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3rd ICFA Beam Dynamics Mini-Workshop on Machine Learning Applications for Particle Accelerators (Chicago, IL - Palmer House Hilton)

Nov 1 – 4, 2022
Chicago, IL
US/Central timezone

Workshop Coordinator

Contribution List

103 / 103
57. Registration
11/1/22, 8:00 AM
64. Tutorials - Prep and Instructions
11/1/22, 8:45 AM
66. Tutorial on Bayesian Optimization
Ryan Roussel (SLAC)
11/1/22, 9:00 AM
67. Tutorial on Anomaly Detection
Antonin Sulc (MCS (MCS Fachgruppe 4))
11/1/22, 10:05 AM
68. Tutorial on Reinforcement Learning (Speaker: Kishansingh Rajput, JLAB)
11/1/22, 11:10 AM
65. ALCF - HPC for AI/ML (Corey J. Adams, ANL)
Corey Adams (ANL)
11/1/22, 1:25 PM
69. Tutorial on Uncertainty Quantification
Natalie Isenberg (Computational Science Initiative)
11/1/22, 2:10 PM
70. Xopt
Ryan Roussel (SLAC)
11/1/22, 3:15 PM
71. Badger
Zhe Zhang (SLAC)
11/1/22, 3:25 PM
72. GeOFF and COI
Nico Madysa (CERN)
11/1/22, 3:35 PM
73. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
11/1/22, 3:45 PM
74. Open Discussion
11/1/22, 3:55 PM
75. Xopt
Ryan Roussel (SLAC)
11/1/22, 4:35 PM
76. Badger
Zhe Zhang (SLAC)
11/1/22, 4:45 PM
77. GeOFF and COI
Nico Madysa (CERN)
11/1/22, 4:55 PM
78. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
11/1/22, 5:05 PM
79. Open Discussion
11/1/22, 5:15 PM
58. Meet & Greet
11/1/22, 6:00 PM
80. Registration (Coffee and Snacks will be available)
11/2/22, 8:00 AM
81. Welcome
11/2/22, 8:30 AM
82. Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements
Sara Miskovich (staff@stanford.edu;member@stanford.edu)
11/2/22, 8:55 AM
83. Machine Learning Tools to support the ATLAS Ion Linac Operations at Argonne
Jose L. Martinez-Marin (member@anl.gov)
11/2/22, 9:20 AM
84. Bayesian Optimization for Trajectory Alignment at LEReC
Yuan Gao
11/2/22, 9:45 AM
85. Machine Learning for Slow Spill Regulation in the Fermilab Delivery Ring
Mattson Thieme (NorthWestern)
11/2/22, 10:40 AM
86. Reinforcement Learning Applied to Optimization of LHC Beams in the CERN Proton Synchrotron
Joel Axel Wulff (CERN)
11/2/22, 11:05 AM
87. A Closer Look at Reinforcement Learning for Beam-Based Feedback Systems
Leander Grech (Univ. of Malta)
11/2/22, 11:30 AM
88. SRF Cavity Fault Classification and Prediction at Jefferson Lab
Chris Tennant (Jefferson Laboratory)
11/2/22, 1:25 PM
89. Beam-Based RF Station Fault Identification at the Linac Coherent Light Source
Ryan Humble (Stanford)
11/2/22, 1:50 PM
90. Status of Data-Driven Bea Trajectory Anomaly Detection
Antonin Sulc (MCS (MCS Fachgruppe 4))
11/2/22, 2:15 PM
91. Disentangling Beam Losses in the Fermilab Main Injector Enclosure Using Real-time Edge AI
Kyle Hazelwood (FNAL)
11/2/22, 2:40 PM
92. Uncertainty Aware Anomaly Detection to Predict Errant Beam Pulses and GradCAM Analysis
Kishansingh Rajput (Jefferson Lab)
11/2/22, 3:35 PM
93. Al for Muon Collider Design: Progress and Plans
Elena Fol (member@cern.ch)
11/2/22, 4:00 PM
94. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
Jonathan Edelen (RadiaSoft, LLC)
11/2/22, 4:25 PM
155. Classification and Prediction of Superconducting Magnet Quenches
Joshua Curtis-Einstein (RadiaSoft, LLC)
11/2/22, 4:45 PM
128. Beam Loss Disentangling Model Hyperparameter Tuning Methods
Isaiah Jones (Northwestern University)
11/2/22, 4:47 PM
129. Graph Embeddings for CEBAF Operations: Progress and Future Plans
Chris Tennant (Jefferson Laboratory)
11/2/22, 4:49 PM
130. Emittance Measurement Speedup with Machine Learning at the Coherent electron Cooling Experiment at RHIC
