M.S., Ph.D. in Statistics, University of Iowa

B.E. in Automatic Control, Dalian University of Technology

Dr. Liu is an Associate Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen, and elected member in the International Statistical Institute. Dr. Liu graduated at the School of Electronics and Information of Dalian University of Technology. He earned both M.S. and Ph.D. degree in Statistics at the Department of Statistics and Actuarial Science of University of Iowa. Dr. Liu got his postdoc training at the Department of Biostatistics, Yale University, USA.

Dr. Liu’s research is primarily focused on statistical genetics/genomics, bioinformatics, AI4Science, and machine learning. He is interested in solving practical problems for single-cell/spatial omics, developing MR methods to draw causal inference with practical considerations, and developing unified TWAS methods using summary-level GWAS and single/multi-tissue eQTL data. His collaborative research includes cancer genomics, metabolism, and biotech in telomere length measurement.

Since 2015, Dr. Liu has won the Academic Research Fund (AcRF Tier 2, PI) from the Ministry of Education of Singapore four times, the Thematic Programs Fund from the Institute of Mathematical Sciences, National University of Singapore in 2019, for organizing international workshop in statistical genetics/genomics, and the Khoo Bridge Funding Award from Duke-NUS in 2021. Currently, his research is supported by NSFC, Guangdong province and Shenzhen municipality.

Methodology:

1. Liao, X., Kang, L., Peng, Y., Chai, X., … Jiao, Y.*, & Liu, J.* (2024). Multivariate stochastic modeling for transcriptional dynamics with cell-specific latent time using SDEvelo. Nature Communications, 15(1), 10849.
2. Huang, J., Jiao, Y., Kang, L.*, Liao, X., Liu, J.*, & Liu, Y. (2024). Schrödinger-Föllmer sampler: sampling without ergodicity. IEEE Transactions on Information Theory, accepted.
3. Lu, Y., Oliva, M., Pierce, B. L., Liu, J.*, & Chen, L. S.* (2024). Integrative cross-omics and cross-context analysis elucidates molecular links underlying genetic effects on complex traits. Nature Communications, 15(1), 2383.
4. Huang, J., Jiao, Y., Liao, X., Liu, J.*, & Yu, Z. (2024). Deep dimension reduction for supervised representation learning. IEEE Transactions on Information Theory, 70(5), 3583-98.
5. Shi, X.*, Yang, Y., Ma, X., Zhou, Y., Guo, Z., Wang, C., & Liu, J.* (2023). Probabilistic cell/domain-type assignment of spatial transcriptomics data with SpatialAnno. Nucleic Acids Research, 51(22), e115-e115.
6. Liu, W., Liao, X., Luo, Z., Yang, Y., Lau, M. C., Jiao, Y., ... & Liu, J.* (2023). Probabilistic embedding and clustering with alignment for spatial transcriptomics data integration with PRECAST. Nature Communications, 14(1),296.
7. Zhou, X., Jiao, Y., Liu, J., & Huang, J. (2023). A deep generative approach to conditional sampling. Journal of the American Statistical Association, 118(543), 1837-1848.
8. Liu, W., Lin, H., Zheng, S., & Liu, J. (2023). Generalized factor model for ultra-high dimensional correlated variables with mixed types. Journal of the American Statistical Association, 118(542), 1385-1401.
9. Cheng, Q., Zhang, X., Chen, L. S.*, & Liu, J.* (2022). Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology. Nature Communications, 13(1), 6490.
10. Liu, W., Liao, X., Yang, Y., Lin, H., Yeong, J., Zhou, X., ... & Liu, J.* (2022). Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data. Nucleic Acids Research, 50(12), e72-e72.
11. Yang, Y., Shi, X., Liu, W., Zhou, Q., Chan Lau, M., Chun Tatt Lim, J., ... & Liu, J.* (2022). SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes. Briefings in bioinformatics, 23(1), bbab466.
12. Shi, X., Chai, X., Yang, Y., Cheng, Q., Jiao, Y., Chen, H., ... & Liu, J.* (2020). A tissue-specific collaborative mixed model for jointly analyzing multiple tissues in transcriptome-wide association studies. Nucleic acids research, 48(19), e109-e109.
13. Yang, Y., Shi, X., Jiao, Y., Huang, J., Chen, M., Zhou, X., ... & Liu, J.* (2020). CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies. Bioinformatics, 36(7), 2009-2016.
14. Cheng, Q., Yang, Y., Shi, X., Yeung, K. F., Yang, C., Peng, H., & Liu, J.* (2020). MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy. NAR genomics and bioinformatics, 2(2), lqaa028.
15. Yang, C., Wan, X., Lin, X., Chen, M., Zhou, X., & Liu, J.* (2019). CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information. Bioinformatics, 35(10), 1644-1652.

 Collaborative:

16. Zhu, S., Xie, P., Zhang, Y., Zhang, J., Yang, Y., Fang, K., … & Lin, C. (2025) Maternal ELL3 loss-of-function leads to oocyte aneuploidy and early miscarriage. Nature Structural & Molecular Biology, accepted.
17. Liu, X., Zhang, K., Kaya, N. A., Jia, Z., Wu, D., Chen, T., ... & Zhai, W. (2024). Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma. Nature Communications, 15(1), 3169.
18. Tham, C.Y., Poon, L., Yan, T., Koh, J.Y., Ramlee, M.K., Teoh, V.S., ...& Li, S. (2023) High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform. Nature Communications, 14(1), 281.
19. Kaya, N. A., Chen, J., Lai, H., Yang, H., Ma, L., Liu, X., ... & Zhai, W. (2022). Genome instability is associated with ethnic differences between Asians and Europeans in hepatocellular carcinoma. Theranostics, 12(10), 4703.
20. Goh, D., Lee, J. N., Tien, T., Lim, J. C. T., Lim, S., Tan, A. S., ... & Yeong, J. (2022). Comparison between non-pulmonary and pulmonary immune responses in a HIV decedent who succumbed to COVID-19. Gut, 71(6), 1231-1234.
21. Zhou, Q., Wan, Q., Jiang, Y., Liu, J., Qiang, L., & Sun, L. (2020). A landscape of murine long non-coding RNAs reveals the leading transcriptome alterations in adipose tissue during aging. Cell reports, 31(8), 107694.
22. Chen, J., Yang, H., Teo, A. S. M., Amer, L. B., Sherbaf, F. G., Tan, C. Q., ... & Zhai, W. (2020). Genomic landscape of lung adenocarcinoma in East Asians. Nature genetics, 52(2), 177-186.
23. Yeong, J., Tan, T., Chow, Z. L., Cheng, Q., Lee, B., Seet, A., ... & Tan, P. H. (2020). Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC. Journal of Clinical Pathology, 73(9), 557-562.
24. Yuan, Z., Zhu, H., Zeng, P., Yang, S., Sun, S., Yang, C., ... & Zhou, X. (2020). Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies. Nature communications, 11(1), 1-14.
25. Yeong, J., Lim, J. C. T., Lee, B., Li, H., Ong, C. C. H., Thike, A. A., ... & Tan, P. H. (2019). Prognostic value of CD8+ PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer. Journal for immunotherapy of cancer, 7(1), 1-13.