Steven Broll

Steve is a statistician specialized in the development of methodology for biomedical data involving the modeling of disease onset or progression over time. He is particularly interested in data that is high-dimensional, where we have a collection of variables that is much larger than our sample size, and time-varying in both outcome and variables. His work involves the development of data fusion techniques and statistical models to understand the heterogeneity of diabetes including biological pathways, blood glucose variability, and environmental exposures. To do so, he utilizes time-varying -omic biomarkers and exposure data along with measurements from wearable continuous glucose monitoring devices, which measure blood glucose levels every few minutes. Improvements in the understanding of the heterogeneity of diabetes can lead to advancements in disease management and risk reduction, and so it has recently been of strong interest to the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the diabetes research community.