Innovative Projects Realized

Inner Alliance: A game for gender-responsive leadership, diversity, inclusivity and readiness in defense and national security teams

The Archipelago of Design (AOD) is a non-profit organization supporting the leading independent network of purpose-driven security practitioners, educators and researchers empowering leaders to shift mindsets for the sustainable evolution of national security organizations across NATO members and partners. This project strategically aligns with AOD’s mission of cultural transformation in defence, security, government, and academic institutions and organizations to better set conditions for inclusivity. The proposed project aims to develop a digital prototype of a squad-based tactics game focused on disaster relief for marketing purposes. The game will covertly teach players about inclusivity and team coherence while they battle their environment. By employing serious game methodology, the project will address urgent issues like climate change and equity, diversity, and inclusion (EDI) in a fun and engaging way. The digital prototype will help AOD showcase the potential of transformative training tools to their extensive security and defense network, illustrating their innovative approach and generating funds to develop the full game experience.

Gestion des eaux pluviales dans le parc Prieur

Le projet de recherche s’intéresse à la problématique de la gestion des eaux pluviales dans l’arrondissement Ahuntsic – Cartierville à Montréal, accentué par l’augmentation des événements de précipitation extrêmes liés aux changements climatiques. Les infrastructures de drainage vieillissantes et les conceptions de l’époque rendent le réseau particulièrement vulnérable. Pour remédier à ces problèmes, deux principales stratégies sont envisagées : l’implantation d’infrastructures vertes favorisant l’infiltration et l’évapotranspiration pour retenir le ruissellement à la source, et la modification de la trajectoire du ruissellement vers des zones moins vulnérables.
Le parc Prieur de l’arrondissement est situé dans une dépression et reçoit naturellement des eaux de ruissellement à la suite d’un événement de précipitation et permet de faire de la rétention de façon temporaire. Pour cette raison, il a été ciblé comme un site potentiel pour implanter des infrastructures vertes et y rediriger un maximum de ruissellement afin de soulager le réseau de drainage existant. Ces travaux de recherche ont pour objectif d’analyser le comportement hydrologique et hydraulique actuel du parc et d’émettre des recommandations pour en maximiser l’efficacité en matière de gestion des eaux pluviales, notamment en y intégrant des infrastructures vertes.

Design and development of low-area high-accuracy controller circuit on ASIC for stabilizing a novel SiP-based external-cavity laser (ECL)

FONEX Data System Inc. is developing solutions to address the challenges that telecommunication service providers face in upgrading their access networks to sustain the growth in data traffic. A key component of these solutions is the development of a low-cost, widely tunable external cavity laser (ECL) utilizing Photonic Integrated Circuit (PIC) technology. A significant advantage of these PIC-based ECLs is their potential for integration with electronic circuits on the same wafer. This inherent compatibility enables a synergistic fusion of photonics and electronics, paving the way for advanced functionalities. In this research, our ultimate objective is to meticulously design a wavelength controller on an application-specific integrated circuit (ASIC) platform. This specialized ASIC platform is envisioned to serve as a robust control system for the newly developed ECLs. The proposed monolithic integration of electronic and photonic circuits is expected to deliver significant benefits to FONEX customers, including Canadian network operators, by meeting their evolving demands with cutting-edge technology.

Smart Textile Development for Health Monitoring

This project aims to develop a smart textile-based solution for early detection and management of sleep apnea, a condition that significantly impacts health, especially in those with chronic illnesses like heart failure. Traditional diagnostic methods are often inconvenient, uncomfortable, and expensive. To address these challenges, the project focuses on creating a comfortable, non-invasive, and cost-effective alternative using smart wearable textiles.

The project involves developing a smart T-shirt embedded with textile-based dry electrodes to monitor physiological signals such as ECG, body posture, and respiration. The T-shirt prototype will be finalized during a 3-month internship at Lille University, where extensive training in textile engineering and smart textile development will be provided. Afterward, data collection will be conducted in Canada at KITE, UHN, using the new prototype with participants over 40 years old. The study will assess the accuracy of the captured signals compared to traditional methods.

