Lauren Liao


Lauren Liao is currently a doctoral candidate in Biostatistics at the University of California, Berkeley, co-advised by Sam Pimentel and Alejandro Schuler. Her research interests broadly encompass efficiently using prior studies to support causal study design and analysis in support of the underrepresented population. She currently leads the statistical methods development in prognostic-covariate adjustment with efficient estimators in randomized trial analysis. Recent work has been in treatment prediction for gestational diabetes using supervised machine learning.

Research interests: 

causal inference, machine learning, observational study design, efficient estimators, maternal and child health