Personal profile
Personal profile
Dr. Amanda Chu is currently an assistant professor at The Education University of Hong Kong (EdUHK). She received her Ph.D. from The University of Hong Kong, Master’s degree in Business Administration from The Chinese University of Hong Kong, and Bachelor’s degree in Social Sciences (Statistics) from The University of Hong Kong. She is also a certified Financial Risk Manager of Global Association of Risk Professionals (GARP) and a certified Professional Risk Manager of the Professional Risk Managers’ International Association (PRMIA). Her research interests include risk management, health care analytics, and applied statistics. She has papers in journals like Annals of Applied Statistics, Journal of Econometrics, Decision Support Systems, Journal of Business Ethics, Statistical Methods and Medical Research, among others.
Before starting her academic career, Dr. Chu has obtained 10 years of experience in consulting, market research, risk management, and business development. She managed over five government-funded research projects and more than 10 industry collaborative projects with various associations and global companies when she was a consultant in the industry.
Research interests
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Collaborations and top research areas from the last five years
Research Outputs
- 65 Articles
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Nurses’ knowledge, attitudes, and role perception in medication administration: Do hospital context and nurses’ level of professional experience make a difference?
CHU, M. Y. A., SO, H.-Y., YU, L. W. L., HO, B. P. Y., CHANG, S. S. Y., CHAN, L. S. H., OR, C. K. L. & SO, M. K. P., Jan 2026, In: BMC Nursing. 25, 37.Research output: Contribution to journal › Articles › peer-review
Open Access -
A hybrid Markov chain monte Carlo approach for structural learning in Bayesian networks based on variable blocking
CHAN, L. S. H., CHU, M. Y. A. & SO, M. K. P., Mar 2025, (E-pub ahead of print) In: Bayesian Analysis.Research output: Contribution to journal › Articles › peer-review
Open Access -
A multivariate randomized response model for mixed-type data
CHU, M. Y. A., OMORI, Y., SO, H.-Y. & SO, M. K. P., 2025, In: Journal of Applied Statistics. 52, 14, p. 2597-2635Research output: Contribution to journal › Articles › peer-review
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Dynamic network Poisson autoregression with application to COVID-19 count data
ASAI, M., CHU, M. Y. A. & SO, M. K. P., 2025, In: Journal of Data Science. 23, 1, p. 208-224Research output: Contribution to journal › Articles › peer-review
Open Access1 Link opens in a new tab Citation (Scopus) -
Utilizing Google Trends data to enhance forecasts and monitor long COVID prevalence
CHU, M. Y. A., TSANG, J. T. Y., CHAN, S. S. C., CHAN, L. S. H. & SO, M. K. P., 2025, In: Communications Medicine. 5, 179.Research output: Contribution to journal › Articles › peer-review
Open Access4 Link opens in a new tab Citations (Scopus)