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Ph.D. Student

Amanda Quay

Quay's research examines the water-energy-food nexus through the lens of environmental engineering and public policy. She focuses mainly on environmental policy analysis for California agriculture through the use of unique large datasets including satellite imagery. Previous research projects focused on Central Valley water and soil--these include (i) neural network models to predict soil salinity using Landsat imagery, (ii) Bayesian hierarchical models to map groundwater depth and associated uncertainty, and (iii) Ricardian models to observe crop switching behavior attributable to soil salinization. Her current research's focal point is the Sustainable Groundwater Management Act and supporting its implementation and enforcement. Quay is also interested in developing machine learning algorithms for fault detection and attribution in wastewater treatment processes.

Skip to 34:33 in the following video for Quay's AEESP presentation of their research.