Mark van der Laan Dept of Statistics School of Public Health targeted learning, real-world data integration in RCTs, sequential adaptive designs, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies
Sam Pimentel Dept of Statistics causal inference, health services & policy analysis, biostatistics, discrete optimization
Aaron Fisher Dept of Psychology Idiographic Science, Group-to-Individual Generalizability, Personalization, EMA, Time Series, physiology, Methods and Statistics
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Sophia Rabe-Hesketh School of Education biostatistics, educational statistics, latent variable models, missing data methods, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models
Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Alan Hubbard School of Public Health causal inference, targeted learning, statistical issues in epidemiology, precision medicine and public health