Research

I develop statistical and machine learning methods with real-world applications in the areas of:

Please see my Google Scholar page for a full list of publications. Here, I highlight some of my research.

[2025]

Han, L. (2025). Considerations for Using Clinical Practice Data to Study COVID-19 Vaccines in Patients with Cancer. [JAMA Oncology]
Han, L. (2025). Addressing Distribution Shift for Robust and Trustworthy Prediction and Causal Inference in Clinical AI Settings. [JAMA Network Open]
Gilbert, P. B., Peng, J., Han, L., … & Diaz, I. (2025). A Surrogate Endpoint Based Provisional Approval Causal Roadmap, Illustrated by Vaccine Development. [Biostatistics]
Gao, C., Gilbert, P.B., & Han, L. (2025). Bridging Fairness and Efficiency in Conformal Inference. [International Conference on Machine Learning (ICML)]
Liu, Y., Levis, A. W., Zhu, K., Yang, S., Gilbert, P. B., & Han, L. (2025). Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift. [arXiv]
Liu, Y., Zhu, K., Han, L., & Yang, S. (2025). COADVISE: Covariate Adjustment with Variable Selection in Randomized Controlled Trials. [arXiv]
Han, L., Hou, J., Cho, K., Duan, R., & Cai, T. (2025). Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects. [Journal of the American Statistical Association]
Guo, Z., Li, X., Han, L., & Cai, T. (2025). Robust Inference for Federated Meta-Learning. [Journal of the American Statistical Association]

Gao, C., Gilbert, P. B., & Han, L. (2024). On the Role of Surrogates in Conformal Inference of Individual Causal Effects. [arXiv]
Han, L. (2024). Truncated, Not Forgotten—Handling Left Truncation in Time-to-Event Studies. [NEJM Evidence]
Rubinstein, M., Agniel, D., Han, L., Horvitz-Lennon, M., & Normand, S. L. (2024). Bounding Causal Effects with an Unknown Mixture of Informative and Non-Informative Censoring. [arXiv]
Bather, J. R., Han, L., Bennett, A. S., Elliott, L., & Goodman, M. S. (2024). Detecting Univariate, Bivariate, and Overall Effects of Drug Mixtures using Bayesian Kernel Machine Regression. [The American Journal of Drug and Alcohol Abuse]
Han, L., Li, Y., Niknam, B., & Zubizarreta, J. R. (2024). Privacy-Preserving, Communication-Efficient, and Target-Flexible Hospital Quality Measurement. [The Annals of Applied Statistics]
Liu, Y., Levis, A., Normand, S. & Han, L. (2024). Multi-Source Conformal Inference Under Distribution Shift. [International Conference on Machine Learning (ICML)]
Han, L., Arfè, A., & Trippa, L. (2024). Sensitivity Analyses of Clinical Trial Designs: Selecting Scenarios and Summarizing Operating Characteristics. [The American Statistician]

Han, L., Shen, Z., & Zubizarreta, J. (2023). Multiply Robust Federated Estimation of Targeted Average Treatment Effects. [Advances in Neural Information Processing Systems 36 (NeurIPS)]
Han, L. (2023). Breaking Free from the Hazard Ratio: Embracing the Restricted Mean Survival Time in Clinical Trials. [NEJM Evidence]
Wang, X., Parast, L., Han, L., Tian, L., & Cai, T. (2023). Robust Approach to Combining Multiple Markers to Improve Surrogacy. [Biometrics]
Zhang, H. G., Honerlaw, J. P., Maripuri, M., …, 4CE Consortium (Han, L.),…, & Brat, G. A. (2023). Potential Pitfalls in the Use of Real-World Data for Studying Long COVID. [Nature Medicine]

Han, L., Wang, X., & Cai, T. (2022). Identifying surrogate markers in real‐world comparative effectiveness research. [Statistics in Medicine]
Day, S., Hlatshwako, T. G., Lloyd, A., Han, L., Tang, W., Bayus, B., & Tucker, J. D. (2022). Evaluating and volunteering for crowdsourced interventions: Cross-sectional data on COVID-19 safety from a University Survey. [Plos One]
Weber, G. M., Hong, C., Xia, Z., …, 4CE Consortium (Han, L.), …, & Brat, G. A. (2022). International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. NPJ Digital Medicine

