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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 out of 103 displayed
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    1. 57. Registration
      11/1/22, 8:00 AM
    2. 64. Tutorials - Prep and Instructions
      11/1/22, 8:45 AM
    3. 66. Tutorial on Bayesian Optimization
      Ryan Roussel (SLAC)
      11/1/22, 9:00 AM
    4. 67. Tutorial on Anomaly Detection
      Antonin Sulc (MCS (MCS Fachgruppe 4))
      11/1/22, 10:05 AM
    5. 68. Tutorial on Reinforcement Learning (Speaker: Kishansingh Rajput, JLAB)
      11/1/22, 11:10 AM
    6. 65. ALCF - HPC for AI/ML (Corey J. Adams, ANL)
      Corey Adams (ANL)
      11/1/22, 1:25 PM
    7. 69. Tutorial on Uncertainty Quantification
      Natalie Isenberg (Computational Science Initiative)
      11/1/22, 2:10 PM
    8. 70. Xopt
      Ryan Roussel (SLAC)
      11/1/22, 3:15 PM
    9. 71. Badger
      Zhe Zhang (SLAC)
      11/1/22, 3:25 PM
    10. 72. GeOFF and COI
      Nico Madysa (CERN)
      11/1/22, 3:35 PM
    11. 73. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
      11/1/22, 3:45 PM
    12. 74. Open Discussion
      11/1/22, 3:55 PM
    13. 75. Xopt
      Ryan Roussel (SLAC)
      11/1/22, 4:35 PM
    14. 76. Badger
      Zhe Zhang (SLAC)
      11/1/22, 4:45 PM
    15. 77. GeOFF and COI
      Nico Madysa (CERN)
      11/1/22, 4:55 PM
    16. 78. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
      11/1/22, 5:05 PM
    17. 79. Open Discussion
      11/1/22, 5:15 PM
    18. 58. Meet & Greet
      11/1/22, 6:00 PM
    19. 80. Registration (Coffee and Snacks will be available)
      11/2/22, 8:00 AM
    20. 81. Welcome
      11/2/22, 8:30 AM
    21. 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
    22. 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
    23. 84. Bayesian Optimization for Trajectory Alignment at LEReC
      Yuan Gao
      11/2/22, 9:45 AM
    24. 85. Machine Learning for Slow Spill Regulation in the Fermilab Delivery Ring
      Mattson Thieme (NorthWestern)
      11/2/22, 10:40 AM
    25. 86. Reinforcement Learning Applied to Optimization of LHC Beams in the CERN Proton Synchrotron
      Joel Axel Wulff (CERN)
      11/2/22, 11:05 AM
    26. 87. A Closer Look at Reinforcement Learning for Beam-Based Feedback Systems
      Leander Grech (Univ. of Malta)
      11/2/22, 11:30 AM
    27. 88. SRF Cavity Fault Classification and Prediction at Jefferson Lab
      Chris Tennant (Jefferson Laboratory)
      11/2/22, 1:25 PM
    28. 89. Beam-Based RF Station Fault Identification at the Linac Coherent Light Source
      Ryan Humble (Stanford)
      11/2/22, 1:50 PM
    29. 90. Status of Data-Driven Bea Trajectory Anomaly Detection
      Antonin Sulc (MCS (MCS Fachgruppe 4))
      11/2/22, 2:15 PM
    30. 91. Disentangling Beam Losses in the Fermilab Main Injector Enclosure Using Real-time Edge AI
      Kyle Hazelwood (FNAL)
      11/2/22, 2:40 PM
    31. 92. Uncertainty Aware Anomaly Detection to Predict Errant Beam Pulses and GradCAM Analysis
      Kishansingh Rajput (Jefferson Lab)
      11/2/22, 3:35 PM
    32. 93. Al for Muon Collider Design: Progress and Plans
      Elena Fol (member@cern.ch)
      11/2/22, 4:00 PM
    33. 94. RadiaSoft Tools (RadiaSoft Team, RadiaSoft)
      Jonathan Edelen (RadiaSoft, LLC)
      11/2/22, 4:25 PM
    34. 155. Classification and Prediction of Superconducting Magnet Quenches
      Joshua Curtis-Einstein (RadiaSoft, LLC)
      11/2/22, 4:45 PM
    35. 128. Beam Loss Disentangling Model Hyperparameter Tuning Methods
      Isaiah Jones (Northwestern University)
      11/2/22, 4:47 PM
    36. 129. Graph Embeddings for CEBAF Operations: Progress and Future Plans
      Chris Tennant (Jefferson Laboratory)
      11/2/22, 4:49 PM
    37. 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
    38. 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
    39. 132. Enhancing UED temporal resolution with time-stamping virtual diagnostics
      FREDERICK CROPP (UCLA)
      11/2/22, 4:55 PM
    40. 133. Analysis and Visualisation of Transverse beam properties at the European XFEL
      Raimund Kammering (Deutsches Elektronen-Synchrotron DESY)
      11/2/22, 4:57 PM
    41. 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
    42. 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
    43. 136. Machine learning-based surrogate model construction for optics matching at the European XFEL
      Zihan Zhu (DESY)
      11/2/22, 5:03 PM
    44. 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
    45. 138. Image Segmentation for Automated Sample Alignment in Neutron Scattering Experiments
      M. Henderson (RadiaSoft, LLC)
      11/2/22, 5:07 PM
    46. 139. Optimization of dynamic aperture for the Electron-Ion Collider
      Daniel Marx
      11/2/22, 5:09 PM
    47. 154. BPM measurement prediction based on HOM signals using Machine Learning
