Galen Gorski is a Machine Learning Specialist for the USGS Water Mission Area, based in Reston, VA.
I am interested in understanding fundamental connections between hydrologic and biogeochemical cycling in natural and managed landscapes. This requires a suite of methods and approaches including data-driven techniques, field campaigns, and laboratory analysis. I am interested in projects that use machine learning and other data-driven techniques to cut across these boundaries and develop understanding of the connections between water quantity and quality and their implications for water resource management and sustainability.
In my previous work, I investigated controls on nitrogen cycling in managed aquifer recharge settings in agricultural areas of California. I have also worked to develop local and regional recharge suitability maps in California and the Middle East North Africa Region to help guide future project siting. I’m excited about combining my experiences with the incredible expertise at USGS to tackle important water resource challenges.