Xiangyu Luo is an assistant professor at the Institute of Statistics and Big Data, Renmin University of China, starting from Sep. 2018. He obtained his Ph.D. degree from Department of Statistics, The Chinese University of Hong Kong in 2018 and was supervised by Prof.Yingying Wei. Prior to that, Xiangyu Luo graduated from Department of Statistics and Finance, University of Science and Technology of China with a Bachelor of Science degree in 2014.

Xiangyu Luo has broad research interests in Bayesian statistics, nonparametric Bayes, statistical genomics, bioinformatics, statistical computing, and statistical learning. He likes involving in developing novel statistical models to solve practical biological problems. His specific research fields include reconstructing biological regulatory/co-expression networks via statistical graphical models, correcting batch effects in high-throughput genomic data, deconvoluting methylation signals in epigenome-wide association studies, discovering subject heterogeneity at single-cell resolution, and multi-omics data integration.

Please visit my homepage https://sites.google.com/view/xiangyuluo for more information.

Selected Publications:

Qiuyu Wu^, Xiangyu Luo*. Nonparametric Bayesian two-level clustering for subject-level single-cell expression data. Statistica Sinica. [in press, software SCSC]

Xiangyu Luo, Joel Schwartz, Andrea Baccarelli, Zhonghua Liu* (2020) Testing cell-type-specific mediation effects in genome-wide epigenetic studies. Briefings in Bioinformatics. [paper link, software MICS]

Xiangyu Luo, Can Yang*, and Yingying Wei* (2019) Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies. Nature Communications, Volume 10, Article number: 3113. [paper link, software HIREewas]

Xiangyu Luo, and Yingying Wei* (2019) Batch effects correction with unknown subtypes. Journal of the American Statistical Association, 114:526, 581-594. [paper link, software BUScorrect]

Xiangyu Luo, and Yingying Wei* (2018) Nonparametric Bayesian learning of heterogeneous dynamic transcription factor networks. The Annals of Applied Statistics, Vol. 12, No. 3, 1749-1772. [paper link, C code]

(note: * indicates the corresponding author, and ^ represents supervised students.)