His PhD was in Biophysics/NMR spectroscopy. He did a Bioinformatics Postdoc in Soybean genetics and now runs the Genome Informatics Facility at Iowa State University.
Kerrie is an ARS SCINet postdoc in the research group of Dr. Deb Peters in Las Cruces, NM. Her M.S. and Ph.D. degrees are in Atmospheric Sciences and her research background is in climate modeling.
Rowan is a physical scientist in the Rangeland Resource & Systems Research Unit in Fort Collins, CO. He specializes in analyzing large, multidimensional geospatial data using a variety of approaches from machine learning to numerical analysis.
Laura E. Boucheron received the B.S. and M.S. degrees in electrical engineering from New Mexico State University, Las Cruces, in 2001 and 2003, respectively, and the Ph.D. degree in electrical and computer engineering from the University of California, Santa Barbara, in 2008. She has intern and graduate research experience at both Sandia National Laboratories and Los Alamos National Laboratory and postdoctoral and research faculty experience in the Klipsch School of Electrical and Computer Engineering at New Mexico State University. She is currently an Associate Professor in the Klipsch School. Her teaching interests include signals & systems, digital signal processing, digital image processing, and pattern recognition and machine learning. Her research interests include image analysis, feature extraction, pattern recognition and machine learning, temporal image analysis, interdisciplinary research, solar image analysis, and biomedical image analysis.
Suzy is an ARS SCINet postdoc in the research group of Dr. Deb Peters in Las Cruces, NM. Her M.S. and Ph.D. degrees are in Hydrometeorology and her research background is in hydrologic observations and projections.
Amy began her SCINet postdoc in May 2020 working with Dr. Debra Peters in Las Cruces, NM after recently completing a PhD in Natural Resources from the University of Arizona. Her research background is in examining climate-ecosystem interactions at regional to hemispheric scales by integrating multiple data sources. Past projects have focused on how changes in the Northern Hemisphere jet stream influence surface climate conditions, with impacts on the length of the growing season and continental insect migration. By leveraging signatures of climate on annual tree growth, Amy has also worked on teams to reconstruct Hadley Cell extent and summer temperatures in the US Northern Rockies, lending historical context to recent observed climate. Amy is currently involved in ARS research projects that include 1) a cross-site synthesis of the impacts of climate on long-term ecology at dryland sites and 2) determining the influence of broadscale climate on the spatial spread of the vector-borne virus Vesicular Stomatitis.
Yanghui started her SCINet Postdoc position in May 2020 after receiving a Ph.D. degree in Geography from the University of Wisconsin-Madison. She works with Dr. Feng Gao and Dr. Martha Anderson at the Hydrology and Remote Sensing Laboratory in the Beltsville Agricultural Research Center, Beltsville, Maryland. Yanghui’s research projects have focused on the large-scale high-resolution monitoring of core agroecosystem variables (e.g., Leaf Area Index (LAI), crop yield), with the help of satellite remote sensing, machine learning, crop growth modeling, and data assimilation techniques. At ARS, Yanghui is currently developing a machine-learning-based approach to map LAI from Landsat and Sentinel-2 images over the entire globe. She is also interested in deriving crop phenological stages from satellite observations and monitoring agroecosystem dynamics through data assimilation.
Her PhD was in Bioinformatics and Computational Biology with a minor in Statistics. During her PhD, she developed the C++ software Mango Graph Studio which has been licensed to a startup. Since then, she has worked on automating the Influenza A Virus in Swine reports and recently has been designing Nextflow pipelines for highly scalable and reproducible pipelines. She enjoys designing workflows to reduce tedium and increase joy of discovery.