Innovative Projects Realized

Exposing the Invisible – Designing with the Uncertainty of Wind

The objective of this project is to connect architects and wind engineers early on within a project so that affects associated with wind such as pedestrian comfort and building strength may be maintained from the start of a project. Rather than making post-construction modifications to a building through the costly use of screens, covers or even redesign, favorable wind conditions could be achieved through the collaboration between architects and wind engineers during the initial stages of design. This would reduce the dangers of increasing wind speeds on ground level, the costs to redesign or add in components and finally save time on construction. Instead of sealing ourselves inside buildings, we could begin to understand wind flows and expand our ideas of what architectural form, technologies and experiences could be created. The idea is to not only promote the goals of safe environments from RWDI but to also spread the word and clarify the importance of wind to a larger audience so that wind can play a larger role in the development of our cities.

Quantifying the Safety and Efficiency of Dance Styles Using Wearable Sensors at University College Cork and Tyndall Institute

This project, based at the Tyndall Institute at University College Cork in Ireland, is creating one of the first open-access, lab-quality biomechanics datasets focused on dance. It will record movement from different dance styles using motion capture, wearable sensors, and muscle activity measurements to better understand the physical demands of dance techniques and the risks of injury. The project will also develop standardized methods for processing and interpreting the data, making it easier to apply in training, rehabilitation, and machine learning. By sharing these resources openly, the project supports innovation in sensing technology, artificial intelligence, and human performance research.

Querying the immigrant: data classification and technical construction of the risky entries

The project is part of a thesis that investigates logic of classification embedded in advanced data analytics and automated decision-making tools (and, now “AI”), implemented to determine Canada’s temporary resident visa applicants, which involves sorting applicants for risk, inadmissibility, ineligibility, and illegality.

Developing Advanced Topologies for High-Power Motor Drives

Energy saving is one of the important issues in today world. In order to improve the performance of the industrial motor drives for high-power applications, higher voltage power converters are recommended. Compared with low-power converters, high-power systems have their distinct characteristics and challenges, and usually require converter configurations capable of processing energy conversion at higher power and voltage levels. The technical requirements and challenges for MV systems differ in many aspects from those of the low-voltage AC converters, which have been mostly resolved. In this project I would like to perform research into promising high-power converter topologies and new control algorithms that are an improvement over existing technology in terms of power quality, cost, efficiency, and reliability. This helps Rockwell Automation Canada to develop new technologies for the next generation of the motor drive systems.

L2M – AI-optimized RF energy harvesting and Simultaneous Wireless Information and Power Transfer (SWIPT) platform

Ocean technology companies and research organizations rely on autonomous sensors, buoys, and communication nodes to monitor marine environments and support offshore operations. While these devices provide essential data, their dependence on batteries creates high servicing costs, logistical challenges, and limited deployment lifetimes in harsh marine conditions. Overcoming these limitations is critical for enabling sustainable, long-term ocean monitoring.
This project will develop a wireless RF energy harvesting and Simultaneous Wireless Information and Power Transfer (SWIPT) system tailored for marine applications. By delivering both power and data wirelessly, the approach aims to eliminate battery dependence, reduce costs, and enable continuous, scalable sensor operation. Unlike incremental improvements in battery technology, this solution offers a transformative approach to powering remote ocean platforms.
The research objectives are fourfold: (1) model and simulate RF energy harvesting and SWIPT systems; (2) design machine learning algorithms for adaptive impedance matching, beamforming, and scheduling; (3) integrate RF and ML simulations to test system performance under dynamic marine conditions; and (4) validate the framework using representative marine sensor case studies. In parallel, the project will explore biodegradable housing materials to reduce environmental impact and align with sustainability goals.
By combining RF engineering, AI-driven optimization, and application-focused validation, the project will deliver a proof-of-concept system that advances ocean monitoring capabilities. The outcomes are expected to reduce operational costs, extend device lifetimes, and strengthen Canada’s leadership in ocean innovation, supporting applications in fisheries, offshore energy, and climate research.

L2M –Next-Generation Marine and Offshore Components via Canadian High-Entropy Alloys and Laser Powder Bed Fusion (LPBF)

This project focuses on developing next-generation marine and offshore components using high-entropy alloys (HEAs) derived from Canadian resources and manufactured through Laser Powder Bed Fusion (LPBF), an advanced metal additive manufacturing technology. The marine and offshore oil and gas industries operate in some of the world’s most corrosive and mechanically demanding environments, where corrosion, fatigue, and biofouling severely limit component lifetimes and drive up maintenance costs. Conventional materials, including stainless steels, bronzes, and nickel alloys, offer only partial solutions and cannot meet the complex design and durability requirements of modern marine systems.

To address these challenges, this project introduces a two-stage innovation framework. The first stage focuses on designing HEAs using strategic Canadian elements, niobium (Nb), aluminum (Al), copper (Cu), and iron (Fe), to achieve outstanding resistance to corrosion, fatigue, and biofouling. These alloys are engineered at the microstructural level to withstand harsh seawater exposure, reduce maintenance intervals, and improve energy efficiency. The second stage leverages LPBF additive manufacturing to fabricate intricate geometries such as pump blades, valve housings, impellers, and fluid-handling components that are impossible to produce by traditional methods.

The integration of HEA alloy design with LPBF manufacturing will establish a Canadian-led innovation framework that links domestic materials resources with advanced manufacturing expertise. This project not only addresses critical needs in marine and offshore industries but also strengthens Canada’s position in the global blue economy by developing sustainable, high-performance solutions from homegrown materials. The outcomes, optimized alloy compositions, validated manufacturing parameters, and demonstrated prototypes, will provide a foundation for future industrial adoption, supporting Canada’s economic growth, technological leadership, and environmental resilience.

