Sara Geneletti

Sara Geneletti is an Associate Professor and MSc Health Data Science Programme Director at the Department of Statistics, London School of Economics and Political Science (LSE). Her research focuses on causal inference methodologies, particularly Bayesian approaches and regression discontinuity design (RDD), applied to healthcare and epidemiological studies. She co-leads an MRC-funded project analyzing drug effects using primary care data. Her work addresses bias correction in observational studies, evidence synthesis from multiple data sources, and methodological challenges in causal analysis.

Her research interests include causal inference frameworks, Bayesian modeling, and applications in public health. She explores how clinical knowledge can improve causal analyses of real-world data, emphasizing rigorous statistical methods for addressing confounding and selection bias. Her expertise spans epidemiological study designs, missing data mechanisms, and the integration of Bradford-Hill criteria in genomics.

Geneletti’s publications highlight methodological advancements in RDD, longitudinal data analysis, and bias mitigation techniques. Her work bridges statistical theory with practical challenges in healthcare, policy evaluation, and environmental health studies. She actively contributes to advancing health data science education through her role in the MSc programme.