IN014
Growing Opportunities for Multiparty Collaborations in Artificial Intelligence and Machine Learning for Science Research and Applications

Session ID#: 158529

Session Description:
The NASA Science Mission Directorate (SMD) seeks to expand the use of Artificial Intelligence and Machine Learning (AI/ML) for NASA science research and applications. Over the last two years, a cross-disciplinary NASA/SMD team has conducted a series of activities to this end; the past year has focused on developing benchmark training datasets and models in each of the NASA/SMD Divisions (Planetary, Astrophysics, Heliophysics, Biological and Physical Sciences), with an emphasis on cross-divisional applications. This session will use short overviews of the benchmark training datasets and models to seed discussion among attendees on how to stimulate and expand AI/ML science research with other agencies, universities, companies, and non-profits in order to cultivate sustainable partnerships and collaborations. The session invites talks and posters on interdisciplinary and cross-organizational AI/ML science research, in particular with regard to (but by no means limited to) benchmark training datasets and models. The overall goal of enabling science research, while cultivating growing trust in evidence-based science, are in consonance with AGU’s strategic plan.
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
1916 Data and information discovery [INFORMATICS]
1942 Machine learning [INFORMATICS]
1954 Natural language processing [INFORMATICS]

Primary Convener:  Megan Ansdell, NASA Headquarters, Science Mission Directorate, Washington, DC, United States
Convener:  Megan Ansdell, NASA Headquarters, Science Mission Directorate, Washington, DC, United States
 
A Self-Supervised Learning-Based Recommender System for NASA's PDS (1084077)
Jeffrey Claiborne Smith1, Douglas A. Caldwell2, Matthew S Tiscareno2, Mark Showalter1 and Robert S French2, (1)SETI Institute Mountain View, Mountain View, CA, United States, (2)SETI Institute, Mountain View, CA, United States
 
First NASA Challenge Results: AI/ML approach to find faint comets in SOHO/LASCO data (1093187)
Ekaterina Verner, NASA Headquarters, Washington, DC, United States and Karl Battams, Naval Research Laboratory, Washington, DC, United States
 
Benchmarking NASA’s Black Marble Product Suite for Near-Real Time Monitoring of Nighttime Combustion (1132046)
Srija Chakraborty1, Tomohiro Oda2, Virginia L. Kalb3, Zhuosen Wang3, Eleanor C Stokes4 and Ranjay Man Shrestha3, (1)Universities Space Research Association, Columbia, United States, (2)Universities Space Research Association, Earth from Space Institute, Columbia, United States, (3)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (4)Universities Space Research Association, Columbia, MD, United States
 
A Computer Vision-based Wetland Classification and Runoff Delineation Approach for Discontinuous Permafrost Landscapes of Northern Canada (1133765)
Shaghayegh Akbarpour, University of Waterloo, Civil and Environmental Engineering, Waterloo, ON, Canada and James R Craig, University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada
 
Deep learning of detecting ionospheric precursors associated with M ≥ 6.0 earthquakes in Taiwan (1135209)
Hau-Kun Jhuang1, Tsung-Che Tsai2, Yi-Ying Ho3, Lou-Chuang Lee4, Kun-han Lee4, Ching-Chou Fu4 and Cheng-Ling Kuo5, (1)Institute of Earth Sciences, Academia Sinica, Taoyuan, TAIWAN, (2)National Center for High-Performance Computing, Hsinchu, Taiwan, (3)NCU National Central University of Taiwan, Jhongli, Taiwan, (4)Institute of Earth Sciences Academia Sinica, Taipei, Taiwan, (5)Institute of Space Science National Central University, Jhongli, Taiwan
 
