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

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

Deep Learning Classification for Crop Types in North Dakota

Ziheng Sun | Liping Di | Hui Fang | Annie Burgess


Artificial Intelligence in Earth Science

Ziheng Sun | Nicoleta Cristea | Pablo Rivas

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.


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

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GeoWeaver: Building An Open-Source Platform for Enabling Ad Hoc Management, Open Sharing, and Robust Reuse of NASA Earth Data-Driven Hybrid AI Workflows


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