Research

Kim, R. C., Santacatterina, M., Zabih, R., Mukherjee, R., & Diaz, I. (2026). Statistical Inference for Continuous Action Bandits. arXiv

Kim, R. C., Zhu, J., Zabih, R., & Santacatterina, M. (2026). Are Good Generators Good Decision-Makers? Policy Learning for General Interventions via Retargeted Counterfactual Generation. arxiv

Kim, R. C., Gilbert, B., Zabih, R., Santacatterina, M., & Diaz, I. (2026). Data-adaptive and model-robust covariate adjustment for time-to-event outcomes in stratified randomized trials. arxiv

Kim, R. C., Nethery, R. C., Chen, K. L., & Bargagli-Stoffi, F. J. (2026). Fair Policy Learning under Bipartite Network Interference: Learning Fair and Cost-Effective Environmental Policies. arXiv. Under Major Revision at JASA.

Kim, R. C., Bargagli-Stoffi, F. J., Chen, K. L., & Nethery, R. C. (2026). Towards optimal environmental policies: Policy learning under arbitrary bipartite network interference. Biostatistics, 27(1), kxaf041. arxiv pub

Ghosh, S.*, Kim, R. C.*, Chhabria, P., Dwivedi, R., Klasnja, P., Liao, P., & Murphy, S. (2024). Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. Machine Learning. 113 (7) 3961-3997. arxiv pub

Kim, R. C., Lin, T., Pang, G., Liu, Y., Tungate, A. S., Hendry, P. L., Kurz, M. C., Peak, D. A., … Linnstaedt, S. D. (2023). Derivation and validation of risk prediction for posttraumatic stress symptoms following trauma exposure. Psychological Medicine, 53(11), 4952–4961. pub