Open-Source Data Pipelines and Statistical Tool for Studying Pre-Seismic and Post-Seismic Disturbances in the Ionosphere and Geomagnetic Field (1143490)
Luke Cullen1, Asadullah Galib2, Andrew William Smith3, Debvrat Varshney4, Edward Brown1, Peter J Chi5, Xiangning Chu6 and Filip Svoboda1, (1)University of Cambridge, Cambridge, United Kingdom, (2)Michigan State University, East Lansing, United States, (3)University of Southampton, Department of Physics and Astronomy, Southampton, United Kingdom, (4)Computer Vision and Remote Sensing Laboratory, University of Maryland Baltimore County, Baltimore, MD, United States, (5)University of California Los Angeles, Department of Earth Planetary and Space Sciences, Los Angeles, CA, United States, (6)University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, United States
 
A Knowledge Graph Connecting Multiple NASA Science Mission Directorate Domains (1159458)
Megan Mark1,2, Fech Scen Khoo2,3, Marcella Scoczynski Ribeiro Martins2,4, Roelien Timmer2,5, Anamaria Berea2,6 and Gregory Renard2, (1)Florida Institute of Technology, Melbourne, FL, United States, (2)Frontier Development Lab, Mountain View, United States, (3)University of Oldenburg, 26111 Oldenburg, Germany, (4)Federal University of Technology - Paraná/Brazil, Curitiba, Brazil, (5)University of New South Wales, Sydney, Australia, (6)George Mason University Fairfax, Fairfax, United States
 
The Online Archiving Facility (OLAF): Whats New and How Can It Help You? (1159580)
Kristina Lopez, Tucson, AZ, UNITED STATES, Eric E Palmer, Planetary Science Institute, Tucson, AZ, United States, Conor Kingston and Mike Drum, NASA GODDARD SPACE FLIGHT CENTER - PLANETARY DATA, Tucson, AZ, United States
 
Machine Learning Based Benchmark for Space Flown Rodent Liver RNA Sequencing Data in Space Biology Research (1162919)
Nishan Pantha1, Iksha Gurung1, Muthukumaran Ramasubramanian1, Lauren Sanders2, James Casaletto3, Manil Maskey4 and Sylvain Costes5, (1)University of Alabama in Huntsville, Huntsville, AL, United States, (2)NASA Ames, Mountain View, CA, United States, (3)NASA, Mountain View, California, United States, (4)NASA, Huntsville, United States, (5)NASA ARC, Mountain View, CA, United States
 
Content-based Search of Large Image Archives at PDS Imaging Node (1164476)
Steven Lu1, Emily Dunkel1, Kevin Grimes2, Bhavan Vasu3, James McAuley1 and Kiri L. Wagstaff1, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (3)Jet Propulsion Laboratory, Machine Learning and Instrument Autonomy, Pasadena, United States
 
Benchmark Models for Classification of Radiation Type Induced in Immune Cells (1172256)
Vishal Perekadan1, Iksha Gurung1, Muthukumaran Ramasubramanian1, Lauren Sanders2, Adrienne Hoarfrost2, Manil Maskey3 and Sylvain Costes4, (1)University of Alabama in Huntsville, Huntsville, AL, United States, (2)NASA Ames, Mountain View, CA, United States, (3)NASA, Huntsville, United States, (4)NASA ARC, Mountain View, CA, United States
 
Mapping the Sun and its Irradiance in Extreme Ultraviolet from any Viewpoint with an End-to-End ML Pipeline (1172414)
Miraflor Santos, Woods Hole Oceanographic Institution, Woods Hole, United States, Benoit Tremblay, University of Montreal, Physics department, Montreal, QC, Canada, Margarita Bintsi, Imperial College London, Computing, London, United Kingdom, Robert Jarolim, University of Graz, Graz, Austria, Anna Jungbluth, University of Oxford, Oxford, United Kingdom, Andres Munoz-Jaramillo, Montana State University, Bozeman, United States, James P. Mason, Johns Hopkins University Applied Physics Laboratory, Laurel, United States, Angelos Vourlidas, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States and Sairam Sundaresan, Intel Corporation, Santa Clara, United States
 
