-
10:00
Bayesian Optimization Techniques for Accelerator Control and Characterization
-
Ryan Roussel
(SLAC National Laboratory)
-
10:20
Machine learning for digital twin development and polarization optimization at BNL hadron injectors
-
Lucy Lin
(Cornell University)
-
10:40
Beam Condition Forecasting with non-destructive measurements at FACET-II
-
Matt Kilpatrick
(RadiaSoft)
-
11:00
Machine Learning applications for collider luminosity maximization
-
Ji Qiang
(LBNL)
Sherry Li
(LBNL)
Will Fung
(MSU)
Xiaofeng Gu
(Collider Accelerator Department, BNL)
Yi-Kai Kan
(LBNL)
Yue Hao
(Michigan State University / Brookhaven National Laboratory)
-
11:35
Anomaly detection at an X-ray FEL
-
Daniel Ratner
(staff@stanford.edu;member@stanford.edu)
-
11:55
Uncertainty estimation and RL applications at JLab
-
Malachi Schram
(Thomas Jefferson National Accelerator Facility)
-
12:15
Using Machine Learning to Improve Dynamic Aperture Estimates
-
Frederik Van der Veken
(CERN)
-
12:35
Discussion
