Jon develops and pairs methods in econometrics, spatial statistics and machine learning with global socio-environmental datasets to empirically estimate the relationships that govern our climate and agricultural systems. For example, in recent work Jon uses volcanic eruptions as natural experiments to provide the first empirically-based estimates of how solar geoengineering might impact agricultural yields. In a second strand of research he develops, characterizes and democratizes new algorithms for planetary-scale monitoring using satellite imagery. Jon graduated from Stanford University in 2014 where he studied Earth Systems; he will earn his PhD in Agricultural and Resource Economics from the University of California, Berkeley in August, 2019.
As a joint Data Science and Environmental Fellow, Jon will continue to explore 1) how human activity alters the transfer of sunlight through the atmosphere, and in turn, how these changes in radiation impact crop productivity and 2) how remote sensing measurements can be efficiently made and appropriately applied to quantify relationships in socio-environmental systems. He is excited to pursue these questions with Peter Huybers, Jim Stock, and others. When he’s not at his desk, you can find Jon backpacking, rock climbing, or teaching and performing improvisational theater.