Faculty Profile
Yi Li, PhD
- M. Anthony Schork Collegiate Professor of Biostatistics
- Professor, Global Public Health
Li has contributed to a wide range of statistical areas, including survival analysis,
data science, high-dimensional inference, machine learning, deep learning, spatial
data analysis, random-effects models, clinical trial design, and infectious disease
modeling.
He is interested in cancer genetics/genomics, radiomics, racial disparity analysis,
chronic disease research and opioid overuse research. He has published more than 280
papers in major statistical journals, such as JASA, Biometrika, JRSSB, and Biometrics,
as well as premier subject matter journals, such as PNAS, JAMA and JCO. His methodologic
research is funded by various NIH statistical grants starting from year 2003. Li is
actively involved in collaborative research in cutting-edge clinical and observational
studies with researchers from the University of Michigan and Harvard University.
- Postdoctor, Biostatistics, Harvard, 1999-2000
- PhD, Biostatistics, University of Michigan, 1999
- MS, Biostatistics, University of Michigan, 1996
Research Interests:
Survival analysis, data science, high-dimensional inference, machine learning, deep
learning, spatial data analysis, random-effects models, clinical trial design, and
infectious disease modeling, with applications in cancer genetics/genomics, radiomics,
chronic disease research and opioid overuse research.
- New Statistical Methods for Modelling Cancer Outcomes
- Causal Machine Learning in Cancer Survival by Integrating Multiple High-dimensional Observational Studies
Meng, X., Zhang, E. and Li, Y. (2025) Statistical inference on high-dimensional covariate-dependent
Gaussian graphical regressions. Biometrics, in press.
Wen, S., Li, Y., Kong, D. and Lin, H (2025) Prediction of cognitive function via brain
region volumes with applications to Alzheimer’s disease based on space-factor-guided
functional principal component analysis. Journal of the American Statistical Association,
120(551), 1373–1385.
Zhang, J. and Li, Y. (2025) Multi-task learning for Gaussian graphical regressions
with high dimensional covariates. Journal of Computational and Graphical Statistics,
34(3), 961–970.
Guha, S. and Li, Y. (2024) Causal meta-analysis by integrating multiple observational
studies with multivariate outcomes. Biometrics, 80(3), ujae070.
Sun, Y., Salerno, S., Pan, Z., Yang, E., Sujimongkol, C., Song, J., Wang, X., Han,
P., Zeng, D., Kang, J., Christiani, D., and Li, Y. (2024) Assessing the prognostic
utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges
and lessons learned. Harvard Data Science Review, 6.1.
Zhao, G., Ma, Y., Lin, H. and Li, Y. (2024) Evaluation of transplant benefits with
the U.S. Scientific Registry of Transplant Recipients by semiparametric regression
of mean residual life. Annals of Applied Statistics, 18(3), 2403-2423.
Sun, Y., Kang, J., Haridas, C., Mayne, N., Potter, A., Yang, C., Christiani, D. and
Li, Y. (2024) Penalized deep partially linear Cox models with application to CT scans
of lung cancer patients. Biometrics, 80(1), ujad024.
Salerno, S. and Li, Y. (2023) High-dimensional survival analysis: methods and applications.
Annual Review of Statistics and Its Application, 10, 25-49.
Sun, Y., Kang, J., Brummett, C. and Li, Y. (2023) Individualized risk assessment of
preoperative opioid use by interpretable neural network regression. Annals of Applied
Statistics, 17, 434-453.
Zhang, E. and Li, Y. (2023) High dimensional Gaussian graphical regression models
with covariates. Journal of the American Statistical Association, 118(543), 2088-2100.
Salerno, S., Messana, J., Gremel, G., Dahlerus, C., Hirth, R., Han, P., Segal, J.,
Xu, T., Shaffer, D., Jiao, A., Simon, J., Tong, L., Wisniewski, K., Nahra, T., Padilla,
R., Sleeman, K., Shearon, T., Callard, S., Yaldo, A., Borowicz, L., Agbenyikey, W.,
Horton, G., Roach, J. and Li, Y. (2021) Characteristics and mortality outcomes of
COVID-infected dialysis patients enrolled in Medicare. JAMA Network Open, 4(11), e2135379.
doi:10.1001/jamanetworkopen.2021.35379
Email: yili@umich.edu
Address:
M2102 SPH II
1415 Washington Heights
Ann Arbor, MI 48109
For media inquiries: sph.media@umich.edu
Areas of Expertise: Biostatistics, Cancer, Chronic Disease, Clinical Trials, COVID-19, Firearm Injury Prevention, Genetics, Genomics, Global Public Health, Health Care, Opioids, Precision Health, Substance Use