I am dedicated to developing novel statistical methods tailored for handling complex structured data and addressing associated challenges. My specific areas of interest encompass data fusion, transfer learning, high-dimensional inference, measurement errors, missing data and compositional data analysis.
If you are interested in my research, please feel free to email me and we can discuss further. Looking forward to working on an interesting research project together.
Publications
- Zhao, H. and Wang, T. (2024). “Debiased high-dimensional regression calibration for errors-in-variables log-contrast models”, Biometrics.
- Zhao, H. and Wang, T. (2026+). “Doubly robust transfer learning under sub-group shift for cohort-level missing indicator covariates”, Statistica Sinica, accepted.
Under Review
- Zhao, H. and Wang, T. (2025+). “A simulation-free extrapolation method for misspecified models with errors-in-variables in epidemiological studies”.
- Zhao, H. and Wang, T. (2025+). “Augmented transfer regression learning for handling completely missing covariates”.
- An earlier version won the 2025 IMS Hannan Graduate Student Travel Award
Working Papers
- Zhao, H. and Deng, K. (2025+). “Transfer learning for generalized linear models with completely missing data”.
- Zhao, H., Liu, M., and Wang, T. (2025+). “A data fusion framework for errors-in-variables”.
- Zhao, H. and Deng, K. (2026+). “A low-rank hierarchical ANOVA logistic model for imported food data studies”.