王学钦
讲席教授
邮箱：wangxq20@ustc.edu.cn
网页：https://bs.ustc.edu.cn/chinese/profile-650.html
电话：+86-551-63606292
主要研究方向：
人工智能的统计学理论、方法与计算
最优子集选择问题
度量空间的统计推断理论、方法与计算
基于机理和数据融合的统计建模和推断
统计机器学习
精准医疗
医疗政策
风险管理和政策评估
代表性荣誉：
国际统计学会推选会员 (ISI Elected Member）（2024）
高等学校科学研究优秀成果奖自然科学二等奖（排名第一）(2023)
国家级领军人才（2021）
“广东特支计划”百千万工程领军人才（2016）
优秀青年科学基金获得者（2013）
教育部新世纪优秀人才支持计划（2012）
期刊任职:
Journal of the American Statistical Association (Associate Editor)
Statistics and Its Interface (Associate Editor)
Statistical Theory and Related Fields (Associate Editor)
应用概率统计（编委）
统计学报（编委）
代表性社会服务：
中国现场统计研究会 副理事长
教育部高等学校统计学类专业教学指导委员会 委员
中国现场统计研究会教育统计与管理分会 理事长
中国工业统计教学研究会 监事会副会长&常务理事
中国现场统计研究会数据科学与人工智能分会 副理事长
全国工业统计学教学研究会数字经济与区块链技术协会 副理事长
中国统计教育学会 常务理事
高等教育出版社《Lecture Notes: Data Science, Statistics and Probability》系列丛书 副主编
主持或参与的科研项目
2022-2027 海量多源数据的融合分析算法，国家重点研发计划/科技部，课题主持
2023-2027 基于高斯随机场的复杂结构数据分析，重点项目/国家自然科学基金委，主持
2021-2025 最优子集选择及其应用，面上项目/国家自然科学基金，主持
2018-2022 条件独立性及其应用。面上项目/国家自然科学基金，主持
代表性期刊论文：
1. Tan, JB, Zhang, GY, Wang, XQ, Huang, H, and Yao, F (2024+), Green’s matching: an efficient approach to parameter estimation in complex dynamic systems, Journal of the Royal Statistical Society Series B: Statistical Methodology, online.
2. Zhang, JN, Wang, JH, and Wang, XQ (2024+), Consistent community detection in inter-layer dependent multi-layer networks, Journal of the American Statistical Association, online.
3. Wang, XQ, Zhu J, and Pan, WL (2024+), Nonparametric statistical inference via metric distribution function in metric spaces. Journal of the American Statistical Association, online.
4. Jiang, YL, Wang, XQ, Wen, CH, Jiang, YK, and Zhang HP (2024), Nonparametric two-sample tests of high dimensional mean vectors via random integration. Journal of the American Statistical Association, 119(545): 701-714.
5. Wang, ZZ, Zhu, JX, Wang, XQ, Zhu, J, Pen, HY, Chen, P, Wang, AR, and Zhang, XK(2024), skscope: Fast Sparsity-Constrained Optimization in Python. Journal of Machine Learning Research, 25, 1-9.
6. Wen, CH, Wang, XQ, and Zhang, AJ (2023), ?0 Trend Filtering. INFORMS Journal on Computing, 35(6): 1491-1510.
7. Du, JH, Guo, YF, and Wang, XQ (2023), High-dimensional portfolio selection with cardinality constraints. Journal of the American Statistical Association, 118(542): 779-791.
8. Zhu, J, Wang, XQ, Hu, LY, Huang, JH, Jiang, KK, Zhang, YH, Lin, SY, and Zhu, JX (2022), abess: A fast best-subset selection library in Python and R. Journal of Machine Learning Research, 23, 1-7.
9. Zhang, YH, Zhu, JX, Zhu, J, and Wang, XQ (2022), A splicing approach to best subset of groups selection. INFORMS Journal on Computing 35 (1): 104-119.
10. Tian, T, Tan, JB, Luo, WX, Jiang, YK, Chen, MQ, Yang, SP, Wen, CH, Pan, WL, and Wang, XQ (2021). The Effects of Stringent and Mild Interventions for Coronavirus Pandemic. Journal of the American Statistical Association, 116(534), 481-491.
11. Zhu, J, Pan, WL, Zheng, W and Wang, XQ (2021). Ball: An R package for detecting distribution differences and associations in metric spaces. Journal of Statistical Software 97 (6), 1-31.
12. Zhu, JX, Wen, CH, Zhu, J, Zhang, HP and Wang, XQ (2020). A polynomial algorithm for best-subset selection problem. Proceedings of the National Academy of Sciences 117(52), 33117-33123.