Weijian Lin (Cornell Univ.)
11/2/22, 4:51 PM
131. Machine Learning for Beam Emittance Measurement and Aberration Correction of an Electron Microscope
Desheng Ma (member@cornell.edu;alum@cornell.edu;student@cornell.edu)
11/2/22, 4:53 PM
132. Enhancing UED temporal resolution with time-stamping virtual diagnostics
FREDERICK CROPP (UCLA)
11/2/22, 4:55 PM
133. Analysis and Visualisation of Transverse beam properties at the European XFEL
Raimund Kammering (Deutsches Elektronen-Synchrotron DESY)
11/2/22, 4:57 PM
134. Muon monitor signal to predict NuMI beam parameters and horn current by applying Machine Learning techniques
Don Athula Wickremasinghe
11/2/22, 4:59 PM
135. Relating Initial Distribution to Beam Loss on the Front End of a Heavy-Ion Linac Using Machine Learning
Anthony Tran (student@msu.edu;member@msu.edu)
11/2/22, 5:01 PM
136. Machine learning-based surrogate model construction for optics matching at the European XFEL
Zihan Zhu (DESY)
11/2/22, 5:03 PM
137. An Efficient Classifier-Based Surrogate Assisted Evolutionary Algorithm
Christopher Pierce (member@cornell.edu;alum@cornell.edu;student@cornell.edu)
11/2/22, 5:05 PM
138. Image Segmentation for Automated Sample Alignment in Neutron Scattering Experiments
M. Henderson (RadiaSoft, LLC)
11/2/22, 5:07 PM
139. Optimization of dynamic aperture for the Electron-Ion Collider
Daniel Marx
11/2/22, 5:09 PM
154. BPM measurement prediction based on HOM signals using Machine Learning
Jorge Diaz Cruz (University of New Mexico)
11/2/22, 5:11 PM
141. Updates on the surrogate model design for MUED
Salvador Sosa (UNM)
11/2/22, 5:13 PM
142. Prospects for Machine Learning and Pulse Shaping in the Scorpius Accelerator
E.R. Scott (NNSS)
11/2/22, 5:15 PM
143. Exploring and Applying Different Machine Learning Techniques in a Synchrotron
Bohong Huang (Stony Brook University)
11/2/22, 5:17 PM
145. Neural Network Surrogate Priors for Efficient Bayesian Optimization
Ryan Roussel (SLAC National Laboratory)
11/2/22, 5:21 PM
146. Longitudinal Phase Space Manipulation at the LCLS using Neural Networks and Bayesian Optimization
Auralee Edelen (SLAC)
11/2/22, 5:23 PM
147. Learning-based Optimisation of Particle Accelerators Under Partial Observability Without Real-World Training
Jan Kaiser (Deutsches Elektronen-Synchrotron DESY)
11/2/22, 5:25 PM
148. APPLICATIONS OF MACHINE LEARNING IN PHOTO-CATHODE INJECTORS
Aasma Aslam
11/2/22, 5:27 PM
149. Xopt: A Simplified Framework for Optimization of Arbitrary Problems using Advanced Algorithms
Ryan Roussel (SLAC National Laboratory)
11/2/22, 5:29 PM
150. Fast THz Radiation Optimization for Linear Accelerator using Surrogate Model
Chenran Xu (member@kit.edu;employee@kit.edu)
11/2/22, 5:31 PM
151. Automatic Optimization of X-ray Free-Electron Laser at SACLA
Hirokazu Maesaka (Spring8)
11/2/22, 5:33 PM
152. A Smart Alarm for the CEBAF Injector
Chris Tennant (Jefferson Laboratory)
11/2/22, 5:35 PM
153. Continuous Anomaly Detection and Labeling for the Fermilab Linac
Jason St. John (Fermilab)
11/2/22, 5:37 PM
156. Apply Machine Learning in Orbit Control and Accelerator Stabilization
Zeyu Dong (Stony Brook University)
11/2/22, 5:39 PM
157. Machine Learning to Support the ATLAS Linac Operations at Argonne
Brahim Mustapha (ANL)
11/2/22, 5:41 PM
158. Design Optimization and In Situ Surrogate Modeling Activities in the Beam, Plasma & Accelerator Simulation Toolkit (BLAST)
Axel Huebl (Lawrence Berkeley National Laboratory)
