Growing Opportunities for Multi-Party Collaborations in Artificial Intelligence and Machine Learning for Science Research
Growing Opportunities for Multi-Party Collaborations in Artificial Intelligence and Machine Learning for Science Research
Session ID#: 124728
Session Description:
The NASA Science Mission Directorate (SMD) Strategic Data Management Working Group seeks to expand the use of Artificial Intelligence and Machine Learning (AI/ML) throughout the NASA science community. To this end, an SMD community-wide survey, several cross-disciplinary projects, and a strategic multi-party (government, private, academic) workshop have been conducted over the past year. The overall goal of enabling science research, while cultivating growing trust in evidence-based science, are in consonance with AGU’s strategic plan.
This session will use short overviews of the cross-disciplinary projects 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 SMD team will summarize their activities to date and invites talks and posters on interdisciplinary and cross-organizational or joint AI/ML science research.
Index Terms:
1906 Computational models, algorithms [INFORMATICS]
1942 Machine learning [INFORMATICS]
1968 Scientific reasoning/inference [INFORMATICS]
Primary Convener: Megan Ansdell, NASA Headquarters, Washington, DC, United States
Conveners: Srija Chakraborty, Arizona State University, School of Computing, Informatics, and Decision System Engineering, Tempe, AZ, United States, Madhulika Guhathakurta, NASA Headquarters, Washington, DC, United States and Michael M Little, NASA Langley Research Center, Hampton, VA, United States
Primary Liaison: Megan Ansdell, NASA Headquarters, Washington, DC, United States
See more of: Earth and Space Science Informatics