Yichi Zhang

Research

My research focuses on developing novel statistical methods to address various problems in biostatistics via the use of appropriate machine learning techniques. Examples include list-based rules for individualized treatment selection and shrinkage methods for electronic health record (EHR) phenotyping. Most of the proposed methods are accompanied with easy-to-use R packages.

Education

2016 PhD North Carolina State University Statistics
2013 MS North Carolina State University Statistics
2011 BS Peking University Probability and Statistics

Previous Positions

2016-2018 Postdoctoral fellow Department of Biostatistics, Harvard University Boston, MA

Selected Publications

  • Cai, Zhang, Ho, et al (2018). Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy: A Phenome-Wide Association Study. JAMA Cardiology
  • Zhang, Laber, Davidian, and Tsiatis (2017). Estimation of optimal treatment regimes using lists. JASA
  • Zhang, Laber, Tsiatis, and Davidian (2015). Using decision lists to construct interpretable and parsimonious treatment regimes. Biometrics