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Haolin (Leo) Li is an Assistant Professor of Biostatistics at the Boston University School of Public Health and an Adjunct Assistant Professor at the UNC Gillings School of Global Public Health. His research focuses on developing statistical and machine learning methods for complex data arising from clinical trials and real-world data. He has expertise in survival analysis, clinical trials, epidemiological research, and data-adaptive machine learning. His work is strongly application-driven and industry-focused, with close collaborations with pharmaceutical companies and public health researchers. His current research includes 

• Machine learning and semiparametric inference methods for survival data in case-cohort studies.

• Design and analysis of precision medicine clinical trials with a focus on subgroup identification and inference and frequentist information borrowing in basket and related trial designs.

• Statistical methodology for complex survey and structured data. 

In addition to methodological development, he collaborates extensively across diverse areas of biomedical science to address methodological challenges in real-world biomedical and clinical applications.