IN13A:
Artificial Intelligence Applications in the Geosciences: Promises and Challenges for the Future I


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Session ID#: 63554

Session Description:
The data volume within the geosciences has grown exponentially over the last few decades, and advanced computing and artificial intelligence techniques are paving new pathways for geoscientific discoveries. Specifically, AI and knowledge-based reasoning promise to accelerate discovery in the next century as approaches in adaptive sensing, machine learning, deep learning, knowledge graphing and other approaches are increasingly applied across the geosciences. Despite the demonstrated power of these techniques, their application to the geosciences is limited to date. The EarthCube sponsored Research Coordination Network for Intelligent Systems in Geosciences, or IS-GEO, is an emerging community of researchers with active working groups that support methodology and technique sharing, encourage cross-disciplinary research collaborations, and development of data benchmarks to accelerate progress. The goal of this session is to discuss the potential benefits and current challenges of artificial intelligence techniques to expand our understanding of geologic processes.
Primary Convener:  Suzanne A Pierce, University of Texas at Austin, Austin, TX, United States
Conveners:  Tarka Wilcox, Pacific Lutheran University, Tacoma, WA, United States, Imme Ebert-Uphoff, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States and Renzhi Cao, Pacific Lutheran University, Computer Sciences, Tacoma, WA, United States
Primary Liaison:  Suzanne A Pierce, Texas Advanced Computing Center, Austin, TX, United States
Chairs:  Tarka Wilcox, Pacific Lutheran University, Tacoma, WA, United States and Imme Ebert-Uphoff, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
OSPA Liaison:  Imme Ebert-Uphoff, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States

Cross-Listed:
  • GC - Global Environmental Change
  • H - Hydrology
  • NH - Natural Hazards
  • SI - Societal Impacts and Policy Sciences
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
1920 Emerging informatics technologies [INFORMATICS]
1942 Machine learning [INFORMATICS]
1968 Scientific reasoning/inference [INFORMATICS]

Abstracts Submitted to this Session:

Towards Deriving Theories from Data: Explorations of Model Inference in Geophysics (447323)
Victor Pankratius1, Cody Millard Rude2, Guillaume Rongier2 and Thomas Herring2, (1)Massachusetts Institute of Technology, Cambridge, MA, United States, (2)Massachusetts Institute of Technology, Department of Earth, Atmospheric and Planetary Sciences, Cambridge, MA, United States
Designing Topic Specific Crawls: Comparing Algorithm Performance (424563)
Ruth Duerr1, Chris A Mattmann2, Siri Jodha S Khalsa3, Srinidhi Nandakumar4, Omid Davtalab4, Simin Ahmadi Karvigh4 and Prerana Teligi Harapanahalli Math4, (1)Ronin Institute for Independent Scholarship, Westminster, CO, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, (4)University of Southern California, Los Angeles, United States
OntoSoft: A Semantic Model Catalog to Support Comparison and Reuse (350718)
Daniel Garijo, Yolanda Gil and Varun Ratnakar, University of Southern California, Information Sciences Institute, Los Angeles, CA, United States
Enhancing Lidar Data using Generative Adversarial Networks (Invited) (393761)
Ibrahim Demir1, Bekir Zahit Demiray2, Muhammed Ali Sit2 and Enes Yildirim3, (1)Tulane University, New Orleans, United States, (2)University of Iowa, Iowa City, IA, United States, (3)University of Iowa, Iowa City, United States

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