Lauren Liao is currently a doctoral student in Biostatistics at the University of California, Berkeley, mentored by Yeyi Zhu, Sam Pimentel, and Alan Hubbard. Her research interests broadly encompass observational study design and analysis in support of understudied, underrepresented, and underreported populations. She currently leads the statistical analysis in Mexican COVID-19 to identify subpopulations with highest risk of severe outcomes. Recent work has been in treatment prediction for gestational diabetes using supervised machine learning.
causal inference, observational study design, sensitivity analysis, improving maternal and early childhood health