Dr. Chaeryon Kang

Biography

I am an Associate professor (biostatistics faculty) in the department of Psychiatry at the University of Pittsburgh. Prior to September 2024, I was an Assistant professor in the department of Biostatistics at the University of Pittsburgh. I received my Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in 2011, under the guidance of Dr. Michael R. Kosorok . From 2011-2014, I was a post-doctoral researcher at the Fred Hutchison Cancer Center in Seattle, mentored by Dr. Hollay Janes and Dr. Ying Huang . As a statistician, I have extensive experience in statistical analysis and modeling. Throughout my career, I have worked on various issues related to clinical trials and observational studies, such as statistical methods in biomarker evaluation for treatment selection and risk prediction, precision (personalized) medicine and predictive modeling using statistical and machine learning techniques, statistical approach in HIV vaccine efficacy trials, survival data analysis, and meta-analysis. I also have significant experience in collaborative research, including studies on cognitive psychology, psychiatric and neurodevelopmental disorders, brain and aging, breast cancer, women's health issues, and Medicare/Medicaid electronic health records. My current research focuses on developing and applying statistical methods and machine learning techniques for evaluating heterogeneity in treatment effects and latent subgroup analysis in clinical trials, observational studies, and mobile health studies.

Academic Position

• Sep. 2024 - Present
  Associate Professor, Department of Psychiatry (Primary), School of Medicine, University of Pittsburgh
• Nov. 2025 - Present
  Assistant Professor, Department of Biostatistics and Health Data Science (Secondary)

  School of Public Health, University of Pittsburgh
• 2014 - Aug. 2024
  Assistant Professor, Department of Biostatistics, School of Public Health, University of Pittsburgh

Education/ Training

• Ph.D.
  Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
• Postdoc
  Research Fellow, Vaccines and Infectious Diseases Division / Public Health Sciences Division, Fred Hutchinson Cancer Research Center , Seattle, WA

Research Interests

• Precision (personalized) medicine, Individualized treatment rule, Empirical processes, Statistical/Machine learning, Latent subgroup analysis, Functional data analysis, Differential equation modeling
• Mobile health, Ecological Momentary Assessment (EMA)/ Actigraphy data analysis, Integrate multiple modalities of data, Brain and aging, Mental health, Statistical methods in HIV vaccine efficacy

Selected Publications

• Kang, C.⁺, Cho, H., Song, R., Banerjee, M., Laber, E. B., and Kosorok, M. R.   Inference for change-plane regression. Bernoulli (2025), Vol. 31, No. 3, 2459-2483. doi.org/10.3150/24-BEJ1812   arxiv.org/abs/2206.06140 (Combined the main and supplementary materials)
• Gorczyca, M. T. and Kang, C.⁺.   On quantifying heterogeneous treatment effects with regression-based individualized treatment rules: Loss function families and bounds on estimation error. Stat (2024), 13(2), e680. doi.org/10.1002/sta4.680 (Top-viewed article in 2025 among works published in Stat in 2024)
• Bo, N.^*, Wei, Y.^*, Zeng, L., Kang, C., and Ding, Y.   A Meta-Learner Framework to Estimate Individualized Treatment Effects for Survival Outcomes. Journal of Data Science (2024), 1-19. doi.org/10.6339/24-JDS1119 (an earlier version won the 2022 JSM Lifetime Data Analysis section student paper award)
• Kang, C.⁺ and Huang, Y.   Identification of immune response combinations associated with heterogeneous infection risk in the immune correlate analysis of HIV vaccine studies. Annals of Applied Statistics (2023), 17(2): 1199-1219. doi.org/10.1214/22-aoas1665
• Kang, C.⁺, Zhang, D., Schuster, J., Kogan, J., Nikolajski, C., and Reynolds III., C.F. (2023). Bias-corrected and doubly robust inference for the three-level longitudinal cluster-randomized trials with missing continuous outcomes and small number of clusters: simulation study and application to a study for adults with serious mental illnesses. Contemporary Clinical Trials Communications, 35, 101194. doi.org/10.1016/j.conctc.2023.101194
• Kang, C.⁺, Janes, H., Tajik, P., Groen, H., Mol, B.W.J., Koopmans, C.M., Broekhuijsen, K., Zwertbroek, E., van Pampus, M. G., and Franssen, M.T.M.   Evaluation of biomarkers for treatment selection using individual participant data from multiple clinical trials. Statistics in Medicine (2018), 37(9):1439-1453. doi.org/10.1002/sim.7608
• Kang, C., Huang, Y., and Miller, C. J. (2015). A discrete time survival model with random effects for designing and analyzing repeated low-dose challenge experiments. Biostatistics, 16(2), 295-310. doi.org/10.1093/biostatistics/kxu040
• Kang, C.⁺, Janes, H., and Huang, Y.   Combining biomarkers to optimize patient treatment recommendation. Biometrics (2014), 70(3): 695-707. (with discussion). doi.org/10.1111/biom.12191 (This paper was discussed by four leading statistical research groups in precision medicine and was ranked the top-cited paper in Biometrics in 2016)

Complete List of Published Work in My Bibliography: NCBI My Bibliography

Courses Taught