个人简介
教育背景
2015.09--2020.07,中国科学院数学与系统科学研究院,统计学博士,导师:于丹研究员、李启寨研究员
2011.09--2015.07,北京大学,理学学士
工作经历
2022.07至今,北京理工大学数学与统计学院,预聘助理教授
2020.07--2022.06,北京理工大学数学与统计学院,博士后,导师:田玉斌教授
研究领域
数理统计,生物统计,高维数据分析,关联分析,微生物组学数据分析
近期论文
查看导师最新文章
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Wang J., Li N., Meng Z., Li Q. (2023) Change point detection for high dimensional data via kernel measure with application to human aging brain data. Statistics in Medicine, accepted.
Jiang Z., Guo H., Wang J*. (2023) Feature screening for multiple responses. Journal of Multivariate Analysis, 105223.
Wang J., Long M., Li Q. (2023) A maximum kernel-based association test to detect the pleiotropic genetic effects on multiple phenotypes. Bioinformatics, 39(5), btad291.
Jiang, Z., Guo, H.,Wang, J*. (2023). Screening properties of trend tests in genetic association studies. Scientific Reports, 13(1), 9139.
Wang J., Jiang Z., Guo H., Li Z.. (2022) Divided-and-combined omnibus test for genetic association analysis with high-dimensional data. Statistical Methods in Medical Research, 32 (3): 626-637.
Wang J., Zhao Y., Tang L., Mueller C., Li Q. (2022) A resample-replace Lasso procedure for combining high-dimensional markers with limit of detection. Journal of Applied Statistics, 49(16), 4278-4293.
Li Z., Wang B., Luo W., Xu Y., Wang J., Xue Z., Niu Y., Cheng Z., Ge S., Zhang W., Zhang J., Li Q., Chong K. (2022) Natural variation of codon repeats in COLD11 endows rice with chilling resilience. Science Advances 9, eabq5506.
Wang J., Jiang Z., Liu H., Meng Z.. (2021) Association testing for high-dimensional multiple response regression. Journal of Systems Science & Complexity, accepted.
Wang Z., Wang J., Li Q. (2021) Quadratic and Cauchy statistics. Journal of Applied Statistics and Management, 40(3): 405-416.
Wang J., Li J., Xiong W., Li Q. (2020) Group analysis of distance matrices. Genetic Epidemiology, 44: 620-628.
Xue Y., Ding J., Wang J., Zhang S., Pan D. (2020) Two-phase SSU and SKAT in genetic association studies. Journal of Genetics, 99(1): 1-10.
Wang J., Ding J., Huang S., Li Q., Pan D. (2019) A powerful method to test associations between ordinal traits and genotypes. G3-Genes, Genomes, Genetics, 9(8): 2573-2579.
Xue Y., Wang J., Ding J., Zhang S., Li Q. (2019) A powerful test for ordinal trait genetic association analysis. Statistical Applications in Genetics and Molecular Biology, 18(2): 20170066.