Victoria Chui

Victoria Chui

PhD Student in Information: Human-Centered Data Science

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publications

Applying Human-Centered Data Science to Healthcare: Hyperlocal Modeling of COVID-19 Hospitalizations

Published in GROUP 2023: Companion Proceedings of the 2023 ACM International Conference on Supporting Group Work, 2023

We examine previous work in healthcare executed with a human-centered design, to analyze the multiple frameworks which effectively create human-centered application, as extended to healthcare.

Recommended citation: Victoria Chui, Jessica Pater, Tammy Toscos, and Shion Guha. 2023. Applying Human-Centered Data Science to Healthcare: Hyperlocal Modeling of COVID-19 Hospitalizations. In Companion Proceedings of the 2023 ACM International Conference on Supporting Group Work (GROUP 23). Association for Computing Machinery, New York, NY, USA, 24–26. https://doi.org/10.1145/3565967.3570979 http://victoriachui.github.io/files/hcds.pdf

Towards Human-Centered Models in Healthcare: Development of Practical Applications for Surgical Wards

Published in tspace.library.utoronto.ca, 2023

This thesis outlines the process of implementing a human-centered design through model development, comparing results of these models to those previously seen in literature.

Recommended citation: Victoria Chui. 2023. Towards Human-Centered Models in Healthcare: Development of Practical Applications for Surgical Wards. Master’s Thesis. University of Toronto, Toronto, Canada. https://tspace.library.utoronto.ca/handle/1807/129773

Principles and Practices of Engaging Communities in Socially Responsible Deployment of Artificial Intelligence for Population Health: Findings from the AI for Diabetes Prediction and Prevention Project

Published in Canadian Association for Health Services and Policy Research Conference, 2025

This presentation explores community engagement strategies for responsible AI development and deployment in Canadian public health settings.

Recommended citation: Abejirinde IO, Itanyi I, Kornas K, Zaim R, Guha S, Chui V, Lipscombe L, Rosella L, Shaw J (2025, May 25–29). Principles and Practices of Engaging Communities in Socially Responsible Deployment of Artificial Intelligence for Population Health: Findings from the AI for Diabetes Prediction and Prevention Project. Canadian Association for Health Services and Policy Research Conference, Ottawa, Canada.

A participatory approach to deploy responsible artificial intelligence for diabetes prediction and prevention

Published in DIGITAL HEALTH, 2025

In this commentary, we discuss the planned use of participatory approaches to responsibly deploying validated machine learning models, with a specific case example of diabetes prediction models that can address the challenge of preventing and managing diabetes in a health system.

Recommended citation: Laura C Rosella, James Shaw, Shion Guha, Ibukun-Oluwa Omolade Abejirinde, Jennifer L Gibson, Lorraine Lipscombe, Kathy Kornas, Remziye Zaim, Victoria Chui, and Ijeoma Uchenna Itanyi. 2025. A participatory approach to deploy responsible artificial intelligence for diabetes prediction and prevention. DIGITAL HEALTH 11, (2025), 20552076251358540. https://doi.org/10.1177/20552076251358541

Towards Sustainable Community-Designed AI Systems in the Public Sector

Published in ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS ’25), 2025

This workshop aims to create a space for interdisciplinary dialogue, hands-on collaboration, and knowledge-sharing around the development of sustainable, community-informed AI systems in the public sector.

Recommended citation: Victoria Chui, Kelly McConvey, Erina Seh-Young Moon, Maya Ghai, and Shion Guha. 2025. Towards Sustainable Community-Designed AI Systems in the Public Sector. In ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS ’25), July 22–25, 2025, Toronto, ON, Canada. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3715335.3737683

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