Machine Learning Collaboration Meeting

Contribution List

1. Welcome & Introduction

Kevin Brown (C-AD)

21/08/2024, 08:30

2. Overview of polarized proton acceleration and highlights of the current RHIC run

Vincent Schoefer (CAD)

21/08/2024, 09:00

3. Status of accurate accelerator models for L2B, Booster, BtL, and AGS

Eiad Hamwi (Cornell University)

21/08/2024, 09:45

4. Experimental examples of Bayesian Optimization at BNL

Lucy Lin (Cornell University)

21/08/2024, 11:00

14. Status of bunch-merge simulations and experiments using Reinforcement Learning

Yuan Gao

21/08/2024, 11:45

5. Overview of Uncertainty Quantification and application to p-p acceleration

Nathan Urban (Brookhaven National Laboratory)

21/08/2024, 16:00

6. Basis of Bayesian Optimization - connecting theory to experiment

Yinan Wang

21/08/2024, 16:30

8. Application options of the JLAB approach to reinforcement learning

Armen Kasparian

22/08/2024, 08:30

7. Connecting Bmad and BNL control systems - Digital Twin preparations

Kiel Hock (Brookhaven National Laboratory)

22/08/2024, 09:15

9. Applications of international ML experiences in the Linac to RHIC chain

Auralee Edelen (SLAC/Stanford)

22/08/2024, 10:00

10. Bmad Julia - what new code do ML applications need

David Sagan (faculty@cornell.edu;member@cornell.edu;alum@cornell.edu;employee@cornell.edu)

22/08/2024, 11:00

11. Improved emittance measurements

Jon Edelen (RadiaSoft)

22/08/2024, 11:45

12. Steps toward digital twins

Lucy Lin (Cornell University)

22/08/2024, 13:30

13. Summary, and brain storming

Georg Hoffstaetter (Cornell)

22/08/2024, 14:00