NIST - National Institute of Standards and Technology
07/03/2025 | Press release | Distributed by Public on 07/04/2025 03:15
Event Report for 'MLXN25: Machine Learning for X-ray and Neutron Scattering'
Published
July 3, 2025
Author(s)
Peter Beaucage, Tanny Andrea Chavez Esparza, Alexander Hexemer, Tyler Martin, Peter Müller-Buschbaum, Stephan Roth, Xiaoping Wang
Abstract
The MLXN25 virtual event was held on April 15, 2025, as a continuous 24-hour global event, uniting over 300 registered participants from 18 countries and 20 user facilities to discuss how machine learning (ML) is transforming X-ray and neutron science. This year's program offered a sweeping view of emerging ML methodologies across data processing, simulation, autonomous control, and instrumentation development. The event featured 31 talks, 5 tutorials, 6 open discussions, and several live demonstrations. With contributions from academia, government laboratories, and industry, MLXN25 exemplified a vibrant, global research community pushing the boundaries of scientific discovery through artificial intelligence
Citation
Synchrotron Radiation News
Pub Type
Journals
Machine learning
Citation
Beaucage, P. , Chavez Esparza, T. , Hexemer, A. , Martin, T. , Müller-Buschbaum, P. , Roth, S. and Wang, X. (2025), Event Report for "MLXN25: Machine Learning for X-ray and Neutron Scattering", Synchrotron Radiation News (Accessed July 4, 2025)
Additional citation formats
- Google Scholar
- BibTeX
- RIS
Issues
If you have any questions about this publication or are having problems accessing it, please contact [email protected].
NIST - National Institute of Standards and Technology published this content on July 03, 2025, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on July 04, 2025 at 09:15 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at support@pubt.io