      Jorge Diaz Cruz (University of New Mexico)
      11/2/22, 5:11 PM
    48. 141. Updates on the surrogate model design for MUED
      Salvador Sosa (UNM)
      11/2/22, 5:13 PM
    49. 142. Prospects for Machine Learning and Pulse Shaping in the Scorpius Accelerator
      E.R. Scott (NNSS)
      11/2/22, 5:15 PM
    50. 143. Exploring and Applying Different Machine Learning Techniques in a Synchrotron
      Bohong Huang (Stony Brook University)
      11/2/22, 5:17 PM
    51. 145. Neural Network Surrogate Priors for Efficient Bayesian Optimization
      Ryan Roussel (SLAC National Laboratory)
      11/2/22, 5:21 PM
    52. 146. Longitudinal Phase Space Manipulation at the LCLS using Neural Networks and Bayesian Optimization
      Auralee Edelen (SLAC)
      11/2/22, 5:23 PM
    53. 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
    54. 148. APPLICATIONS OF MACHINE LEARNING IN PHOTO-CATHODE INJECTORS
      Aasma Aslam
      11/2/22, 5:27 PM
    55. 149. Xopt: A Simplified Framework for Optimization of Arbitrary Problems using Advanced Algorithms
      Ryan Roussel (SLAC National Laboratory)
      11/2/22, 5:29 PM
    56. 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
    57. 151. Automatic Optimization of X-ray Free-Electron Laser at SACLA
      Hirokazu Maesaka (Spring8)
      11/2/22, 5:33 PM
    58. 152. A Smart Alarm for the CEBAF Injector
      Chris Tennant (Jefferson Laboratory)
      11/2/22, 5:35 PM
    59. 153. Continuous Anomaly Detection and Labeling for the Fermilab Linac
      Jason St. John (Fermilab)
      11/2/22, 5:37 PM
    60. 156. Apply Machine Learning in Orbit Control and Accelerator Stabilization
      Zeyu Dong (Stony Brook University)
      11/2/22, 5:39 PM
    61. 157. Machine Learning to Support the ATLAS Linac Operations at Argonne
      Brahim Mustapha (ANL)
      11/2/22, 5:41 PM
    62. 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
    63. 159. Data-Driven Chaos Indicators for Beam Dynamics
      Robert Rainer (Brookhaven National Laboratory)
      11/2/22, 5:45 PM
    64. 96. Data-Driven Chaos Indictor for Nonlinear Dynamics and Applications on Storage Ring Lattice Design
      Robert Rainer (BNL)
      11/3/22, 8:30 AM
    65. 97. Towards End-to-End Differentiable Accelerator Modeling
      Juan Pablo Gonzalez-Aguilera (University of Chicago)
      11/3/22, 8:55 AM
    66. 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
    67. 99. Luminosity Tuning for Future Electron Ion Collider
      Derong Xu (Brookhaven National Laboratory)
      11/3/22, 9:45 AM
    68. 100. Application of Natural Language Processing on Electronic Logbooks
      Jennefer Maldonado (Brookhaven National Laboratory)
      11/3/22, 10:40 AM
    69. 101. Towards (more) autonomous accelerators - Status and Vision at CERN
      Verena Kain (CERN)
      11/3/22, 11:05 AM
    70. 102. How to get ML into the Control Room - the CERN ML Frameworks
      Nico Madysa (member@cern.ch)
      11/3/22, 11:30 AM
    71. 103. Data Analysis and Control of an MeV Ultrafast Electron Diffraction System Using Machine Learning
      Trudy Bolin (UNM)
      11/3/22, 1:25 PM
    72. 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
    73. 105. Towards Linac RF Optimization with Machine Learning
      Ralitsa Sharankova (FNAL)
      11/3/22, 2:15 PM
    74. 106. ID Orbit Compensation with Neural Networks for PETRA III
      Bianca Veglia (DESY)
      11/3/22, 2:40 PM
    75. 107. Recent Progress on ML-based Optimization and anomaly prediction at APS
      Nikita Kuklev (ANL)
      11/3/22, 3:35 PM
    76. 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
    77. 109. Improving Neural Networks Predictions using Physics - PINN for the CERN Accelerators
      Francesco Maria Velotti (CERN)
      11/3/22, 4:25 PM
    78. 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
    79. 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
    80. 112. Modeling, Affiliation
      11/4/22, 8:30 AM
    81. 113. Analysis Affiliation
      11/4/22, 8:45 AM
    82. 125. Open Discussion
      11/4/22, 9:00 AM
    83. 114. Opt, Affiliation
      11/4/22, 9:10 AM
    84. 115. RL, Affiliation
      11/4/22, 9:25 AM
    85. 116. BO, Affiliation
      11/4/22, 9:40 AM
    86. 124. Open Discussion
      11/4/22, 9:55 AM
    87. 119. Prog, Affiliation
      11/4/22, 10:05 AM
    88. 118. Facility, Affiliation
      11/4/22, 10:20 AM
    89. 126. Open Discussion
      11/4/22, 10:35 AM
    90. 120. Future Workshop
      Daniel Ratner (SLAC National Laboratory)
      11/4/22, 10:45 AM
    91. 121. Concluding Remarks
      Kevin Brown (C-AD), Sandra Biedron (Univ. of NM), Sandra Biedron (Element Aero)
      11/4/22, 10:55 AM
    92. 63. Tour of FNAL
      11/4/22, 12:00 PM

      Tour Details & Tour Sign-up Form

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