Isabel Fulcher recently obtained her PhD in Biostatistics from Harvard University and is currently a postdoctoral fellow at the Harvard Data Science Initiative. Isabel’s research aims to develop innovative causal inference methodologies to improve the delivery of sexual and reproductive health care to at-risk populations. Her statistical interests include the development of causal inference methods that account for unmeasured confounding or peer effects on a network. She is particularly interested in the use of semiparametric and nonparametric methods to relax reliance on modeling assumptions in such settings. Currently, Isabel is working to evaluate and improve the implementation of digital maternal health interventions in Tanzania and Rwanda. As part of these global partnerships, she is committed to statistical capacity building by supporting in-country researchers to participate in and lead research.
