ED013
Education and Workforce Development for Convergence and Data Sciences in the Era of Artificial Intelligence and Machine Learning

Session ID#: 159480

Session Description:
We are witnessing unprecedented advances and increased applications of artificial intelligence (AI), machine learning (ML), and data sciences in all areas of science and society and are facing a critical need for professionals with expertise in data and information technologies, along with domain knowledge. Academia has begun producing and modifying curriculum to include enhanced training in AI/ML and data science so that students graduate with the requisite skills, literacies, and competencies. This session welcomes contributions from thought leaders and practitioners in multiple earth sciences disciplines and information science to discuss challenges, opportunities and best practices for educators, learners, and researchers to create a workforce for advancing convergence science. The proposed session will be of interest to several AGU sections, including but not limited to Atmospheric Sciences, Hydrology, Education, and Earth and Space Science Informatics.
Index Terms:

0825 Teaching methods [EDUCATION]
1817 Extreme events [HYDROLOGY]
1928 GIS science [INFORMATICS]
1942 Machine learning [INFORMATICS]

Primary Convener:  Mohan K Ramamurthy, University Corporation for Atmospheric Research, Unidata, Boulder, CO, United States
Conveners:  Venkatesh Merwade, Purdue University, West Lafayette, IN, United States, Anthony Castronova, Consortium of Universities for the Advancement of Hydrological Science, Washington, United States and Deanna A Hence, University of Illinois at Urbana Champaign, Department of Atmospheric Sciences, Urbana, United States
 
Title: WIFIRE or Why Fires? Hot New Fire Science Tools for Wildfire Prediction, Management & Prevention (1074064)
Yvonne Marie Andres, Global SchoolNet Foundation, Collaborative Learning, San Diego, United States and Elena Yualeva, Global Forest Link, San Diego, United States
 
GeoSMART: Machine Learning Training and Curriculum Development for Earth Science Studies (1101618)
Nicoleta C Cristea, University of Washington Seattle Campus, eScience Institute, Seattle, United States, Ziheng Sun, George Mason University, Center for Spatial Information Science and Systems, Fairfax, VA, United States, Anthony A Arendt, eScience Institute University of Washington, Seattle, United States, Scott T Henderson, University of Washington Seattle Campus, Seattle, United States, Marine Denolle, University of Washington, Department of Earth and Space Sciences, Seattle, United States and Annie Burgess, Earth Science Information Partners, Severna Park, MD, United States
 
Developing Innovative Problem Solvers: Engaging University Students with NASA Data to Analyze Earth System Phenomena (1109067)
Elizabeth Joyner, NASA Goddard Space Flight Center, Greenbelt, MD, United States and Kevin Ward, NASA Headquarters, Earth Science Data Systems, Washington, DC, United States
 
CyberTraining for Findable, Accessible, Interoperable, and Reusable (FAIR) Science in Water and Climate (1143252)
Venkatesh Merwade1, Carol X Song1, Matt Huber2, Sayan Dey1, Jibin Joseph1 and Lan Zhao1, (1)Purdue University, West Lafayette, IN, United States, (2)Purdue University, Department of Earth, Atmospheric, and Planetary Sciences, West Lafayette, United States
 
Teaching Remote Data Science in a University Setting: Lessons Learned and Future Directions (1179785)
Thomas Martin, National Energy Technology Laboratory, Golden, United States
 
Developing an Interdisciplinary Graduate Course to Combine Deep Learning with Process-Based Models (1182449)
Jiaqi Gong, Tuscaloosa, AL, UNITED STATES and Steven J Burian, University of Alabama, Alabama Water Institute, Tuscaloosa, AL, United States
 
The Earth Data Science Corps & ESIIL Stars Programs: Models for Learning and Teaching Environmental Data Science Skills (1189111)
Nathan Quarderer1, Jennifer Balch2, R. Chelsea Nagy3, Anne U Gold4, Elsa Culler5, Lauren Herwehe6, Nathan Korinek7, Katherine Halama8, James Sanovia9, Charles Jason Tinant10, David Parr11, Emily Biggane12, Jessica Logan12, William Travis13 and Leah Wasser14, (1)University of Colorado Boulder, CIRES / Earth Lab / Environmental Data Science Innovation & Inclusion Lab (ESIIL), Boulder, United States, (2)University of Colorado Boulder, CIRES, ESIIL, Boulder, United States, (3)University of Colorado at Boulder, ESIIL, Boulder, United States, (4)University of Colorado Boulder, Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO, United States, (5)University of Colorado at Boulder, Civil, Environmental, and Architectural Engineering, Boulder, United States, (6)University of Colorado at Boulder, Earth Lab Earth Analytics Education Initiative - CIRES, Boulder, CO, United States, (7)University of Colorado at Boulder, Earth Lab Earth Analytics Education Initiative - CIRES, Boulder, United States, (8)University of Colorado Boulder, CIRES / Earth Lab, Boulder, United States, (9)Oglala Lakota College, Kyle, United States, (10)Oglala Lakota College, Rapids City, United States, (11)Metropolitan State University of Denver, Denver, United States, (12)United Tribes Technical College, Bismarck, United States, (13)Earth Lab, University of Colorado Boulder, Boulder, CO, United States, (14)PyOpenSci, Boulder, United States
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