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I  am a research scientist within the UCSB Climate Hazards Center. My research focuses on the intersections of climate, food systems, food security, and human health. My work often intersects with the Famine Early Warning System Network (FEWSNET) as I  try to discover and document the relationships among weather, crop production, prices, and food insecurity in the world’s poor countries. I spend a lot of time exploring how to make spatially-explicit forecasts of food security inputs and outcomes and then make that information accessible to the famine response community. My methods research has focused on dealing with time-varying spatial correlation structures, spatial clustering of time-series data, and empirically based spatially-explicit simulations.  I have a strong interest in spatial-time series analysis and, more recently, machine learning. Specifically, I am interested in exploring how and if various machine learning algorithms can be modified to work with data that has an explicit spatial-temporal correlation structure. When I was a PhD student I was  part of an NSF project examining 30 years of social, physical, and economic changes in the Mexican maize system. In my pre-academic life I spent 5 years as a GIS Analyst and Strategic planner, implementing enterprise GIS and Decision support systems for environmental agencies in California, Panama, and the United Arab Emirates. In total I have 19 years of combined academic and professional experience using spatial data and analytical methods to conduct research, support decisions, and solve problems.

 

You can find my CV here (updated every six months or so) and view my published papers on my google scholar page.