Han, L., Tang, W., Ritchwood, T., … & Tucker, J. (2021). Joint international consensus statement on crowdsourcing challenge contests in health and medicine: results of a modified Delphi process. [BMJ Open]
Nauffal, V., Marstrand, P., Han, L., … & Ho, C. Y. (2021). Worldwide differences in primary prevention implantable cardioverter defibrillator utilization and outcomes in hypertrophic cardiomyopathy. [European Heart Journal]
Marston, N. A., Han, L., Olivotto, I., … & Ho, C. Y. (2021). Clinical characteristics and outcomes in childhood-onset hypertrophic cardiomyopathy. [European Heart Journal]
Lakdawala, N. K., Olivotto, I., Day, S. M., Han, L., … & Ho, C. Y. (2021). Associations between female sex, sarcomere variants, and clinical outcomes in hypertrophic cardiomyopathy. [Circulation: Genomic and Precision Medicine]

Wang, C., Han, L., Stein, G., … & Tucker, J. D. (2020). Crowdsourcing in health and medical research: a systematic review. [Infectious Diseases of Poverty]
Sidhu, K., Han, L., Picard, K. C., Tedrow, U. B., & Lakdawala, N. K. (2020). Ventricular tachycardia in cardiolaminopathy: characteristics and considerations for device programming. [Heart Rhythm]
Marstrand, P., Han, L., Day, S. M., … & SHaRe Investigators. (2020). Hypertrophic cardiomyopathy with left ventricular systolic dysfunction: insights from the SHaRe registry. [Circulation]
Halpaap, B. M., Tucker, J. D., Mathanga, D., …Han, L., …, & Reeder, J. C. (2020). Social innovation in global health: sparking location action. [The Lancet Global Health]

McCoy Jr, T. H., Han, L., Pellegrini, A. M., Tanzi, R. E., Berretta, S., & Perlis, R. H. (2019). Stratifying risk for dementia onset using large-scale electronic health record data: a retrospective cohort study. [Alzheimer’s & Dementia]
Han, L., Fine, J., Robinson, S. M., Boyle, A. A., Freeman, M., & Scholtes, S. (2019). Is seniority of emergency physician associated with the weekend mortality effect? An exploratory analysis of electronic health records in the UK. [Emergency Medicine Journal]
Li, K. T., Tang, W., Wu, D., …, Han, L., … & Tucker, J. D. (2019). Pay-it-forward strategy to enhance uptake of dual gonorrhea and chlamydia testing among men who have sex with men in China: a pragmatic, quasi-experimental study. [The Lancet Infectious Diseases]

Qin, Y., Han, L., Babbitt, A., … & Tucker, J. D. (2018). Experiences using and organizing HIV self-testing. [AIDS]
Wong, N. S., Tang, W., Han, L., … & Tucker, J. D. (2017). MSM HIV testing following an online testing intervention in China. [BMC Infectious Diseases]
Han, L., Hudgens, M. G., Emch, M. E., … & Hoffman, I. F. (2017). RTS, S/AS01 malaria vaccine efficacy is not modified by seasonal precipitation: results from a phase 3 randomized controlled trial in Malawi. [Scientific Reports]
Han, L., Wei, C., Muessig, K. E., Bien, C. H., Meng, G., Emch, M. E., & Tucker, J. D. (2017). HIV test uptake among MSM in China: implications for enhanced HIV test promotion campaigns among key populations. [Global Public Health]
Zhang, T. P., Liu, C., Han, L., … & Tucker, J. D. (2017). Community engagement in sexual health and uptake of HIV testing and syphilis testing among MSM in China: a cross‐sectional online survey. [Journal of the International AIDS Society]
Tang, W., Han, L., Best, J., … & Tucker, J. D. (2016). Crowdsourcing HIV test promotion videos: a noninferiority randomized controlled trial in China. [Clinical Infectious Diseases]
Han, L., Bien, C. H., Wei, C., … & Tucker, J. D. (2014). HIV self-testing among online MSM in China: implications for expanding HIV testing among key populations. [Journal of Acquired Immune Deficiency Syndromes]