Faculty Profile

Kevin He

Kevin He, PhD

  • Associate Professor, Biostatistics

Kevin He is a core faculty member of the Kidney Epidemiology and Cost Center (KECC) at the University of Michigan. His primary research interests include survival analysis, healthcare provider profiling, risk prediction, data integration, machine learning, statistical optimization, causal inference and statistical genetics with application in organ transplantation, kidney dialysis, psoriasis, cancer and stroke. These works are motivated by large and complex datasets such as national disease registries, claims data, high-throughput genomics, epigenomics and transcriptomics.

  • PhD, Biostatistics, University of Michigan, 2012
  • MS, Biostatistics, University of Michigan, 2008
  • BS, Statistics, Queen's University, 2006
  • MS, Epidemiology, Queen's University, 2004
  • BM, Clinical Medicine, Dalian Medical University, 2002

Research Interests:
Survival analysis, healthcare provider profiling, risk prediction, data integration, machine learning, statistical optimization, causal inference and statistical genetics, organ transplantation, kidney dialysis, psoriasis, cancer and stroke

Research Projects:
He currently holds an R01 (PI) for improving statistical methods for profiling healthcare providers.

Since 2019, He has served as the Statistical PI for the Data Analysis for the Quality, Safety and Oversight of the ESRD, a contract by the Centers for Medicare and Medicaid Services (CMS) to lead the national effort monitoring dialysis facilities, transplant centers, organ procurement organizations and ESRD Networks.

Through a number of collaborations, He developed several data integration and transfer learning models (with application in post-transplant outcomes, kidney allocation decision, polygenic risk scores and polygenic hazard scores) to robustly integrate published prediction models and newly collected data to improve prediction performance, accounting for challenges including heterogeneity, data sharing, and privacy constraints.

He, K., Kang, J., Zhu, J. and Li, Y. (2021). Stratified Cox models with time-varying effects for national kidney transplant patients: a new block-wise steepest ascent method. Biometrics, In Press.

He, K., Dahlerus, C., Xia, L., Li, Y.M. and Kalbfleisch, J.D. (2020). The profiling inter-unit reliability. Biometrics, 76(2), 654-663.

He, K., Kang, J., Hong, H.G., Zhu, J., Li, Y.M., Lin, H.Z., Xu, H. and Li, Y. (2019). Covariance-insured screening. Computational Statistics and Data Analysis, 132,100-114. He, K., Zhou, X., Jiang, H., Wen, X.Q. and Li, Y. (2018).

He, K., Yang, Y., Li, Y.M., Zhu, J. and Li, Y. (2017). Modeling time-varying effects with large-scale survival data: an efficient quasi-Newton approach. Journal of Computational and Graphical Statistics, 26(3), 635-645.

He, K. and Schaubel, D.E. (2015). Standardized mortality ratio for evaluating center-specific mortality: assessment and alternative. Statistics in Biosciences, 7,296-321.

He, K., Kalbfleisch, J.D., Li, Y. and Li, Y.J. (2013). Evaluating hospital readmission rates in dialysis facilities; adjusting for hospital effects. Lifetime Data Analysis, 19(4), 490-512.

Suite 3645, Room 3655 SPH I
1415 Washington Heights
Ann Arbor, MI 48109

Email: kevinhe@umich.edu
Office: 734-764-2279

For media inquiries: sph.media@umich.edu