Prof. Jing OUYANG
創新及資訊管理學
Assistant Professor
3910 3107
KK 1020
Academic & Professional Qualification
- Ph.D. in Statistics, University of Michigan, 2024
- BSc. in Mathematics and Economics, HKUST, 2019
Biography
Prof. Jing Ouyang is an Assistant Professor in Innovation and Information Management at HKU Business School. Prior to joining HKU, Jing received a Ph.D. in Statistics from University of Michigan in 2024 and a BSc. in Mathematics and Economics from Hong Kong University of Science and Technology in 2019.
Research Interest
- Latent variable models
- Psychometrics
- High-dimensional statistical inference
- Statistical machine learning
Selected Publications
- J. Ouyang, K. M. Tan, and G. Xu (2023) “High-dimensional Inference for Generalized Linear Models with Hidden Confounding.” Journal of Machine Learning Research, 24(296):1−61.
- Y. Chen, C. Li, J. Ouyang, and G. Xu (2023) “Statistical inference for noisy incomplete binary matrix.” Journal of Machine Learning Research, 24(95):1−66.
- Y. Chen, C. Li, J. Ouyang, and G. Xu (2023) “DIF Statistical Inference without Knowing Anchoring Items.” Psychometrika, 88, 1097–1122.
- C. Ma, J. Ouyang, C. Wang, and G. Xu (2024) “A note on improving variational estimation for multidimensional item response theory.” Psychometrika, 89, 172–204.
- C. Ma, J. Ouyang, and G. Xu (2023) “Learning latent and hierarchical structures in cognitive diagnosis models.” Psychometrika, 88, 175–207.
- J. Ouyang and G. Xu (2022) “Identifiability of latent class models with covariates.” Psychometrika, 87, 1343–1360.