Innovative Projects Realized

Conditions favorables aux rencontres arts science | Expéditions Bleues 2018–2024.

Dans la crise climatique actuel, artistes et scientifiques collaborent de plus en plus afin de mieux comprendre les écosystèmes et de sensibiliser la population aux enjeux écologiques. Pourtant, les conditions qui rendent ces collaborations interdisciplinaires durables et porteuses demeurent encore peu documentées.

Ce projet s’appuie sur les Expéditions Bleues, des expéditions en milieu naturel menées par Organisation Bleue, qui rassemblent artistes, scientifiques et équipes de coordination autour de la protection des écosystèmes marins. En analysant les expériences vécues lors des expéditions réalisées entre 2018 et 2024, la recherche vise à mieux comprendre ce qui favorise ou freine les rencontres entre les disciplines dans un contexte d’immersion en nature.

À partir d’entretiens avec les participant·e·s, le projet examinera comment les conditions de terrain, l’organisation des projets et les relations humaines influencent la collaboration. La photographie sera utilisée comme outil de dialogue pour soutenir le récit des expériences et rendre visibles des dimensions sensibles souvent difficiles à exprimer autrement.

Les résultats mèneront à la production d’un guide pratique destiné à soutenir la planification de futures expéditions interdisciplinaires.

L2M – MSDL-CPFE: Multiscale Crystal Plasticity and Multiphysics Simulation Software

This project aims to turn an advanced research software into a practical tool that helps the nuclear industry better predict how critical reactor components degrade over time. These components operate in extreme conditions, and replacing them is very expensive, so improving lifetime predictions can lead to significant cost savings and safety benefits. The project will focus on understanding where and how the software provides the most value, and how it can be integrated into real industrial decision-making processes. The expected benefit to the partner organization is a clearer path to using the software as a reliable decision-support tool, helping reduce uncertainty, limit unnecessary component replacement, and support safer, more cost-effective operation of nuclear systems.

God’s Voice on Earth Goes Digital: Making and Mediating the Voice of the Pope

This project examines how the Vatican’s recent shift to digital audio technology is changing the way the Pope communicates with the world’s 1.3 billion Catholics, including over 12 million in Canada. By studying the audio engineers who design and operate the Vatican’s recording equipment, the church officials who make decisions about how the Pope should sound, and Catholic families in Sicily and Canada who listen to Vatican broadcasts, this research explores how religious institutions use new technology to maintain their authority and connect with global communities. The project benefits the University of Toronto by bringing back specialized knowledge about audio technology and institutional communication that will enhance teaching and research capacity, while the University of Palermo gains strengthened international research partnerships and expanded networks with North American scholars studying religion, technology, and Mediterranean communities. Both institutions benefit from collaborative publications and conference presentations that position them as leaders in understanding how digital transformation affects global religious institutions, knowledge increasingly relevant as churches, governments, and cultural organizations worldwide face similar challenges in adapting their communication strategies for the digital age.

Understanding the Process and Consequences of Hybrid Governance for Water Delivery in Odisha

Research shows that gaps in urban water provision in the Global South are often linked to governance arrangements rather than only physical water scarcity or inadequate infrastructure. This has led to institutional reforms that change who plans, manages, and delivers water. However, governance transition is typically gradual rather than a single transformative event, with older practices often persisting alongside new rules and procedures. There is limited empirical understanding of how these reforms are carried out in practice and why similar reforms produce different outcomes across contexts. This project examines a governance transition in the Indian state of Odisha, where responsibility for water services shifted from a government engineering department to a publicly owned utility. Using official documents and in-depth interviews, the study traces how the transition unfolded, how older and newer organisational arrangements were adapted, combined, or continued in parallel, and how this shaped everyday service delivery. This project will generate evidence on how governance reforms affect service outcomes. The host institution will benefit from original field-based data and a process-oriented case that supports theory-building on institutional change in public services. The home institution will benefit through analytical strengthening of doctoral research and research collaboration.

Manufacturing-to-Measurement and Verification for the Harvest Platform

This project will help Harvest Systems improve how the performance of its waste heat recovery technology is tracked and reported. By creating a secure system that automatically aggregates and analyzes data from installed units, the project will generate clear reports on energy savings and system performance. This will help restaurants lower energy costs and reduce emissions, while also helping Harvest Systems scale its technology, strengthen customer confidence, and support broader commercial growth across Canada.

