- Main
ESnet Data and AI Workshop Report
- Guok, Chin;
- Balas, Ed;
- Balasubramanian, Sowmya;
- Balcas, Justas;
- Daneshamooz, Jaber;
- Gholba, Sukhada;
- Haberman, M;
- Kwang, Shawn;
- MacAuley, John;
- Moats, Sam;
- Nikahd, Matthew;
- Oehlert, Sam;
- Rotermund, Cody;
- Robb, Chris;
- Stewart, Garrett;
- Tian, Jiachuan;
- Tracy, Chris;
- Wiedlea, Andrew;
- Wu, John;
- Yang, Xi;
- Yu, Se-young
Published Web Location
https://doi.org/10.2172/2571672Abstract
In February 2025, the DOE user facility Energy Sciences Network (ESnet) held a three-day Data and AI Workshop in Berkeley, California. The objective of the workshop was to identify challenges within ESnet that could be addressed through data-driven methods, to help define ESnet’s data-analysis requirements, and to shape its AI strategy, guiding data-stewardship efforts and the direction of AI research and AIOps exploration for ESnet7, the next iteration of ESnet’s network. This report summarizes the multi-faceted discussions and findings and presents a set of recommendations for next steps.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.