占翔，必威betway西汉姆博士生导师。2015年毕业于美国宾夕法尼亚州立大学，获得统计学博士学位。2017年-2021年，在美国宾夕法尼亚州立大学公共卫生学院，担任助理教授职位。2021年-2024年，在北京大学公共卫生学院和北京国际数学研究中心，担任副教授职位。2024年-至今，在必威betway西汉姆，担任教授职位。

2016年，获国际生物统计学会北美东部地区分会（IBS-ENAR）年会优秀博士生论文奖。2017、2021年，获美国统计学会(ASA)联合统计会议(JSM)生物统计分会（Biometrics Section）的David P. Bayer青年学者论文奖。2021年，指导博士生的论文获国际印度裔统计学家协会（IISA）年会最佳应用统计论文奖。主要研究方向为生物统计、遗传统计、高维成分数据分析、核方法等。在Journal of the American Statistical Association、Annals of Applied Statistics、Biometrics、Bioinformatics等统计、生物统计、生物信息学相关领域的核心期刊上发表过50余篇SCI论文。

Dr. Zhan Xiang is a Professor and Doctoral Supervisor at the School of Statistics and Data Science, Southeast University. He obtained his Ph.D. in Statistics from Pennsylvania State University, USA, in 2015. From 2017 to 2021, he served as an Assistant Professor at the Department of Public Health, Pennsylvania State University. Subsequently, from 2021 to 2024, he held the position of Associate Professor at the School of Public Health and Beijing International Center for Mathematical Research at Peking University. Since 2024, he has been a Professor at the School of Statistics and Data Science at Southeast University.

His primary research areas include biostatistics, statistical genetics, high-dimensional compositional data analysis, and kernel methods. He has published multiple articles in major statistics, biostatistics and bioinformatics journals such as JASA,Annals of Applied Statistics,Biometrics, andBioinformatics. If you have any queries, please email Dr. Zhan for more information.

1. 国家自然科学基金面上项目（12371287），基于高维微生物组学成分数据的新型统计方法和理论，2024-2027（主持）

2.科技部国家重点研发计划生物大分子与微生物组专项（2022YFA1305400），细胞外囊泡纳米尺度空间组学分析与实时动态监测技术的研发，2022-2027（参与）

3.美国国立健康研究院（NIH）R21项目（R21AI144765），Novel statistical methods for controlled variable selection of microbiome data，2020-2021（主持）

4.美国国家科学基金委（NSF）标准项目（DMS1953189），Collaborative Research: New Methods, Theory and Applications for Nonsmooth Manifold-Based Learning，2020-2021（共同主持）

5.美国国立健康研究院（NIH）科学中心项目（U01DK127384），Data Coordinating Center for the Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC)，2020-2021（参与）

1. Jiang, R.,Zhan, X.*,  Wang, T.*, 2023. A flexible zero-inflated poisson-gamma model with application to microbiome sequence count data. Journal of the American Statistical Association, 118, 792-804.

2. Rios, N., Xue, L., Zhan, X.*, 2024. A latent variable mixture model for composition-on-composition regression with application to chemical recycling. Annals of Applied Statistics, 18, 3253-3273.

3. Srinivasan, A., Xue, L.*, Zhan, X.*, 2021. Compositional knockoff filter for high-dimensional regression analysis of microbiome data. Biometrics, 77, 984-995.

4. Zhan, X.*, Plantinga, A., Zhao, N.,  Wu, M. C.*, 2017. A fast small-sample kernel independence test for microbiome community-level association analysis. Biometrics, 73, 1453-1463.

5. Zhan, X., Tong, X., Zhao, N., Maity, A., Wu, M. C.*, Chen, J.*, 2017. A small‐sample multivariate kernel machine test for microbiome association studies. Genetic Epidemiology, 41, 210-220.