13. Li, TB, Li, YW, Hu, YX, Wang, YY, Lam, CM, Ni, W, Wang, XQ, Yi, L (2020). Heterogeneity of Visual Preferences for Biological and Repetitive Movements in Children with Autism Spectrum Disorder. Autism Research 14 (1), 102-111.
14. Wen, CH, Zhang, AJ, Quan, SJ and Wang, XQ (2020). BeSS: An R Package for Best Subset Selection in Linear, Logistic, and CoxPH Models. Journal of Statistical Software 94(1), 1-24.
15. Liu, Y, Bible, PL, Zou, B, Liang, QX, Dong, C, Wen, XF, Li, Y, Ge, XF, Li, XF, Deng, XL, Ma, R, Guo, SX, Liang, JR, Chen, TT, Pan, WL, Liu, LX, Chen, W, Wang, XQ and Wei, L (2020). CSMD: A computational subtraction-based microbiome discovery pipeline for species-level characterization of clinical metagenomic samples. Bioinformatics 36(5), 1577-1583.
16. Pan, WL, Wang, XQ, Zhang, HP, Zhu, HT and Zhu, J (2020). Ball Covariance: A Generic Measure of Dependence in Banach Space. Journal of the American Statistical Association 115(529), 307-317.
17. Pan, WL, Wang, XQ, Xiao, WN and Zhu, HT (2018). A Generic Sure Independence Screening Procedure. Journal of the American Statistical Association 114 (526), 928-937.
18. Pan, WL, Tian, Y, Wang, XQ and Zhang, HP (2018). Ball Divergence: Nonparametric Two Sample Test. Annals of Statistics 46(3), 1109-1137.
19. Pan, WL, Wang, XQ, Wen, CH, Styner M and Zhu HT (2017). Conditional local distance correlation for manifold-valued data. Information Processing in Medical Imaging, 41-52.
20. Wang, XQ, Pan, WL, Hu, WH, Tian Y and Zhang, HP (2015). Conditional distance correlation. Journal of the American Statistical Association 110(512), 1726-1734.
21. Wang, XQ, Jiang, YL, Huang, M and Zhang, HP (2013). Robust Variable Selection with Exponential Squared Loss. Journal of the American Statistical Association 108(502), 632-643.
22. Xiong YY, Chen, XS, Chen, ZD, Wang XZ, Shi, SH, Wang, XQ, Zhang, JZ and He XL (2010). RNA sequencing shows no dosage compensation of the active X chromosome. Nature Genetics 42(12), 1043-1047.
23. Zhang, HP, Liu, CT and Wang, XQ (2010). An Association Test for Multiple Traits Based on the Generalized Kendall’s Tau. Journal of the American Statistical Association 105(490), 473-481.
软件：
1. cdcsis: Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference. https://cran.r-project.org/web/packages/cdcsis/
2. Ball: Statistical Inference and Sure Independence Screening via Ball Statistics. https://cran.r-project.org/web/packages/Ball/ and https://pypi.org/project/Ball/
3. Fit GLM with LEP-Based Penalized Maximum Likelihood. https://cran.r-project.org/web/packages/glmlep/
4. BeSS: Best Subset Selection in Linear, Logistic and CoxPH Models. https://cran.r-project.org/web/packages/BeSS/
5. AMIAS: Alternating Minimization Induced Active Set Algorithms. https://cran.r-project.org/web/packages/AMIAS/
6. FastSF: Fast Structural Filtering. https://cran.r-project.org/web/packages/FastSF/
7. fastmit: Fast Mutual Information Based Independence Test. https://cran.r-project.org/web/packages/fastmit
8. eimpute: Efficiently Impute Large Scale Incomplete Matrix. https://cran.r-project.org/web/packages/eimpute/
9. gif: Graphical Independence Filtering. https://cran.rstudio.com/web/packages/gif/
10.BeSS: A Python Package for Best Subset Selection. https://pypi.org/project/bess/
11.Ball: A Python Package for Detecting Distribution Differences and Associations in Metric Spaces. https://pypi.org/project/Ball/
招生要求：
至少具备很强的以下三个能力之一：A）数学能力；B）计算能力；C）沟通（写作）能力。
科学学位硕士生提交以下材料：
(1)提交主要课程成绩单、个人简历、获奖证书与论文
(2)写明博士意愿和明确读博原因
(3)明确指出是从事理论研究还是应用研究
(4)回答招生总体要求中所提及的事宜。
报考联系：（1）欢迎优秀的学生Email联系我；（2）请附上相关申请材料。
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