工作及教育经历
2017年 --- 至今，中国科学技术大学，管理学院统计与金融系，教授
2015年 - 2017年，中国科学技术大学，管理学院统计与金融系，副研究员
2010年 - 2015年，美国南加州大学，应用数学专业，博士
2006年 - 2010年，中国科学技术大学，数学与应用数学专业，学士
研究兴趣
高维统计推断，变量选择，分类及相关的大数据问题
荣誉奖项
海外校友基金会青年教师事业奖, 2018
福布斯中国U30(30位30岁以下)精英榜, 2017
CAMS Prize for Excellence in Research, University of Southern California, 2015
IMS Travel Award, Institute of Mathematical Statistics, 2014
Merit Fellowship, USC Dana and David Dornsife College of Letters, Arts and Sciences, 2012-2013
主要学术论文（通讯作者*）
Zheng, Z.*, Lv, J. and Lin, W. (2021). Nonsparse learning with latent variables. Operations Research 69(1), 346-359.
Dong, R., Li, D. and Zheng, Z.* (2021). Parallel integrative learning for large-scale multi-response regression with incomplete outcomes. Computational Statistics & Data Analysis 160, 107243.
Zhou, J., Zheng, Z.*, Zhou, H. and Dong, R. (2021). Innovated scalable efficient inference for ultra-large graphical models. Statistics & Probability Letters 173, 109085.
Zheng, Z., Li, Y., Wu, J.* and Wang, Y. (2020). Sequential scaled sparse factor regression. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2020.1844212.
Zheng, Z., Zhang, J.*, Li, Y. and Wu, Y. (2020). Partitioned approach for high-dimensional confidence intervals with large split sizes. Statistica Sinica, DOI: 10.5705/ss.202018.0379.
Zheng, Z., Shi, H., Li, Y.* and Yuan, H. (2020). Uniform joint screening for ultra-high dimensional graphical models. Journal of Multivariate Analysis 179, 104645.
Wu, J., Zheng, Z.*, Li, Y. and Zhang, Y. (2020). Scalable interpretable learning for multi-response error-in-variables regression. Journal of Multivariate Analysis 179, 104644.
Zheng, Z., Li, L., Zhou, J.* and Kong, Y. (2020). Innovated scalable dynamic learning for time-varying graphical models. Statistics & Probability Letters 165, 108843.
Zheng, Z.*, Bahadori, M. T., Liu, Y. and Lv, J. (2019). Scalable interpretable multi-response regression via SEED. Journal of Machine Learning Research 20, 1-34.
Zheng, Z., Li, Y., Yu, C., Li, G.* (2018). Balanced estimation for high-dimensional measurement error models. Computational Statistics & Data Analysis 126, 78-91.
Kong, Y., Zheng, Z. and Lv, J. (2016). The constrained Dantzig selector with enhanced consistency. Journal of Machine Learning Research 17, 1-22.
Fan, Y., Kong, Y., Li, D. and Zheng, Z. (2015). Innovated interaction screening for high-dimensional nonlinear classification. The Annals of Statistics 43, .
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