Elia Scudiero

Elia Scudiero serves as Associate Professor of Precision Agriculture and Agronomist at the University of California, Riverside (UCR) in the Department of Environmental Sciences, while also holding an Associate Research Agronomist position with the USDA-ARS U.S. Salinity Laboratory. He directs CAFÉ (Center for Agriculture, Food, and the Environment) and leads the Digital Agronomy Lab, collaborating with farmers, water districts, and government agencies to advance sustainable agricultural practices.

His academic credentials include:

• PhD in Crop Science: Environmental Agronomy (2013) from the University of Padua, Italy
• MSc in Environmental Sciences and Technology (2009) from the University of Padua, Italy (with guest study at University of Copenhagen)
• BSc in Environmental Sciences and Technology (2006) from the University of Padua, Italy

Dr. Scudiero's research pioneers the integration of proximal and remote geophysical sensing with machine learning to model soil-plant dynamics. His work spans precision agriculture, soil salinity mapping, and climate-resilient water management, specifically targeting improved resource efficiency through dynamic deficit irrigation and hyper-dimensional data analysis. His methodologies address critical challenges in California's agricultural systems, including groundwater depletion mitigation and drought adaptation in crop production.

His distinguished scientific contributions have earned:

• 2020 Young Scholar Award (Soil Science Society of America)
• NIFA-AFRI New Investigator Grant (2019)
• Geoderma Regional Editor’s Choice (2015)
• University of Padua International Travel Grant (2012)
• Erasmus Student Fellowship (2007-2008)

As Principal Investigator, Dr. Scudiero secures competitive grants including the NIFA-AFRI award and serves as Associate Editor for Irrigation Science. His leadership in the Digital Agronomy Lab translates research into actionable solutions for agricultural stakeholders, emphasizing data-driven decision-making to balance productivity with environmental stewardship.

The Digital Agronomy Lab operates at field-to-continental scales, utilizing the 'Salt Sniffer' geophysical platform and satellite data to develop real-time salinity monitoring systems. Current projects focus on machine learning integration for predictive modeling of crop responses to environmental stressors, with direct applications for California's water-scarce agricultural regions.