Kyle Compare

Kyle's research interests involve applying data-driven practices to advance the understanding of water quantity and quality issues. He has worked on statistical analysis of groundwater-surface water exchanges, machine learning of aquatic geochemical datasets, and artificial neural network modeling of hydrologic systems. He also works in coordination with the USGS Data Science Branch to develop data science products for national-scale investigations.