Beyond Carbon: Community Wellbeing in the Chyulu Hills REDD+ Project

As carbon markets expand across the Global South, community-based carbon projects are increasingly promoted as “triple-win” climate solutions that mitigate emissions, support economic development, and enhance local wellbeing. In Kenya, REDD+ projects have proliferated rapidly, yet there remains limited community-centred research examining their impacts on lived experience. This study addresses this gap through a qualitative case study of the Chyulu Hills REDD+ Project (CHRP). Grounded in environmental justice, the study critically examines how REDD+ projects shape community wellbeing, with particular attention to Maasai communities whose livelihoods, land relations, and cultural practices are closely tied to the landscape. It situates REDD+ within neoliberal conservation frameworks and Kenya’s colonial conservation history, highlighting how power, knowledge, and resources circulate through carbon governance. The research introduces an original conceptual framework—the “carbonscape”—adapted from Appadurai’s scapes, to examine the global–local flows of ideology, finance, actors, and technologies shaping carbon projects. Using semi-structured interviews, ethnographic observation, key interlocutor interviews, and photovoice, the study assesses wellbeing across social, economic, cultural, environmental, and political dimensions, focusing on participation, benefit sharing, land access, and cultural inclusion. The findings contribute Kenya-specific empirical insights to debates on REDD+, carbon markets, and climate justice, with implications for more equitable climate governance.

Mongolia Filmmaking Project 2026

Our goal with this project is to use filmmaking as a medium to engage in knowledge-sharing in Indigenous communities in Mongolia. In order to do this, we plan to work alongside the Frozen Commons project as they organize various workshops and and fieldwork throughout Mongolia. By working with the Frozen Commons, as well as collaborating with Indigenous communities, we aim to enter a collaborative space where films and other video-media projects can be created as a way of sharing and preserving knowledge.

ENDOMATRIX – Développement de matrices biomimétiques pour la culture 3D d’organoïdes et de tumoroïdes d’endomètre.

Le cancer de l’endomètre est l’un des plus fréquents affectant les organes reproducteurs féminins et touche plus de 420 000 femmes chaque année dans le monde.
Afin de mieux comprendre le développement et la progression du cancer de l’endomètre, la matrice extra-cellulaire (MEC) est de plus en plus étudiée. Composée de plus de 1000 protéines formant le matrisome, elle joue un rôle essentiel dans la régulation de l’équilibre normal des tissus. Lors de la tumorigenèse, la MEC est dérégulée et participe activement à la progression du cancer, notamment par la modification des forces physico-mécaniques du microenvironnement.
La MEC d’endomètre sain et la MEC des différents sous-types de tumeurs endométriales sont encore mal caractérisées. Pour pallier à cela, l’équipe de recherche a purifié la MEC de tissus sains et de tumeurs de l’endomètre. Le matrisome a été analysé par spectrométrie de masse, permettant d’obtenir des signatures protéiques des différents sous-types de cancers de l’endomètre.
Le présent projet vise donc à la création de matrices biomimétiques récapitulant les caractéristiques biochimiques et physiques de la MEC endométriale, afin de permettre la culture en 3D d’organoïdes dérivés de patientes dans des conditions proches de l’in vivo.

Amélioration des prévisions des feux au Maroc avec l’utilisation de la télédétection et l’intelligence Artificielle

Ce projet vise à améliorer la prévision du risque d’incendies de forêt au Maroc en combinant la télédétection (données satellites) et l’intelligence artificielle. Il intégrera des données météorologiques (température, humidité, vent, précipitations) et des indicateurs de sécheresse et d’état de la végétation dérivés de satellites afin de produire des cartes de risque plus précises. Les résultats contribueront à mieux cibler la prévention, la surveillance et l’allocation des ressources pendant les périodes de feux de forêt au Maroc.

ESROP – Metallization Optimization in Tandem Solar Cells

This project focuses on identifying optimal patterns in a special type of solar cell, the tandem solar cell, in which different light-absorbing materials are stacked to increase efficiency. Specifically, the project aims to analyze an important, understudied aspect of these cells: their metallization patterns, which have a significant impact on cell performance. This project aims to identify optimal patterns in performance and cost using data-driven machine learning algorithms. If time allows, these patterns will be tested on a tandem solar cell. The proposed project benefits the participating institutions by fostering a global network of researchers and enabling shared development among independent organizations and universities.

ESROP Intelligent Robotics Development and Implementation

The ESROP Global project with the Innovative Cognitive Computing (IC2) lab aims to implement and develop prior intelligent robotic systems with a focus on effective interactive systems and artificial intelligence integration for multimodal input data. This will be achieved through a combination of diverging as a team to develop extensions of current systems and data analysis of system effects and modelling. Such systems include the “I See Too” intelligent robot for climate awareness. Other focus projects may include frameworks for healthcare companionship and response, such as for Elderly communities, or integration of serious game systems. An associated aim is to conduct human data analysis for project evaluation and further model development, with ethical considerations as appropriate.

ESROP + A research-oriented project to study diffusion-based LLMs

This project studies a promising alternative to current autoregressive (AR) large language models: diffusion-based large language models. It aims to make them generate high-quality text more efficiently while maintaining speed and energy efficiency. The research will focus on understanding how these models work, identifying their root limitations, and developing improved methods that balance text quality, speed, and energy use. Through a combination of literature review, theoretical analysis, and experiments, the project will propose and evaluate new approach for faster and more reliable text generation. The participating institutions will benefit by advancing their expertise in AI models, strengthening international research collaboration, and producing research outcomes that can support future work in efficient and scalable language models.