Xingyu (Mark) Zhang, Ph.D.

Xingyu (Mark) Zhang

Applied Biostatistics Laboratory
Research Assistant Professor
Department of Systems, Populations and Leadership
Room 1177

University of Michigan School of Nursing
400 North Ingalls Building
Ann Arbor, MI 48109-5482

Telephone: (734) 763-0930


  • Health outcomes with an emphasis on study design and statistical analysis
  • Electronic health record data mining
  • Predictive modeling in healthcare
  • Statistical medical imaging diagnostic modeling
  • Public health surveillance modeling

Xingyu Zhang is a Research Assistant Professor at the School of Nursing’s Applied Biostatistics Laboratory (ABL).  He received his Ph.D. in Biomedical Science concentrated on biostatistics from the University of Auckland in 2016.  Prior to joining the ABL, he was a postdoctoral research fellow in epidemiology and biostatistics at Emory University, and also a visiting research scholar in medical informatics at Georgia Institute of Technology. Dr. Zhang’s research focuses on healthcare outcomes with an emphasis on study design and statistical analysis. The methods he applied include multi-level analysis, time series analysis, infection early warning modeling, medical imaging analysis, feature extraction, pattern classification, neural networks, support vector machine, natural language processing, deep learning, survival analysis, meta-analysis, etc.  

Notable Awards / Honors

  • Postdoc Research Fellow, Emory University School of Medicine, 2016-2018
  • Visting Scholar, Georgia Institute of Technology College of Computing, 2017-2018


  • PhD, University of Auckland, Auckland, New Zealand, IN 2016
  • MS, Sichuan University, Chengdu,China, IN 2013
  • BS, Binzhou Medical University, Yantai, China, IN 2010

Publication Highlights

  • Zhang, X., Melanson, T. A., Plantinga, L. C., Basu, M., Pastan, S. O., Mohan, S., . . . Patzer, R. E. (2018). Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system. American Journal of Transplantation.

  • Zhang, X., & Liu, Y.-C. (2018). The resurgence of scarlet fever in China. The Lancet Infectious Diseases.

  • Gander, J. C., Zhang, X., Plantinga, L., Paul, S., Basu, M., Pastan, S. O., ... & Patzer, R. E. (2018). Racial Disparities in Preemptive Referral for Kidney Transplantation in Georgia. Clinical transplantation, e13380.

  • Zhang, X., Kim, J., Patzer, R. E., Pitts, S. R., Patzer, A., & Schrager, J. D. (2017). Prediction of emergency department hospital admission based on natural language processing and neural networks. Methods of Information in Medicine, 56(05), 377-389.

  • Zhang, X., Medrano-Gracia, P., Ambale-Venkatesh, B., Bluemke, D. A., Cowan, B. R., Finn, J. P., . . . Young, A. A. (2017). Orthogonal decomposition of left ventricular remodeling in myocardial infarction. GigaScience, 6(3), 1-15.

  •  Zhang, T., Yin, F., Zhou, T., Zhang, X., & Li, X.-S. (2016). Multivariate time series analysis on the dynamic relationship between Class B notifiable diseases and gross domestic product (GDP) in China. Sci Rep, 6(1), 29.

  • Zhang, X., Hou, F., Li, X., Zhou, L., Liu, Y., & Zhang, T. (2016). Study of surveillance data for class B notifiable disease in China from 2005 to 2014. International Journal of Infectious Diseases, 48, 7-13.

  • Zhang, X., Hou, F., Qiao, Z., Li, X., Zhou, L., Liu, Y., & Zhang, T. (2016). Temporal and long-term trend analysis of class C notifiable diseases in China from 2009 to 2014. BMJ open, 6(10), e011038.

  • Zhang, X., Zhang, T., Pei, J., Liu, Y., Li, X., & Medrano-Gracia, P. (2016). Time series modelling of syphilis incidence in China from 2005 to 2012. PLoS One, 11(2), e0149401.

  • Zhang, X., Ambale-Venkatesh, B., Bluemke, D. A., Cowan, B. R., Finn, J. P., Kadish, A. H., . . . Suinesiaputra, A. (2015). Information maximizing component analysis of left ventricular remodeling due to myocardial infarction. Journal of translational medicine, 13(1), 343.

  • Zhang, X., Zhang, T., Young, A. A., & Li, X. (2014). Applications and comparisons of four time series models in epidemiological surveillance data. PLoS One, 9(2), e88075.

  • Zhang, J., Yin, F., Zhang, T., Yang, C., Zhang, X., Feng, Z., & Li, X. (2014). Spatial analysis on human brucellosis incidence in mainland China: 2004–2010. BMJ open, 4(4), e004470.

  • Zhang, T., Zhang, X., Ma, Y., Zhou, X. A., Liu, Y., Feng, Z., & Li, X. (2014). Bayesian spatio-temporal random coefficient time series (BaST-RCTS) model of infectious disease. Mathematical biosciences, 258, 93-100.

  • Zhang, X., Cowan, B. R., Bluemke, D. A., Finn, J. P., Fonseca, C. G., Kadish, A. H., . . . Young, A. A. (2014). Atlas-based quantification of cardiac remodeling due to myocardial infarction. PLoS One, 9(10), e110243.

  • Zhang, X., Liu, Y., Yang, M., Zhang, T., Young, A. A., & Li, X. (2013). Comparative study of four time series methods in forecasting typhoid fever incidence in China. PLoS One, 8(5), e63116.