Hongyuan Cao

In addition to her position at MBZUAI, Professor Cao is a Professor in the Department of Statistics at Florida State University, having previously held faculty appointments at the University of Missouri – Columbia and the University of Chicago.

• Ph.D. in Statistics from the University of North Carolina-Chapel Hill.
• Bachelor of Science in Mathematics and Applied Mathematics from Zhejiang University.

• ASA fellow, 2024.
• ENAR distinguished student paper award, 2009.

• Wang, P., Lyu, P., Peddada, S., Cao, H.: "Statistical analysis of correlated expression data from high throughput experiments." Genetics, accepted, 2025.
• Dayu Sun, Zhuowei Sun, Xingqiu Zhao, Hongyuan Cao: "Kernel meets sieve: transformed hazards models with sparse longitudinal covariates." JASA, accepted, 2025.
• Sun, Z. and Cao, H.: "Regression analysis of multiplicative hazards model with time-dependent coefficient for sparse longitudinal covariates." Journal of Non-parametric Statistics, accepted, 2025.
• Kley, T., Liu, Y., Cao, H. and Wu, W. B.: "Change point analysis with irregular signals." Annals of Statistics, 52(6), 2024.
• Li, Y., Zhou, X., Chen, R., Zhang, X. and Cao, H.: "STAREG: statistical replicability analysis of high throughput experiments with applications to spatial transcriptomic studies." PLOS Genetics, 20(10), 2024.
• Li, Y., Lei, H., Wen, X., and Cao, H.: "A powerful approach to identify replicable variants in genome-wide association studies." American Journal of Human Genetics, 111, 2024.
• Sun, Z., Cao, H., Chen, L. and Fine, J. P.: "Analysis of longitudinal data with omitted asynchronous longitudinal covariate." Journal of Statistical Planning and Inference, 231, 2024.
• Liu, C., Sun, Z. and Cao, H.: "Regression analysis of mixed sparse synchronous and asynchronous longitudinal data in varying-coefficient regression models." Electronic Journal of Statistics, 17, 2023.
• Lyu, P., Li, Y., Wen, X. and Cao, H.: "JUMP: replicability analysis of high-throughput experiments with applications to spatial transcriptomic studies." Bioinformatics, 39(6), 2023.
• Boadu, F., Cao, H. and Cheng, J: "Combining protein sequences and structures with transformers and equivariant graph neural networks to predict protein function." Bioinformatics, 39, 2023.
• Cao, H., Chen, J. and Zhang, X.: "Optimal false discovery rate control for large-scale multiple testing with auxiliary information." Annals of Statistics, 50, 2022.
• Li, Y., Zhou, X. and Cao, H.: "Statistical analysis of spatially resolved transcriptomic data by incorporating multi-omics auxiliary information." Genetics, 221(4), 2022.
• Sun, Z., Cao, H., and Chen, L.: "Regression analysis of additive hazards model with sparse longitudinal covariates." Lifetime Data Analysis, 28, 2022.
• Cao, H. and Wu, W.: "Testing and estimation for clustered signals." Bernoulli, 28, 2022.