Projets novateurs réalisés

Optimized catalyst layers for efficient hydrogen production

Applicability of functional size measurement to quantum error correction software

The primary objective of this research is to measure error correction schemes in quantum computing and their impact on the functional size of quantum software. By analyzing various Quantum Error Correction (QEC) methods, the research aims to optimize quantum software measurement and development. Additionally, a key goal is to define specifications for an automated tool based on the COSMIC method.
This RGA application is related to the in-progress IT-34807 ETS-MITACS project.

Évaluation de l’utilisation du BIM pour deux aéroports au Québec

Le Building Information Modeling (BIM) est une véritable révolution dans la réalisation des projets de construction. Les technologies qui lui sont associées devraient permettre des gains appréciables dans la qualité, les coûts ainsi que les délais de réalisation tout en augmentant la productivité dans la conception et la construction. Cependant de telles retombées ne sont possibles qu’avec une reconfiguration des modes d’échanges d’information entre les différentes entreprises impliquées dans le projet. Cette recherche est une première dans la documentation des problématiques reliées à cette reconfiguration à l’aide de deux cas exceptionnels par leur nature, Aéroport de Québec Inc (AQI) et Aéroports de Montréal (ADM). Elle permettra l’équipe de projet de développer une expertise unique dans la planification et la gestion des projets BIM et à l’AQi de maximiser les retombées du BIM pour leur projet. Elle bénéficiera aussi à toute l’industrie dans la compréhension des enjeux reliés à une implantation performante du BIM.

Building Bridges: The Role of Mentorship in Addressing Youth Gang Involvement Through the Mentorship and Gang Solutions (MAGS) Program

The Mentorship and Gang Solutions (MAGS) program, supported by the Edmonton Police Service (EPS), aims to reduce youth gang involvement through targeted mentorship. This initiative connects high-risk youth with Lived Life Experienced Mentors (LLEMs) who share their own journeys of experiencing similar challenges. These mentors, equipped with firsthand knowledge and understanding, guide youth toward positive life changes and away from gang activities and violence. This research will evaluate the effectiveness of MAGS in facilitating youth reintegration into the community and reducing gang involvement. The research will examine how mentorship impacts youths’ mental health, social behaviour, education, and employment opportunities, while also exploring the experiences and development of the mentors themselves. This evaluation will assess both the implementation process and outcomes of MAGS in facilitating youth reintegration, reducing gang involvement, and fostering stronger community ties. The findings from this study will help refine mentorship practices and enhance community-based strategies to support high-risk youth. By documenting the successes and learnings from the challenges of the MAGS program, we aim to contribute to safer, more supportive environments for Edmonton’s youth, ensuring they have the opportunities and support needed to thrive.

In vitro three dimensional models of breast cancer-cell metastasis to bone.

This MITACS Globalink Award research proposal aims to engineer and characterize biomimetic dense collagenous gels as in vitro models for studying breast cancer metastasis to bone. At McGill, we have advanced the Gel Aspiration-Ejection (GAE) technique, a robust and simple method to create 3D anisotropic, cellular dense collagen (DC) gels. By applying negative pressure, collagen gels are aspirated into a capillary, inducing compaction and mesoscale anisotropy, and then controllably ejected by reversing the pressure. This technique also facilitates the alignment of seeded cells, influencing their morphology and differentiation. Our research has shown that DC gels serve as excellent in vitro bone extracellular matrix-like models, enhancing osteogenic differentiation and matrix mineralization via carbonate hydroxyapatite formation. The goal of this collaboration is to investigate the impact of metastatic breast cancer cells on collagen alignment and osteoblast-mediated mineralization. At UCL, Professor Cheema’s team will provide expertise on three-dimensional in vitro tumor models and the analysis of interactions between breast cancer and osteoblastic cells co-cultured in the GAE-generated DC gels. This collaborative visit will further our understanding of bone metastasis and contribute to developing new strategies for cancer treatment.

Uncovering the genetic basis of adaptation during the course of rapid experimental evolution in nature

Nature is experiencing an ever-changing world where dramatic environmental changes require species to adapt rapidly to new conditions. As a result, understanding when species can rapidly adapt and persist has become crucial to ensuring the preservation of vulnerable populations such as freshwater ecosystems. The current project addresses our limited understanding of the parallelism of adaptation and rapid evolution by studying genetic changes in unique protected populations of threespine stickleback fish in Haida Gwaii, BC. Although these populations are protected under the Species At Risk Act, climate change and human activities can have dramatic impacts on these populations. Understanding how these populations can rapidly adapt to a drastic change of environmental conditions thus helps us understand more generally the potential for evolution to promote long-term preservation of species and the ecosystem services they provide. This project will identify what are the key factors responsible for explaining how populations manage to rapidly adapt to new environments. It will also help identify how parallel is the adaption to similar environmental conditions. Further we will gain a better understanding of the process of adaptation to changing environments which can help protecting these populations and other freshwater environments.