Machine Learning for Data Constrained Planetary Mission Instruments (1178852)
Victoria Da Poian1, Eric Lyness2, Jay Qi3, Isha Shah3, Christine A Knudson4, Doug Archer5, Amy McAdam6, Greg Lipstein7 and Charles Malespin8, (1)NASA Goddard Space Flight Center, Planetary Environments Laboratory, Greenbelt, MD, United States, (2)NASA Goddard Space Flight Center, Washington, DC, United States, (3)DrivenData, Washington DC, United States, (4)CRESST/University of Maryland College Park, College Park, MD, United States, (5)NASA Johnson Space Center, Houston, United States, (6)NASA Goddard SFC, Greenbelt, MD, United States, (7)DrivenData, Denver, CO, United States, (8)NASA Goddard Space Flight Center, Greenbelt, MD, United States
 
Processing and Analysis of ISS Accelerometer Data (1181006)
Michael Scott1, Adrienne Dove2 and Kayla Schang1, (1)University of Central Florida, Orlando, FL, United States, (2)University of Central Florida, Center for Microgravity Research, Orlando, FL, United States
 
First Steps in Developing an Ontology of Targeting for the Planetary Data System (PDS) Archives (1181876)
Anne Raugh, University of Maryland College Park, Astronomy, College Park, United States, John S Hughes, Jet Propulsion Laboratory, Pasadena, United States, Edward A Guinness, Washington University in St Louis, Department of Earth and Planetary Sciences, St. Louis, United States and Mitchell K Gordon, SETI Institute Mountain View, Carl Sagan Center, Mountain View, United States
 
Radiation-Induced DNA Damage Microscopy Data Benchmarking for Machine Learning in Space Biology Research (1182782)
Lauren Sanders1, Adrienne Hoarfrost2, Vishal Perekadan3,4, Iksha Gurung3, Muthukumaran Ramasubramanian3, Manil Maskey5 and Sylvain Costes6, (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)NASA Ames, Mountain View, CA, United States, (3)University of Alabama in Huntsville, Huntsville, AL, United States, (4)NASA-IMPACT, Huntsville, United States, (5)NASA, Huntsville, United States, (6)NASA ARC, Mountain View, CA, United States
 
Machine Learning is its Own Language: a Common Tool for the ML Community (1196514)
Sara Bond1, Kiri L. Wagstaff1,2 and James McAuley1, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (2)Oregon State University, Corvallis, United States
 
Machine Learning (ML) Applications for Metadata Automation (1196997)
Maggie R Davis, Oak Ridge National Laboratory, Climate Change Science Institute, Environmental Sciences, Oak Ridge, TN, United States, Hannah Collier, Oak Ridge National Laboratory, Oak Ridge, United States and Rachael Isphording, University of New South Wales, Sydney, Australia
 
Modeling Molecular Complexity: Building a Novel Multidisciplinary Machine Learning Framework to Understand Molecular Synthesis and Signatures (1200601)
Jaden J. A. Hastings, Weill Cornell Medicine, Dept of Biophysics and Physiology, New York, United States, Aaron C Bell, The University of Tokyo, Tokyo, Japan, Timothy Gebhard, Max Planck Institute for Intelligent Systems, Empirical Inference, Tübingen, Germany, Jian Gong, Massachusetts Institute of Technology, Earth, Atmospheric, and Planetary Sciences, Cambridge, MA, United States, Atılım Güneş Baydin, University of Oxford, Department of Engineering Science, Oxford, United Kingdom, Matthew Fricke, University of New Mexico, Albuquerque, United States, Massimo Mascaro, Google, Applied AI, Mountain View, United States, Michael Phillips, University of Northern Colorado, School of Psychological Sciences, Greeley, CO, United States, Kimberly Warren-Rhodes, SETI Institute Mountain View, Mountain View, United States and Nathalie A Cabrol, SETI Institute, Mountain View, CA, United States
 
Comparative Planetology – Comparing cirques on Mars and Earth using a CNN (1200625)
Josh Williams, University of New Mexico Main Campus, Albuquerque, NM, United States
See more of: Earth and Space Science Informatics
<< Previous Session Proposal | Next Session Proposal >>