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Biography

Dr. Jeong joined the Biometric Research Program (BRP) in the Division of Cancer Treatment and Diagnosis at the National Cancer Institute in 2023. Before joining the NCI, Dr. Jeong was a full professor at the Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh.

Dr. Jeong's main statistical research areas have been time-to-event analysis and clinical trials, both explanatory and pragmatic. His recent research interests include causal inference, deep learning, empirical processes, mixed models, and prediction modeling using machine learning methods.

Dr. Jeong's main responsibilities in BRP are translational research and biomarker studies, including biomarker protocol review and statistical advising and consulting, particularly with the Cancer Diagnosis Program and the Cancer Therapy Evaluation Program.

Dr. Jeong is a fellow of the American Statistical Association, an elected member of the International Statistical Institute, and an elected member of Omicron of the Delta Omega Society (Honorary Public Health Society).

Selected Publications

  1. Fisher, B, Jeong, J., Anderson, S. Bryant, J., Fisher, E., and Wolmark Norman. (2002). Twenty-five year findings from a randomized clinical trial comparing radical mastectomy with total mastectomy and with total mastectomy followed by radiation therapy. New England Journal of Medicine 8, 567-575.
  2. Pogue-Geile, K.L., Kim, C., Jeong, J. et al. (2013). Predicting degree of benefit from adjuvant trastuzumab in NSABP Trial B-31. Journal of the National Cancer Institute 105, 1782-1788.
  3. Jeong, J. (2014). Statistical Inference on Residual Life. New York: Springer.
  4. Balmert, L. and Jeong, J. (2016). Nonparametric inference on quantile lost lifespan. Biometrics 73, 252-259.
  5. Jia, Y. and Jeong, J. (2021). Deep learning for quantile regression: DeepQuantreg. Computational Statistics and Data Analysis. https://doi.org/10.1016/j.csda.2021.107323.

For the complete publications record, see Google Scholar full list of publications.

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