Amanda Hering

Professor Hering is a statistical modeler with problems requiring multivariate time series, spatial statistics, Markov-switching, clustering, and validation of primary interest. Much of her work is interdisciplinary with applications ranging from wind energy to water reuse to defense. Her current interests are in modeling big, multivariate, spatial datasets; developing methods for categorical spatial data; and detecting outliers and faults for process and data monitoring. Dr. Hering works with researchers whose data structures generate new statistical methodologies because either the goals or the size of the data presents a new challenge.