Ryan Gooch is a postdoctoral researcher in image processing and deep learning techniques in the Concentrating Solar Power program at NREL. His work at NREL focuses on applying computer vision and machine learning techniques to solar collector characterization. His background is in weather radar signal and image processing, data discovery, real-time data systems, and community engagement.
Ryan is currently serving as an elected member on the Leadership Council of the NSF-funded EarthCube program, an initiative focused on enhancing cyberinfrastructure and innovating the culture of research in the geosciences. Ryan has served on the Engagement Team since 2016 and was a member of the CHORDS project on real-time data collection, visualization, and analysis in the cloud. He continues to serve the community in governance and participation through various projects and efforts.
Research Interests
Deep learning and transfer learning
Image processing
Solar power
Weather radar
Community advocacy and engagement
Education
Ph.D., Electrical Engineering, Colorado State University
M.S., Electrical Engineering, University of Kentucky
B.S., Electrical Engineering, University of Kentucky
Featured Work
Improving historical data discovery in weather radar image data sets using transfer learning, IEEE Transactions on Geoscience and Remote Sensing (Manuscript submitted for publication, 2020)
Visualization and Storage of Weather Radar Data with CHORDS, EarthCube Annual Meeting (2019)
EarthCube Leadership Council 2019 NSF Solicitation Guidance, NSF EarthCube Technical Report (2019)
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