邮箱：xlwang@btbu.edu.cn

地址：北京市房山区北京工商大学良乡主校区东区数学与统计学院

个人简介

教授，博士生导师，自然科学处副处长，统计科学中心主任。现任中国现场统计研究会因果推断分会秘书长、北京生物统计BBA常务理事、中国统计教育高等教育分会理事，中国现场统计研究会高维数据分会，计算统计分会理事，人工智能+食品安全专家委员会委员等。

研究兴趣

统计因果推断、大数据分析、机器学习、贝叶斯统计及在食品安全、流行病学等应用统计研究。

主讲课程

主讲本科生课程《数据科学的统计基础》、双语《数理统计》，研究生课程《统计因果推断》、《复杂数据分析统计建模》等。

学习经历

北京大学，数学科学学院，概率论与数理统计，理学博士

北京师范大学，统计学院，概率论与数理统计，理学硕士

曲阜师范大学，数学科学学院，数学与应用数学，理学学士

工作经历

2020年至今 ，北京工商大学，数学与统计学院 教授

2010-2011年， 华盛顿大学，生物统计系 访问学者

2006-2020年， 北京邮电大学，理学院 讲师，副教授

主要获奖荣誉

课题论文获得第九届全国统计科学研究优秀成果一等奖

北京市高等教育教学成果奖一等奖”排名第五

研究生教育教学成果奖 北工商 二等奖

指导的研究生多人获得“国家奖学金”和“北京市优秀毕业生”

主要科研项目

1.因果推断中处理依赖潜在结果的因果效应评价与归因研究，北京市教委和北京市自然基金联合重点项目，2023-2026，主持

2.特色食品全链条质量安全特征风险评估和预测预警模型建立，国家重点研发计划-子课题，2020-2023，已结题，主持

3.食品安全缺失数据填补与决策事件关联统计推断，国家重点研发计划委托项目，已结题，主持

4.基于网络搜索数据的经济形势的统计建模与分析预测，全国统计科学研究项目 已结题，主持

5.统计因果推断及缺失数据统计分析，国家自然科学基金青年基金，已结题，主持

6.统计因果推断及混杂因素，国家自然科学基金天元基金，已结题，主持

主要学术成果

[1] Yang Q, Wang X L*, Cao X B, Liu S, Xie F, Li Y. Multi-classification of national fitness test grades based on statistical analysis and machine learning，PLOS ONE ,2024, https://doi.org/10.1371/journal.pone.0295674.

[2]  Shi M, Chu Q, Wang X L*. Probabilistic human health risk assessment of trace elements exposure in crayfish. Journal of Food Composition and Analysis, 2023, 121: 105360.

[3]  Chu Q, Li Y, Wang X L*. Bayesian inference of heavy metals exposure in crayfish for assessing human non–carcinogenic health risk. Food and Chemical Toxicology, 2023, 173: 113595.

[4] Wang X L. Theory and Application of Causal Inference and Bayesian Statistics. Beijing: Science Press, 2022.

[5] Zhang X, Wang X L*, Cao X B , Xiao, G X. Heavy element contents of vegetables and health-risk assessment in China. Science of The Total Environment, 2022, 828:154552.

[6] Li Y, Wang X L*, Du H, et al. Heavy metal accumulation and health risk assessment of crayfish in the middle and lower reaches of Yangtze River during 2015–2017. Environmental Monitoring and Assessment, 2022, 194(1): 1-11.

[7]  Wang X L, Li Y, Jia J. Forecasting of COVID-2019 onset cases: a data-driven analysis in the early stage of delay. Environmental Science and Pollution Research, 2021, 28(16): 20240-20246.

[8]  Wang X L, Wu J P, Yu B J, Dong F, Ma D, Xiao G X, Zhang C, Heavy metals in aquatic products and the health risk assessment to population，Environmental Science and Pollution Research, 2020, 27: 22708–22719.

[9] Wang X L, Zhang Y F, Zhang H, Li Y, Wei X F, Radio Frequency Signal Identification Learning Based on LSTM，Circuits, Systems, and Signal Processing, 2020. 39: 5514–5528.

[10] Yu B J, Wang X L*, Dong F, Xiao G X, Ma D，Heavy metal concentrations in aquatic organisms (fishes, shrimp and crabs) and health risk assessment in China, Marine Pollution Bulletin, 2020. 159:111505.

[11] Wang X L, Zhang Y, Geng Z, Liu Y, Guo L X, Xiao G X. Spatial analysis of heavy metals in meat products in China during 2015-2017. Food Control. 2019, 104(1): 174-180.

[12] Wang X L, Zhang Y F, Zhang H X, Wei X F, Wang G Y. Identification and authentication for wireless transmission security based on RF-DNA fingerprint. EURASIP Journal on Wireless Communications and Networking. 2019, 230；1-12.

[13] Wang X L, Zhou M Q, Jia J Z, Geng Z, Xiao G X. A Bayesian approach to real-time monitoring and forecasting of Chinese foodborne diseases. International Journal of Environmental Research and Public Health. 2018, 15(8): 1740-1753.

[14] Wang X L. Binomial Proportion Estimation in Longitudinal Data with Non-ignorable Non-response, Acta Mathe. Appli. Sinica, 2013, 29 (3): 623-630.

[15] Wang X L, Chen H, Geng Z, Zhou X H. Using Auxiliary Data for Binomial Parameter Estimation with Nonignorable Nonresponse. Communications in Statistics-Theory and Methods, 2012, 41: 1–11.

[16] Wang X L, Geng Z, Chen H, Xie X C. Detecting multiple confounders. Journal of Statistical Planning and Inference, 2009, 139(3):1073-1081.

[17] Wang X L, Geng Z, Zhao Q, Qiao Q，Comparison between estimates of the potential proportion with and without standardization for a non-confounder. Statistica Sinica. 2007, 17(4): 1643-1656.  

[18] Geng Z, He Y B, Wang X L, Zhao Q. Bayesian method for learning graphical models with incompletely categorical data. Computational Statistics & Data Analysis. 2003, 44(1): 175-192.