Additionally, the project will explore the development of functional textiles with sensing capabilities for treating sleep apnea, focusing on comfort and effectiveness. These efforts aim to advance the field of smart textiles, offering practical, user-friendly health monitoring solutions that could lead to earlier diagnosis and intervention for sleep apnea, ultimately improving health outcomes and reducing healthcare costs.

Development of Bio-material based Nanocomposite Thermoelectric Generator

Thermoelectric systems can produce electricity using temperature difference and heating/cooling effect using electricity. Thermoelectric systems are basically combination of p and n-type semiconductor materials. Thermoelectric systems have many advantages such as, environment friendly, no moving parts, silent in operation, and long service life. However, at this stage thermoelectric systems have very low efficiency so they are not popular in usage. Nevertheless, high performance thermoelectric systems can be prepared using nanotechnology. Scientists and engineers around the globe have reported high performance nanostructured thermoelectric materials. In addition to this, most of the thermoelectric materials are rare earth materials and they are not abundant. So, our work addresses two problems; (i) develop high performance nanocomposite thermoelectric generator (ii) use agriculture biomass to reduce the use of rare earth materials. The final outcome of this research can benefit many industries such as automotive, aviation, and energy.

Synthesis and Characterization of Functional Magnetic Polymer Beads for Bioapplications

STEMCELL Technologies supports the research of Canadian and international scientists (academic, industrial, clinical) by supplying labs with research tools to investigate research questions tied to some of the most pressing health care needs faced by the Canadian community. STEMCELL’s high quality standards in the cell and biomolecule isolation market are continuously driving the company to improve their products and applications through an advanced understanding of the critical mechanisms involved. The knowledge gained from this research may impact the development of future products for new bio applications. By participating in this MITACS project, STEMCELL Technologies will collaborate with the academic partner, who has a long-standing track record of tackling fundamental research questions pertinent to glycan research.

Developing Smart Technologies for Aging in Place at Home

Transitioning patients from hospital to at-home care is vital for health care operations. However, there is a general concern that these at-risk populations would not be receiving the same level of care at home as they would in a dedicated medical facility. Elderly populations experience a significantly higher risk of readmission after discharge from acute care hospitals. This shows that there is a significant gap in transitioning the care of older adults from hospitals to home/community settings. Adequate and safe rehabilitation requires close monitoring of the patients’ mobility, nutrition, and exercise to complete the recovery process and ensure restoration of independence. This project aims to develop advanced sensing and imaging technologies for smart home monitoring of elderly populations aging-at-home. This includes a full suite of technologies from various sensors, cameras, and other devices that can measure mobility patterns, nutrition intake, as well as provide self-administered physiotherapy in a home setting.

Machine Learning-Based Modeling of Spreading Dynamics in Complex Interfacial Systems

Understanding droplet interactions with surfaces is crucial for large-scale oil recovery, coating industries, and microfluidic devices. To address the remaining challenges, including the need for a universal timescale and improved theoretical and computational models, this project brings together the SoftSimu group at Western University and the Soft Materials Modelling (SMM) group at Aalto University, Finland. The SoftSimu group, led by Prof. Karttunen, specializes in advanced molecular simulations and applying machine learning to bridge theoretical models with practical applications, particularly in elucidating droplet spreading process. The SMM group, a founding member of the Academy of Finland National Center of Excellence in Life-Inspired Hybrid Materials (LIBER), excels in modeling soft materials from the atomistic to mesoscale, leveraging the advanced LUMI supercomputer. In collaboration with experimental groups at LIBER, they have demonstrated the importance of molecular simulations in designing super-slippery coatings. The project aims to (1) develop expertise in simulating surfactant-laden droplets and SAMs-decorated surfaces, (2) enhance daily collaboration with experimental groups at LIBER, and (3) share expertise in modeling wetting dynamics using machine learning. Through this collaborative effort, we aim to advance the fundamental understanding and practical applications of droplet dynamics, ultimately contributing to the development of more effective and innovative technologies.

