, and outbreak
patterns. Overall, this workflow will enable systematic tracking of evolutionary patterns and mutational changes of circulating viruses which are essential for viral surveillance, vaccine, and therapeutic development. The
outcome of this work will equip labs with tools to alleviate the strain that respiratory virus surges place on Canada’s healthcare system.

Optimal Control on Diesel engines and Aftertreatment Systems

The internal combustion engine will remain the major source of transportation power for decades to come. This project will focus on the control technologies related to minimizing engine-out emission and improving fuel efficiency. Through collaborative control of the engine and its aftertreatment system, an overall optimization of emission and fuel consumption can be realized. The proposed method will be validated through experimental study and tests.