Tenured Associate Professor in the Department of Statistics and Actuarial Science at the University of Iowa
Research focuses on scalable Bayesian computation, dimension reduction, and array-variate mixed models
Develops divide-and-conquer methods to scale posterior inference
Recent work emphasizes applications of array-variate models and high-dimensional Gaussian processes to neuroscience, including multimodal data from local field potentials, gene expression, and imaging
Collaborates extensively with scientists and clinicians and teaches students across diverse backgrounds
Developed and regularly teaches two statistical learning courses at Iowa (launched in Fall 2016 and Spring 2023)