Assessing the Risks of Self-Reinforcing Attacks on Generative AI Systems

(1) the main activities of the partner
ServiceNow develops a platform for client organizations to manage and automate large-scale processes across various industries. In 2020, ServiceNow acquired Element AI to strengthen its presence in the Artificial Intelligence (AI) research landscape and the Canadian AI ecosystem. This acquisition enabled the development of AI-driven products that improve the platform’s capabilities. ServiceNow Research has made significant contributions to the field of foundation models, notably in Natural Language Processing (NLP), and has a strong presence in developing generative models for different data domains.
(2) the challenges the partner aims to solve through this project
The project addresses security risks in commercial AI software systems, focusing on a self-reinforcing attack strategy that progressively poisons databases, influencing AI behavior. It aims to explore these risks and develop defense mechanisms against such stealthy and subtle attacks. This includes examining how untrusted sources, such as web content or emails, can inject malicious data into storage systems, posing significant threats to AI systems using retrieval-augmented generation.
(3) the anticipated social or economic benefits of the project for the partner organization(s)
The project aims to enhance the security and reliability of AI systems by understanding the threats associated with self-reinforcing attacks and developing defenses to protect against them. By open sourcing the findings of this work, we will contribute to safer and more secure AI integration in enterprise environments. This will not only protect sensitive data and reduce potential economic losses but also help bolster user trust of AI technologies and increase the rate at which these technologies can be safely adopted.

Techno-Economic Study on Aircraft Emissions Reduction at the Calgary International Airport

A techno-economy study will be conducted to identify and quantify Scope 3 emissions at the Calgary International Airport to determine the economic impact of financial schemes and/or operational practices that the Calgary Airport Authority can implement to reduce aircraft ground emissions at the airport. Potential financial schemes include incentives, discounts or extra charges, and mandates, while operational practices include tailored operational support and setting minimum performance standards. Data from the Calgary Airport Authority and Transport Canada will be used to evaluate the pros and cons of implementing these schemes/practices on three key operational areas: (i) anti-idling management of ground support equipment; (ii) aircraft class and type of engine; and (iii) aircraft auxiliary power unit management. Expected outcomes will ensure the airport’s pathway toward aircraft emissions reductions and energy use efficiencies, strengthening its position as the fourth busiest airport in Canada and assisting the airport authority in achieving its net-zero targets.

Parksville and District Chamber of Commerce – Stakeholder Engagement & Program Development

The Parksville and District Chamber of Commerce (PDCC) serves as a central hub for local businesses, fostering economic growth, business networking, and community engagement. As the business landscape evolves, PDCC aims to enhance its event programming, marketing strategy, and member engagement while ensuring its initiatives are data-driven and impactful.

To support this vision, PDCC is seeking an MBA intern to:

Strengthen event planning, program development, and internal marketing strategies.

Enhance member engagement through digital outreach, social media, and communications.

Incorporate data collection and analysis to measure event success and community impact.

This internship offers hands-on experience in event coordination, marketing, community engagement, and business strategy, providing a unique opportunity for professional development while supporting real-world impact.

Gut-localized expression of IL-10 for the treatment and/or prevention of peanut allergy

We will evaluate treatments for peanut allergy, the most severe and persistent form of food allergy. The proposed interventions are based on targeted delivery of interleukin-10 (IL-10) to the intestine. IL-10 is a protein that is known to be a potent regulator of the immune system. enGene has developed EG-10, a novel, state-of-the-art technology that can effectively induce a robust and transient production of interleukin-10 in the intestine, i.e., the site where food absorption occurs and food allergy is initiated. enGene can benefit from our demonstrated knowledge in the immunobiology of food allergy and our extensive expertise with mouse models for peanut allergy and anaphylaxis, which we have shown to closely resemble the features of anaphylaxis seen in humans with peanut allergy. In collaboration with enGene, we will investigate the impact of EG-10 on the prevention (prophylactic) and treatment (immunotherapy) of peanut allergy and anaphylaxis

Policy Innovation – CIGI

CIGI aims to address the lack of knowledge relating to regulations and decision-making of emerging dual-use technology. This initiative will focus on quantum technologies as a case-study. There is a need for knowledge-building, knowledge-translation and innovation to advance a technology-dynamics perspective in forming decisions on emerging dual-use technology (quantum). To address this need, CIGI proposes three Policy Innovation Assistants to support the CIGI team dedicated to leading this initiative. This includes analytical, knowledge development and engagement support to CIGI’s Research Director, Transformative Technologies.

ESROP – KMUTT – Hybrid LSTM-GRU Architecture with Adaptive Attention for Financial Data

This research project focuses on using advanced machine learning techniques to better predict stock prices, specifically targeting stocks from the S&P 500. By combining powerful deep learning methods—such as LSTM and GRU networks—with adaptive attention mechanisms inspired by Transformer models, the project aims to create forecasting systems that can dynamically adapt to changing market conditions, like sudden increases in volatility or shifts between bull and bear markets. Currently, traditional models struggle when markets behave unpredictably, leading to less accurate forecasts. The new approach developed through this project could improve forecasting accuracy, helping financial institutions and researchers manage risk and make better-informed investment decisions. For both participating institutions—KMUTT and the University of Toronto — this collaboration will enhance their expertise in quantitative finance, encourage further research, and support the adoption of innovative AI-driven financial modeling techniques.