Modeling and Quantitative Horticulture, Water Relations, Crop Production, Remote Sensing, Machine Learning   With the help of PI's Dave Block and Mason Earles I am pursuing multiple projects and investigating several aspects of agricultural technology simultaneously. Using grapevines at the Robert Mondavi Institute, we have built several models which can reliably predict single plant evapotranspiration using only easily measured biometeorological data. This technology will empower important progress in precision irrigation for high value crops. In a separate endeavor, we are using machine learning to vastly increase the speed and efficiency of the segmentation of 3D plant image datasets (such as microCT), allowing users to extract accurate measurements of 3D anatomy--this work is published and we have several interesting ongoing collaborations.