Publications
Research Papers
Geoweaver: Advanced cyberinfrastructure for managing hybrid geoscientific AI workflows
Ziheng Sun | Liping | Annie Burgess | Jason A. Tullis | Andrew B. Magill
Using Geoweaver to Make Snow Mapping Workflow FAIR
Ahmed Alnaim | Ziheng Sun
Making machine learning-based snow water equivalent forecasting research productive and reusable by Geoweaver
Sun, Ziheng | Cristea, Nicoleta C. | Yang, Kehan | Alnuaim, Ahmed | Bikshapathireddy, Lakshmi Chetana Gomaram | John, Aji | Pflug, Justin | Li, Brian | Pan, Hailey | Shyamsunder, Nikil | Reddygari, Rithvik | Bhandaru, Praneeth
https://ui.adsabs.harvard.edu/abs/2022AGUFMIN23A..04S/abstract
Geoweaver: Connecting Dots for Artificial Intelligence in Geoscience
Sun, Z. | Di, L. | Tullis, J. | Burgess, A. B. | Magill, A.
Geoweaver for Automating ML-based High Resolution Snow Mapping Workflow
Sun, Ziheng | Cristea, Nicoleta search by orcid
https://ui.adsabs.harvard.edu/abs/2021AGUFMIN11C..07S/abstract
Deep Learning Classification for Crop Types in North Dakota
Ziheng Sun | Liping Di | Hui Fang | Annie Burgess
Books
Artificial Intelligence in Earth Science
Ziheng Sun | Nicoleta Cristea | Pablo Rivas
https://shop.elsevier.com/books/artificial-intelligence-in-earth-science/sun/978-0-323-91737-7
About the Book:
Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work.
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Article & Resources
Utility of the Python package Geoweaver_cwl for improving workflow reusability: an illustration with multidisciplinary use cases
Kale, Amruta | Sun, Ziheng | Ma, Xiaogang
GeoWeaver: Building An Open-Source Platform for Enabling Ad Hoc Management, Open Sharing, and Robust Reuse of NASA Earth Data-Driven Hybrid AI Workflows
NASA