Rate My Professor Jay Bartroff

Bartroff's research focuses on methods for the analysis of sequential or streaming data, large-scale multiple testing, Stein's method, optimal experimental design, pharmacokinetics and pharmacodynamics, and biomedical applications including clinical trial design and methods for wearable alcohol biosensors. His work has received funding from the National Science Foundation, National Institutes of Health, U.S. Food and Drug Administration, and National Security Agency. He has published extensively in top-tier journals such as Annals of Statistics, Bernoulli, Biometrics, Statistical Science, and Statistica Sinica. Key publications include the textbook Sequential Experimentation in Clinical Trials: Design and Analysis (Springer, 2012); Modern Sequential Analysis and Its Applications to Computerized Adaptive Testing (Psychometrika, 2008); Two General Methods for Population Pharmacokinetic Modeling: Non-Parametric Adaptive Grid and Non-Parametric Bayesian (Journal of Pharmacokinetics and Pharmacodynamics, 2013); and Sequential Tests of Multiple Hypotheses Controlling Type I and II Familywise Error Rates (Journal of Statistical Planning and Inference, 2014). In 2024, Bartroff co-received the 17th Abraham Wald Prize in Sequential Analysis with his former PhD advisee Jinlin Song. He has also received awards for teaching and grants for pedagogical methods development.