Dr. Cai obtained his PhD degree from The Hong Kong University of Science and Technology in 2022. He received his BSc and MPhil in Statistics from Hong Kong Baptist University. His broad area of interest lies in statistical machine learning and data science with applications in genetics and genomics data analysis. He has been working on scalable statistical methods for high dimensional regression problems and integrative analysis of multi-omics data.
Research Grants
- Single-cell eQTL Mapping Based on Multi-Resource Heterogeneous Data, Young Scientists Fund, Guangdong-Hong Kong-Macau National Center for Applied Math, 2026 - 2027, Mingxuan Cai (PI).
- Statistical and Computational Methods for Causal Inference by Integrating Multi-ancestry Genetic Data, Young Scientists Fund, The National Natural Science Foundation of China, 2026 - 2028, Mingxuan Cai (PI).
- A Statistical Method for Expression Quantitative Trait Loci Mapping with Single-cell RNA-seq Data, REG-Small Scale, City University of Hong Kong, 2025 - 2027, Mingxuan Cai (PI), Xianghong Hu (Co-I).
- Development of Statistical Methods for Multi-ancestry Transcriptome-wide Association Studies, Early Career Scheme, Research Grants Council of Hong Kong, 2025 - 2028, Mingxuan Cai (PI).
Journal
- Liu, Ye. , Zou, Wanpeng. , Li, Yuekai. , Wang, Jiayi. , Cai, Mingxuan. & Cai, Hongmin. (2026). Cross-Modal Denoising and Integration of Spatial Multi-Omics Data with CANDIES. Advanced Science. Online. e23754 doi:10.1002/advs.202523754
- Li, Yuekai. , Xiao, Jiashun. , Ming, Jingsi. & Cai, Mingxuan. (2025). Funmap: integrating high-dimensional functional annotations to improve fine-mapping. Bioinformatics. 41(7). btaf017 doi:10.1093/bioinformatics/btaf017
- Wang, Zhiwei. , Zhang, Fa. , Zheng, Cong. , Hu, Xianghong. , Cai, Mingxuan. & Yang, Can. (2024). MFAI: A Scalable Bayesian Matrix Factorization Approach to Leveraging Auxiliary Information. Journal of Computational and Graphical Statistics. 33(4). 1339 - 1349. doi:10.1080/10618600.2024.2319160
- Cai, Mingxuan. , Wang, Zhiwei. , Xiao, Jiashun. , Hu, Xianghong. , Chen, Gang. & Yang, Can. (2023). XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias. Nature Communications. 14. 6870 doi:10.1038/s41467-023-42614-7
- Xiao, Jiashun. , Cai, Mingxuan. , Yu, Xinyi. , Hu, Xianghong. , Chen, Gang. , Wan, Xiang. & Yang, Can. (2022). Leveraging the local genetic structure for trans-ancestry association mapping. The American Journal of Human Genetics. 109(7). 1317 - 1337. doi:10.1016/j.ajhg.2022.05.013
- Xiao, Jiashun. , Cai, Mingxaun. , Hu, Xianghong. , Wan, Xiang. , Chen, Gang. & Yang, Can. (2022). XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. Bioinformatics. 38(7). 1947 - 1955. doi:10.1093/bioinformatics/btac029
- Cai, Mingxuan. , Xiao, Jiashun. , Zhang, Shunkang. , Wan, Xiang. , Zhao, Hongyu. , Chen, Gang. & Yang, Can. (2021). A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits. The American Journal of Human Genetics. 108(4). 632 - 655. doi:10.1016/j.ajhg.2021.03.002
- Cai, Mingxuan. , Dai, Mingwei. , Ming, Jingsi. , Peng, Heng. , Liu, Jin. & Yang, Can. (2020). BIVAS: a scalable Bayesian method for bi-level variable selection with applications. Journal of Computational and Graphical Statistics. 29(1). 40 - 52. doi:10.1080/10618600.2019.1624365
- Cai, Mingxuan. , Chen, Lin. S. , Liu, Jin. & Yang, Can. (2020). IGREX for quantifying the impact of genetically regulated expression on phenotypes. NAR Genomics and Bioinformatics. 2(1). lqaa010 doi:10.1093/nargab/lqaa010
Openings
- I am looking for highly motivated students with background in statistics, biostatistics, applied statistics, or computer science. Priority will be given to those with a strong interest in statistical genetics and genomics, as well as strong programming skills in R/Python. If you are interested, please send me your CV and transcripts via email.
Last update date :
28 Apr 2026
