Yuanying (Yuna) Pang is a Ph.D. candidate in the School of Information at Florida State University. My work bridges data science, health informatics, and human-computer interaction, with a strong emphasis on designing and evaluating AI-based interventions to promote adherence to digital cognitive training programs among older adults. I has published in journals such as PLOS ONE, JMIR Aging, and Journal of the Association for Information Science and Technology, and co-authored an ARIST paper on data quality assurance practices. I also contribute actively as a journal and conference reviewer (AMIA, PLOS ONE, BMC, etc.) and have received awards, including the Outstanding Doctoral Research Award and a Reviewer Award from the AMIA Informatics Summit. I was also nominated as one of four FSU candidates for the prestigious Google PhD Fellowship.

• Ph.D., Information (Health Informatics), Florida State University, 2022–2026 (expected)

• M.S., Data Science, American University, 2019–2021

• B.S., Mathematics and Applied Mathematics, Hainan University, 2015–2019

My research interests center on health informatics, data quality assurance, and digital health interventions. I focus on improving older adults’ adherence to technology-based cognitive training through predictive modeling, personalized AI-driven support systems, and social interaction features. I also study data quality assurance in research data repositories, aiming to strengthen reproducibility, sharing, and reuse of scientific data.

I have taught and assisted courses in database management, information architecture, innovation and emerging technologies, and information technology project management. My teaching interests include health informatics, data science, artificial intelligence in healthcare, research methods, and information systems, with a focus on equipping students to apply computational and analytical skills to real-world problems.

Research Projects

• Adherence Promotion Person-centered Technology (APPT) – Predicting adherence to gamified cognitive training and developing AI-driven reminder systems.

• DeepCare Project – Exploring AI approaches to improve social connectedness and emotional well-being among older adults at risk for ADRD.

• Data Quality Assurance (DQA) Project – Systematic analysis of practices in research data repositories; developed a conceptual DQA model and ontology.

Refereed Journal Articles

1. Stvilia, B., Pang, Y., Lee, D. J., & Gunaydin, F. (2024). Data quality assurance practices in research data repositories—A systematic literature review. An Annual Review of Information Science and Technology (ARIST) paper. Journal of the Association for Information Science and Technology, 76(1), 238-261.
2. Pang, Y., Singh, A., Chakraborty, S., Charness, N., Boot, W. R., & He, Z. (2024). Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy. PloS one, 19(10), e0311279.
3. Singh, A., Chakraborty, S., He, Z., Pang, Y., Zhang, S., Subedi, R., … & Boot, W. (2024). Predicting adherence to computer-based cognitive training programs among older adults: study of domain adaptation and deep learning. JMIR aging, 7(1), e53793.
4. Lee, D. J., Stvilia, B., Gunaydin, F., & Pang, Y. (2025). Developing a data quality assurance ontology for research data repositories. Journal of Documentation, 81(7), 63-84.
5. He, Z., Pang, Y., von Hollen, L. et al.Usability and acceptance of in-app social-interacting features for promoting adherence to computerized cognitive training: a pilot evaluation. J Cogn Enhanc 9, 439–454 (2025). https://doi.org/10.1007/s41465-025-00337-1.
6. Stvilia, B., Lee, D. J., Pang, Y., & Gunaydin, F. (2025). Challenges in ensuring data quality in research data repositories: A theoretical examination. Journal of Information Science, 01655515251353171.
7. Subedi, R., Chakraborty, S., He, Z., Pang, Y., Zhang, S., Lustria, M. L., … & Boot, W. (2026). Predicting adherence to computer-based cognitive training programs among older adults using source-free domain adaptation: Algorithm development and validation. JMIR aging, 9, e79123.

Peer-Reviewed Conference Publications

8. Pang,Y., Atrinawati, L., Li, R., He, Z., Lustria, M. L., (2026). Voices from Reddit users’ experiences and opinions on generative AI for health problems, Proceedings of the IEEE International Conference on Healthcare Informatics

Peer-Reviewed Conference Abstracts

9. Lee Dong Joon, Ali, F., Stvilia, B., Pang, Y., & Gonthina, K. (2023). Toward the conceptualization of data quality assurance in research data repositories. Proceedings of the Association for Information Science and Technology, 60(1), 1019-1021.
10. Pang, Y., Atrinawati, L., Li, Ruoyu,Lustria, M. L. A., & He, Z. (April 2–4, 2026). Understanding how people use generative AI for health: Insights from Reddit posts. 2026 Kentucky Conference on Health Communication. Lexington, KY.

Still In Process

11. Yuanying Pang, Zhe He, Ruoyu Li, Mia Lisa A Lustria, Walter Boot (2025). Conceptualizing user or technology engagement in digital behavior interventions. Unpublished manuscript. (Still in Process)

• Reviewer Award for the AMIA Informatics Summit
• Outstanding Doctoral Research Award 
• Google PhD Fellowship Nominee  
• Dissertation Research Grant ($1,000), Florida State University
• Top Six Poster Award (Honorable Mention) Kentucky Conference on Health Communication, 2026