TH074
The New Sun-to-Earth Machine Learning Exploratory Committee: Collecting the National Science Foundation Communities for the Application of Machine Learning to Space Physics
The New Sun-to-Earth Machine Learning Exploratory Committee: Collecting the National Science Foundation Communities for the Application of Machine Learning to Space Physics
Friday, 11 December 2020: 10:30-11:30
Primary Contact: Matthew R Argall, University of New Hampshire Main Campus, Department for Physics and Institute for the Study of Earth, Oceans and Space, Durham, NH, United States
Moderators: Viacheslav M Sadykov, New Jersey Institute of Technology, Department of Physics, Edison, NJ, United States, Jacob Bortnik, University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA, United States and Ryan Michael McGranaghan, Atmospheric and Space Technology Research Associates (ASTRA), Louisville, CO, United States
Presenters: Matthew Penn, NVIDIA, Baltimore, MD, United States, Wendy Hawley Carande, Laboratory for Atmospheric and Space Physics, Boulder, CO, United States, Enrico Camporeale, University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, United States, Verena Heidrich-Meisner, University of Kiel, Kiel, Germany, W Kent Tobiska, Space Environment Technologies, Pacific Palisades, CA, United States, Susan Skone, University of Calgary, Calgary, AB, Canada, Viacheslav G Merkin, The Johns Hopkins University, Laurel, MD, United States, Mangala Sharma, NSF, Washington, United States and Chaitanya Baru, National Science Foundation, CISE, Arlington, VA, United States
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