Inventing the Future of AI Applications: Applied Research in Machine Learning at AXL

AXL Labs is the technical arm of AXL, a Toronto-based venture studio that creates and launches companies focused on human-centric artificial intelligence (AI). Their main goal is to leverage human-computer interaction (HCI) and AI in designing and deploying end-to-end solutions for industry and academic applications. Organizations that partner with AXL typically have business problems where they don’t fully understand the breadth of the opportunity that a solution could provide. AXL conducts an opportunity analysis to determine high-impact business areas to develop a full-fledged solution that may alleviate these business problems. As the rapid development of AI technologies continues, organizations must determine how to best leverage and benefit from these models.
The internship is designed to tackle this challenge by building novel interactive systems that utilize advanced machine learning techniques and large language models (LLMs). This problem is particularly relevant to AXL as we aim to innovate in the AI sector, creating cutting-edge AI systems and building new spin-out companies that address market needs. In particular, the proposed project, designing a human-in-the-loop AI ingester for intaking startup ideas, such as pitch decks, founder interviews, and application forms, will aim to reduce the time taken for venture capital and investors to evaluate potential startup ideas, pair founders with potential products, and result in an accelerated feedback loop that can shorten the time it takes for a startup company to reach the broader market. We believe it is possible to create a modular prototype that can ingests the types of unstructured and semi-structured data, as described above, in a multi-modal system within the time proposed.

Hydrometallurgical Production of Niobium and Tantalum Oxide

A hydrometallurgical process for the production of niobium and tantalum oxide from a primary mineral resource and by product of a tin smelting slag is proposed. This process comprises dissolution of the concentrate and slag with the mixture of acids, following by purification and precipitation process. XPS do not have any background in hydrometallurgical recovery of niobium and tantalum and therefore this will provide an important foundation for future work by XPS in this field.

Amélioration des performances des adhésifs par l’ajout d’additifs : diminution des émissions de formaldéhyde et amélioration de la résistance à l’humidité

Les panneaux de particules et de fibres sont omniprésents dans nos maisons, nos écoles et nos bureaux our fabriquer meubles, planchers, armoires et aménagements intérieurs. Leur production repose sur des colles industrielles contenant du formaldéhyde, un composé efficace mais reconnu comme irritant et cancérogène. Avec le temps, ce formaldéhyde s’échappe dans l’air intérieur, représentant un risque direct pour la santé. Comme nous passons la majorité de notre temps à l’intérieur, la réduction de ces émissions est devenue un enjeu de santé publique majeur. Les solutions envisagées jusqu’ici pour remplacer ces colles reposent sur le développement de nouveaux adhésifs sans formaldéhyde. Bien que prometteuses, ces approches exigent souvent des investissements majeurs, car elles nécessitent de repenser complètement les procédés industriels et les infrastructures de production. Une approche alternative consiste à modifier les formulations existantes par l’ajout d’additifs biosourcés capables de limiter la propagation du formaldéhyde dans les pièces intérieures. Cette stratégie ne cherche pas à remplacer totalement les colles utilisées actuellement, mais à les améliorer. Cette approche répond à des enjeux sanitaires en améliorant la qualité de l’air, environnementaux en valorisant des résidus forestiers et réduisant l’usage de produits pétrochimiques, ainsi qu’économiques grâce à une solution rapidement industrialisable et peu coûteuse.

Modelling and Laser Processing Shape Memory Alloys

The goal of the proposed research project is to perform an in-depth analysis of shape memory alloys through thermal and mechanical testing. This analysis will be used to develop new mathematical models to better predict the performance of the shape memory alloys after they have undergone a manufacturing process that is unique to the partner company. The benefit to the partner company is the usage of these models, which will allow for the design and manufacturing of more reliable and customizable shape memory devices for use in many industries, including biomedical and automobile

Amélioration de la formule de partage des Banques alimentaires du Québec (BAQ)

Les Banques alimentaires du Québec (BAQ) sont un organisme à but non lucratif œuvrant dans l’aide alimentaire. Leur mission est de soutenir les membres de leur réseau afin de nourrir les personnes en difficulté, en mutualisant ressources et expertises (BAQ, 2025). L’équité est une valeur centrale pour les BAQ, se traduisant par un partage équitable des dons, qu’ils soient monétaires ou en denrées. Ce partage repose sur une formule qui détermine la portion attribuée à chaque membre selon le type de don.

In situ infra-red spectroscopy of electrode ionomer networks for electrochemical energy system applications

While hydrogen technologies such as fuel cells and water electrolyzers are expected to play pivotal roles in the upcoming energy transition, their insufficient durability continues to hinder their wider adoption. Longevous fuel cells and electrolyzers demand durable materials (i.e., solid electrolytes) that can withstand the corrosive environment within these devices. However, the mechanisms of solid electrolyte degradation and their effect on device performance remain poorly understood. Understanding those mechanisms is an important first step to designing durable solid electrolytes for next generation fuel cells and electrolyzers. The proposed research project is to revolutionize our fundamental understanding of, and develop predictive modelling tools for, solid electrolyte degradation in fuel cells and electrolyzers. We will couple our accelerated electrolyte degradation and characterization techniques with the unique in situy infrared spectroscopy capabilities pioneered by Dr. Chevalier’s group, to generate a first-of-its-kind dataset that can inform novel solid electrolyte designs and operating strategies for durable fuel cells and electrolyzers.