张政 职称：助理教授、博士生导师（统计与大数据研究院）
研究方向：因果推断，缺失数据，半参/非参数统计，随机分析
联系方式：givennamefamilyname@ruc.edu.cn


个人简历2011年于东南大学数学系获学士学位，2015年于香港中文大学统计系获博士学位，2016年加入中国人民大学统计与大数据研究院担任助理教授.


主要论文：


Causal Inference:
1. Chan K. C. G., Yam S. C. P., and Zhang Z. (2015). Globally Efficient Nonparametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting. Journal of the Royal Statistical Society: Series B . 78(3), 673-700. [Link]
2. Ai C., Huang L. and Zhang Z. (2018). A Simple and Efficient Estimation of Average Treatment Effect in the Presence of Unmeasured Confounders. (Revision). [Link]
3. Ai C., Huang L. and Zhang Z. (2019). A Mann-Whitney Test of Distributional Effects in A Multivalued Treatment. (Minor Revision in Journal of Statistical Planning and Inference ). [Link]
4. Ai. C., Linton O., Motegi K. and Zhang Z. (2019). A Unified Framework for Efficient Estimation of General Treatment Models. (Submitted).
5. Ai. C., Linton O., and Zhang Z. (2019). Estimation and Inference of Counterfactual Distribution and Quantile Functions in Continuous Treatment Models. (Major Revision).


Missing Data:
1. Ai C., Linton O. and Zhang Z. (2019). A Simple and Efficient Estimation Method for Models with Nonignorable Missing Data. Statistica Sinica . in press. [Link]
2. Hamori S., Motegi K. and Zhang Z. (2019). Calibration Estimation for Semiparametric Copula Models with Data Missing at Random. Journal of Multivariate Analysis . 173, 85-109. [Link]
3. Hamori S., Motegi K. and Zhang Z.(2019). Copula-based Regression Models with Responses Missing at Random: A Unified Approach. (Major Revision). [Link]
Semi/Nonparametric Statistics:
1. Ai. C., Sun L., Zhang Z. and Zhu L. (2019). Testing Independence and Conditional Independence via Mutual Information. (Submitted).


Stochastic Analysis:
1. Bensoussan A., Yam S. C. P., and Zhang Z. (2015). Well-posedness of Mean-field Type Forward-backward Stochastic Differential Equations. Stochastic Processes and their Applications . 125(9), 3327-3354. [Link]
2. Wright J. A., Yam S. C. P., and Zhang Z. (2017). Enlargement of Filtration on Poisson Space: A Malliavin Calculus Approach. Stochastics . 90(5), 682-700. <span font-size:13.6px;white-space:normal;"="""" style=""line-height:" 28px;">[Link]
3. Privault N., Yam S. C. P., and Zhang Z. (2019). Poisson Discretizations of Wiener Functionals and Malliavin Operators with Wasserstein Estimates. Stochastic Processes and their Applications . 129(9), 3376-3405. [Link]