Phone :86-10-62751837
Office :1498E


Ph. D, Kyushu University, 1989
M. S., Kyushu University, 1986
B. S., Shanghai Jiaotong University, 1982

Research Interests

Statistics, Biostatistics.  (MathSciNet)

1. Causal inference

2. Causal networks, structural learning

3. Confounding bias, collapsibility

4. Surrogate endpoint, evaluation of causal effects

Selected Publications

  • W. Miao, P. Ding,  and  ZGeng, (2016) Identifiability of normal and normal mixture models withnonignorable missing data. J. Am. Statist. Asso. 111, 1673-1683.
  • Z. C. Jiang, Ding, P. and  Z. Geng, (2016) Principal causal effect identification and surrogate endpoint evaluation by multiple trials. J Royal Statist. Soc. B. 78, 829-848.
  •  K. Deng, Z. Geng, and Liu, J. (2014) Association pattern discovery via theme dictionary models.J. Royal Statist Soc. B 76, 319-347.
  • P. Ding, Z. Geng, Yan, W. and Zhou, X. H. (2011) Identifiability and estimation of causal effects by principal stratification with outcomes truncated by death. J. Am. Statist. Asso., 106, 1578-1591.
  • C. Ju,  and Z. Geng,  (2010) Criteria for surrogate endpoints based on causal distributions. J. Royal Statist. Soc. B 72, 129-142.