11/2/22, 5:43 PM
159. Data-Driven Chaos Indicators for Beam Dynamics
Robert Rainer (Brookhaven National Laboratory)
11/2/22, 5:45 PM
96. Data-Driven Chaos Indictor for Nonlinear Dynamics and Applications on Storage Ring Lattice Design
Robert Rainer (BNL)
11/3/22, 8:30 AM
97. Towards End-to-End Differentiable Accelerator Modeling
Juan Pablo Gonzalez-Aguilera (University of Chicago)
11/3/22, 8:55 AM
98. Experience with Integrated Systems for Online Physics Modeling, Adaptive ML Modeling, and Model-Based Control
Auralee Edelen (SLAC)
11/3/22, 9:20 AM
99. Luminosity Tuning for Future Electron Ion Collider
Derong Xu (Brookhaven National Laboratory)
11/3/22, 9:45 AM
100. Application of Natural Language Processing on Electronic Logbooks
Jennefer Maldonado (Brookhaven National Laboratory)
11/3/22, 10:40 AM
101. Towards (more) autonomous accelerators - Status and Vision at CERN
Verena Kain (CERN)
11/3/22, 11:05 AM
102. How to get ML into the Control Room - the CERN ML Frameworks
Nico Madysa (member@cern.ch)
11/3/22, 11:30 AM
103. Data Analysis and Control of an MeV Ultrafast Electron Diffraction System Using Machine Learning
Trudy Bolin (UNM)
11/3/22, 1:25 PM
104. Machine Learning for Tuning, Prediction, and Control at the KIT electron accelerators
Andrea Santamaria Garcia (Karlsruhe Institute of Technology)
11/3/22, 1:50 PM
105. Towards Linac RF Optimization with Machine Learning
Ralitsa Sharankova (FNAL)
11/3/22, 2:15 PM
106. ID Orbit Compensation with Neural Networks for PETRA III
Bianca Veglia (DESY)
11/3/22, 2:40 PM
107. Recent Progress on ML-based Optimization and anomaly prediction at APS
Nikita Kuklev (ANL)
11/3/22, 3:35 PM
108. Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations
Ryan Roussel (SLAC National Laboratory), Ryan Roussel (SLAC)
11/3/22, 4:00 PM
109. Improving Neural Networks Predictions using Physics - PINN for the CERN Accelerators
Francesco Maria Velotti (CERN)
11/3/22, 4:25 PM
110. Transverse 2D Phase-Space Tomography Using BPMs
Kilean Hwang (member@msu.edu;faculty@msu.edu;employee@msu.edu)
11/3/22, 4:50 PM
111. Simulation Studies and Machine Learning Applications for Orbit Correction at the Alternating Gradient Syndhrotron
Lucy Lin (Cornell University), Weijian Lin (Cornell Univ.)
11/3/22, 5:15 PM
112. Modeling, Affiliation
11/4/22, 8:30 AM
113. Analysis Affiliation
11/4/22, 8:45 AM
125. Open Discussion
11/4/22, 9:00 AM
114. Opt, Affiliation
11/4/22, 9:10 AM
115. RL, Affiliation
11/4/22, 9:25 AM
116. BO, Affiliation
11/4/22, 9:40 AM
124. Open Discussion
11/4/22, 9:55 AM
119. Prog, Affiliation
11/4/22, 10:05 AM
118. Facility, Affiliation
11/4/22, 10:20 AM
126. Open Discussion
11/4/22, 10:35 AM
120. Future Workshop
Daniel Ratner (SLAC National Laboratory)
11/4/22, 10:45 AM
121. Concluding Remarks
Kevin Brown (C-AD), Sandra Biedron (Univ. of NM), Sandra Biedron (Element Aero)
11/4/22, 10:55 AM
63. Tour of FNAL
11/4/22, 12:00 PM

Tour Details & Tour Sign-up Form

140. Data-driven modelling of laser-plasma experiments enabled by large datasets
Andre Antoine (University of Michigan)
144. Design Optimization and In Situ Surrogate Modeling Activities in the Beam, Plasma & Accelerator Simulation Toolkit (BLAST)
Alex Huebl (LBNL)
117. Facility, Affiliation
127. ML Experience gained at BESSY II
Pierre Schnizer (BESSY II)
123. Open Discussion
95. Poster Session - 4th Floor
60. Poster Sessions
59. Sessions
61. Sessions
62. Sessions and Close Out
122. test
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