L’insécurité linguistique chez des enseignant.e.s de français langue seconde et étrangère: une étude comparative Brésil-Canada

Si la recherche est abondante à étudier l’insécurité linguistique chez les locuteurs ayant le français comme langue maternelle, moins nombreuses sont les études intéressées au phénomène chez les locuteurs de français langue seconde et étrangère (FLSE) et particulièrement chez les enseignants de FLSE. Pourtant, quelques études suggèrent que ceux-ci subissent de l’insécurité linguistique en raison de deux idéologies majeures, celle du sujet natif et celle du standard, lesquelles produisent des discours d’exclusion des locuteurs qui n’ont pas le français comme première langue et/ou parlent des variétés non franco-françaises.
Ce projet de recherche a pour objectif d’investiguer, dans le cadre d’une approche comparative Brésil-Canada, les causes de l’insécurité linguistique chez des enseignants de FLSE ainsi que de repérer les effets du phénomène sur la maîtrise de la langue et l’activité d’enseignement. L’analyse comparative permettra également d’établir les facteurs internes (relatifs au contexte sociolinguistique dans lequel le français est inséré) ainsi que les facteurs externes (idéologies répandues dans la francophonie) qui suscitent le sentiment chez les enseignants. Trois outils de collecte de données seront mobilisés : un questionnaire sociodémographique, des entretiens individuels semi-dirigés et des groupes focaux. Environ 20 enseignants récemment diplômés ou en début de carrière seront recrutés dans chaque pays.

Civillian involvement in national security as a result of the Russian invasion of Ukraine

Project explores two key aspects of civilian involvement in national security: the evolution of Ukraine’s policies on civilian firearm ownership and the development of “Territorial Defence” institutions in Ukraine and similar “home guard” entities in Central and Eastern Europe, as well as the Nordic/Baltic region. The goal is to understand how these elements contribute to national security and public safety, particularly in light of the current Russian invasion of Ukraine and potential threats to other European nations. By analysing Ukrainian and foreign press, legislation, and scholarly literature, we aim to provide insights that could inform public policies to enhance national security. While the project is not directly focused on Canada, this country is a Nato member that is committed to the security of its European partners. It thus has an interest in understanding how those countries can better secure their own defence. In addition, some of the policy insights we develop from our research may be broadly applicable to Canada as well. This research is a collaborative effort between the University of Toronto and Ukrainian National University “Kyiv-Mohyla Academy,” and holds significant value for Ukrainian citizens and broader theoretical implications for conflict societies.

Automatic Quantification of Neutrophil Accumulation within the Alveolar Space in Lung Histology Images using Artificial Intelligence

This project aims to create advanced artificial intelligence (AI) tools to help scientists and doctors better understand and treat severe lung conditions, like acute lung injury (ALI). ALI is a serious condition that can lead to breathing problems and is often difficult to study because the current methods for analyzing lung tissue are time-consuming and rely heavily on human judgment. We plan to develop AI models that can automatically analyze images of lung tissue to count neutrophils, a type of white blood cell that is important in understanding inflammation in the lungs. Using cutting-edge machine learning techniques, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), our goal is to create a reliable system that not only speeds up the analysis process but also makes it more accurate. These AI tools will be able to explain how they arrive at their conclusions, making it easier for doctors and researchers to trust the results. Ultimately, this project could lead to better ways to study and treat lung diseases, improving patient care and potentially reducing healthcare costs.

Manifold Learning for Anamoly Detection

Modern data analysis tasks often face challenges of high dimension and thus nonlinear dimension reduction techniques emerge as a way to construct maps from high dimensional data to their corresponding low dimensional representations. Finding such low dimensional representations of high dimensional data is beneficial in several aspects. This saves space and processing time. More importantly, the low dimensional representation often provides a better understanding of the intrinsic structure of data, which often leads to better features that can be fed into further data analysis algorithms. Manifold learning is a subfield of machine learning that focuses on dimensionality reduction, with the goal of capturing the underlying structure of high-dimensional data in lower-dimensional representations. The concept behind manifold learning is that even though data might live in a high-dimensional space, it might be constrained to a lower-dimensional manifold within that space. Methods like t-SNE, Isomap, and locally linear embedding (LLE) are some popular techniques in this category. Our aim of this internship project will be to apply manifold learning on tabular data and transactional graph data and see how it can help in better fraud detection (anamoly), feature engineering, clustering, etc.