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I am an Associate Professor in the Department of Biostatistics at the Yale School of Public Health, and hold a secondary appointment in the Department of Internal Medicine (Section of Cardiovascular Medicine) at Yale School of Medicine. I am also a faculty member in the Center for Methods in Implementation and Prevention Science (CMIPS), the Yale Center for Analytical Sciences (YCAS), and the Clinical and Translational Research Accelerator (CTRA). I received my Ph.D. in Biostatistics from Duke University in May, 2019, and joined the Yale Biostatistics faculty in July, 2019.

My research is centered on advancing statistical methodology in causal inference, clinical trial design, and mediation analysis, integrating modern semiparametric and machine learning techniques to address complex challenges in pragmatic trials, clinical research, biomedical science, and public health. Examples of my research agenda include: (1) improving study planning, estimands construction, and model-robust methods that enhance rigor and efficiency of cluster randomized trials and stepped wedge designs; (2) advancing propensity score methods, doubly or multiply robust methods, principal stratification, and causal mediation techniques to address challenges such as censored endpoints, mismeasured exposures, and intermediate variables; (3) developing and integrating flexible and principled frequentist and Bayesian machine learning algorithms to improve both average and individualized causal effect estimation in clinical trials and observational studies with clustered and longitudinal structures, time-varying treatments and intercurrent events. I have led or contributed to the development of many statistical software packages that enable rigorous analysis of biomedical, clinical, and public health data. I am committed to advancing methodological innovations that drive meaningful real-world impact. A full list of my scholarly work can be found on my Google Scholar Page.

I have led and collaborated on multiple extramurally funded research projects, working closely with clinicians, biostatisticians, epidemiologists, and data scientists to advance evidence-based medicine, precision medicine, healthcare delivery science, and implementation science. I also have a few editorial roles, including serving as the Co-Editor-in-Chief for Epidemiologic Methods (2024-present) and Associate Editor for Statistics in Medicine (2020-present), Annals of Applied Statistics (2024-present), Clinical Trials (2020-present), and Implementation Science (2022-present).

Hiring

I am seeking a highly-motivated postdoctoral associate to join my research team at Yale School of Public Health. The position will focus on developing innovative statistical methods in causal inference, with applications to pragmatic clinical trials, observational data and related areas. Details about the position and application instructions can be found here.

Funding

I am grateful for the multiple funded awards which have supported my work on developing new statistical methodology. These include ongoing awards:

and completed awards:

I am also grateful for support from the NIH Pragmatic Clinical Trials Collaboratory (as a member of the Biostatistics and Study Design Core, 2013-present) and NIA IMPACT Collaboratory (as an executive committee member of the Design and Statistics Core, 2019-present).

Contact

Address: Room 229, 135 College Street, New Haven, CT 06510
Office Tel: (203) 764-9835
Email: fan.f.li [@] yale [DOT] edu

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