Session

FRAG MC13 Artificial Intelligence and Machine Learning

FRAG
26 Sept 2025, 09:00
Grand Ballroom (Palmer House Hilton Chicago)

Grand Ballroom

Palmer House Hilton Chicago

17 East Monroe Street Chicago, IL 60603, United States of America

Conveners

FRAG MC13 Artificial Intelligence and Machine Learning

  • Mirjam Lindberg (MAX IV Laboratory)
  • Mike Fedorov (Lawrence Livermore National Laboratory)

Presentation materials

There are no materials yet.
Zachary Lentz (Linac Coherent Light Source)
26/09/2025, 09:00
MC13: Artificial Intelligence & Machine Learning
Contributed Oral Presentation

LCLS is currently developing and deploying beamline optimization techniques at their x-ray endstations. This is an increasingly important topic at LCLS as it fully leverages its new high rep-rate superconducting beam. The increased throughput of the LCLS-II era suddenly shifts the performance bottleneck to on-shift beam setup time. As part of the Illumine collaboration, LCLS is leveraging...

Thierry Neal (TRANSMUTEX)
26/09/2025, 09:15
MC13: Artificial Intelligence & Machine Learning
Contributed Oral Presentation

Transmutex SA is developing an accelerator-driven system (ADS) designed to generate clean energy while reducing the lifetime of radioactive waste. Such a subcritical reactor concept requires high reliability and a high degree of accelerator automation to ensure operational effectiveness.

To address these demands, a machine learning (ML) methodology was developed and experimentally...

Zeyu Dong (Stony Brook University)
26/09/2025, 09:30
MC13: Artificial Intelligence & Machine Learning
Contributed Oral Presentation

The National Synchrotron Light Source II (NSLS-II) uses a highly stable electron beam to produce high-quality X-ray beams with high brightness and low-emittance synchrotron radiation. The traditional algorithm to stabilize the beam applies singular value decomposition (SVD) on the orbit response matrix to remove noise and extract actions. Supervised learning has been studied on NSLS-II storage...

Thorsten Hellert (Lawrence Berkeley National Laboratory)
26/09/2025, 09:45
MC13: Artificial Intelligence & Machine Learning
Contributed Oral Presentation

The deployment of agentic AI systems at the Advanced Light Source (ALS) marks a major step toward autonomous, intelligent facility operations. By connecting large language models (LLMs) with diverse data sources, we are developing agents that not only interface with the control system but also provide a natural language interface for operators and scientists. This allows users to interact with...

Building timetable...