Yuhan (Angelina) Zhou
Ph.D. Student in Information Science, Data Science Concentration
Better data.
Thoughtful AI.
How data quality shapes AI systems?
How can AI systems better support the people who use them?
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Biography
I am a Ph.D. student in Information Science, with a concentration in Data Science, at the University of North Texas and a researcher in the Intelligent Data Engineering and Analytics (IDEA) Lab. I am interested in a question that connects my work across domains: what makes data—and the AI built from it—useful in real settings? In healthcare, I study how diverse expressions of medical concepts can be brought together into more reliable datasets. In autonomous driving, I examine how the quality and redundancy of multisource, multimodal data affect the tasks a system needs to perform. Through ALiT, I am extending that interest to AI-supported professional learning for librarians. Together, these projects connect data evaluation and improvement with thoughtful AI applications that support human expertise.
Ph.D. · University of North Texas · 2024–present
M.Sc. Business Analytics · University of Hong Kong · 2023
B.Sc. Information Resource Management · Zhejiang University · 2022
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News
New book chapter on data quality
Our book chapter, Data Quality: Models, Measures, and Tools, in the Springer Handbook of Data Engineering, is now available.
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New book chapter on data quality
Joining ALiT as a Research Assistant
I am joining the IMLS-funded ALiT project as a Research Assistant for the next three years, working on AI-supported professional learning for librarians.
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Joining ALiT as a Research Assistant
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Publications
Publications
A comprehensive survey on medical concept normalization: Datasets, techniques, applications, and future directions.
H. Chen, Y. Zhou, R. Li, A. M. Illa, A. Cleveland, J. Ding.
Journal of Biomedical Informatics 178, 105005 · 2026
Quality-aware multi-source data fusion and enhancement for Medical Concept Normalization using Large Language Models.
Y. Zhou, R. Li, A. Cleveland, J. Ding, K. Sha, H. Chen.
Journal of Biomedical Informatics, 105093 · 2026
A novel multi-layer task-centric and data quality framework for autonomous driving.
Y. Zhou, H. Chen, K. Sha.
IEEE Internet Computing · 2026
Modeling and Measuring Redundancy in Multisource Multimodal Data for Autonomous Driving.
Y. Zhou, M. Sattari, H. Chen, K. Sha.
IEEE MOST 2026 · Best Paper Award
Disaster Informatics after the COVID-19 Pandemic: Bibliometric and Topic Analysis based on Large-scale Academic Literature.
N. Tran, H. Chen, A. Cleveland, Y. Zhou.
arXiv preprint · 2025
A survey on data quality dimensions and tools for machine learning.
Y. Zhou, F. Tu, K. Sha, J. Ding, H. Chen.
IEEE AItest · 2024