Research

My research focuses on developing statistical methods for causal inference, infectious disease transmission, and individualized decision-making in biomedical and public health studies.

Current Research Themes

• Causal inference for infectious disease surveillance: developing counterfactual frameworks for prevalence estimation under nonrandom repeated testing, symptomatic testing, and contact tracing.
• High-dimensional and semiparametric pairwise survival analysis: developing high-dimensional and semiparametric methods for infectious disease transmission analysis within the pairwise survival analysis framework.
• Reinforcement learning for censored time-to-event outcomes: developing methods for individualized treatment decision-making when outcomes are censored or incompletely observed.

Education

Publications

Methodology

Accepted / Published

1. Lee, J., Yang, J., Rempala, G. A., Schnell, P. M. (2026). A Counterfactual Framework for Estimating Infectious Disease Prevalence under Repeated Testing with Symptomatic and Contact-Tracing Components . Annals of Applied Statistics, 20(3), 1961–1984.
2. Lee, J., Kim, J.-M. (2026). Counterfactual Survival Q-learning via Buckley–James Boosting with Applications to ACTG 175 and CALGB 8923 . Journal of the Royal Statistical Society: Series C (Applied Statistics), qlag013.
3. Lee, J., Kim, J.-M. (2026). Q-learning via Deep Learning-Based Buckley–James Method for Non-Linear Censored Data . Lifetime Data Analysis, 32, 27.
4. Lee, J., Kim, J.-M. (2026). Counterfactual Q-Learning via the Linear Buckley–James Method for Longitudinal Survival Data . Journal of the Royal Statistical Society Series A: Statistics in Society, 189(3), 1473–1489.
5. Lee, J., Choi, T., Choi, S. (2024). Censored Broken Adaptive Ridge Regression in High-Dimension . Computational Statistics, 39(6), 3457–3482.

Manuscripts under Review

1. Lee, J., Kim, J.-M. Copula-Based Decision Making for Censored Time-to-Event Outcomes. Under review.
2. Lee, J., Schnell, P. M., Rempala, G. A., Kenah, E. Variable Selection for Infectious Disease Transmission via Penalized Pairwise Accelerated Failure Time Models. Under review.
3. Lee, J., Rempala, G. A., Schnell, P. M. Kalman Filtering and Smoothing for Improving Precision in Horvitz–Thompson Estimation of Infectious Disease Prevalence. Under review.

Application

1. Jang, H., Cline, M., Lee, J., Reilly, M., Cho, H. (2026). Regional Differences in Young's Modulus of the Porcine Lens Capsule . Annals of Biomedical Engineering, 54, 2027–2039.

Presentations

1. Lee, J., Yang, J., Rempala, G. A., Schnell, P. M. (2026). A Counterfactual Framework for Estimating Infectious Disease Prevalence under Repeated Testing with Symptomatic and Contact-Tracing Components. RSS International Conference 2026, Bournemouth, UK.
2. Lee, J., Schnell, P. M., Rempala, G. A., Kenah, E. (2026). Variable Selection for Infectious Disease Transmission via Penalized Pairwise Accelerated Failure Time Models. The OSU Health and Environment Learning and Modeling (HELM).
3. Lee, J., Yang, J., Rempala, G. A., Schnell, P. M. (2025). A Counterfactual Framework for Estimating Infectious Disease Prevalence under Repeated Testing with Symptomatic and Contact-Tracing Components. The OSU Health and Environment Learning and Modeling (HELM).
4. Lee, J., Choi, T., Choi, S. (2021). Censored Broken Adaptive Ridge Regression in High-Dimension. Joint Statistical Meetings, Virtual.

Teaching

Professional Service

Reviewer: Statistics in Medicine (2), Journal of the Royal Statistical Society: Series A (2), Statistical Analysis and Data Mining (1).