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2nd workshop on Artificial Intelligence for the Electron Ion Collider

10–14 Oct 2022
William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall
US/Eastern timezone
Artificial Intelligence for the Electron Ion Collider

Contacts

Contribution List

45 / 45
45. EIC schedule and overview
Elke-Caroline Aschenauer (BNL), Rolf Ent (Jefferson Lab)
10/10/2022, 10:25
41. DOE perspective on opportunities for AI in nuclear physics
Manouchehr Farkhondeh (US Department of Energy, Office of Nuclear Physics)
10/10/2022, 11:40
42. NSF perspective on opportunities for AI in nuclear physics
Bogdan Mihaila (National Science Foundation)
10/10/2022, 13:30
1. Tutorial on Ax/Botorch: Multi-Objective Optimization
Max Balandat (Meta/AI Facebook )
10/10/2022, 14:00
2. Adaptive experimentation to assist detector design at EIC: from ECCE to ePIC and beyond
karthik suresh (University of Regina)
10/10/2022, 14:55
5. AI-driven detector design for the EIC
Benjamin Nachman
10/10/2022, 15:20
3. ML application for beam optics control in the LHC
Elena Fol (CERN)
10/10/2022, 16:00

Particle accelerator optimization problems deal with non-linear,
multi-objective functions which depend on thousands of time-varying machine components and settings. These properties often meet the limitations of traditional optimization methods and make this problem a perfect candidate for
application of ML-based techniques. In this talk I will present, how ML can improve the control of the...
4. AI/ML overview for accelerator design activities
Todd Satogata (Jefferson Lab)
10/10/2022, 16:25
6. ML for QCD Analysis - 3D Imaging
simonetta liuti (university of virginia)
11/10/2022, 10:00
7. Modeling Hadronization Using ML and the Lund String Model
Tony Menzo (U. Cincinnati)
11/10/2022, 10:25
8. Modeling Hadronization Using ML and the Cluster Model
Siodmok Andzrej (Jagiellonian U.)
11/10/2022, 10:50
9. A(I)DAPT
Astrid Hiller Blin (Thomas Jefferson National Accelerator Facility)
11/10/2022, 11:30
10. Femtoscale Imaging of Nuclei using ML and Exascale Platforms
nobuo sato (Jefferson Lab)
11/10/2022, 11:55
11. Differentiable Simulations
Benjamin Nachman
11/10/2022, 12:20
12. Discussion
11/10/2022, 12:45
15. Fast Detector Simulations with Machine Learning
David Shih (Rutgers)
11/10/2022, 14:00
14. Machine Learning in Spectroscopy and Partial Wave Analysis
William Phelps (Christopher Newport University/Jefferson Lab)
11/10/2022, 14:25
13. Reconstructing DIS and SIDIS properties
Connor Pecar (Duke University)
11/10/2022, 14:50
16. overview talk on ML-based unfolding
Anja Butter (Heidelberg U.)
11/10/2022, 15:35
17. Tutorial on Unfolding
Fernando Torales - Acosta, Vinicius Mikuni (Other@lbl.gov;Staff@lbl.gov;Member@lbl.gov)
11/10/2022, 16:00
18. Interpretable Networks for Identifying Leptons
Daniel Whiteson (UC Irvine)
12/10/2022, 10:00
23. Tagging heavy flavor jets @ RHIC
Raghav Kunnawalkam Elayavalli (Vanderbilt University)
12/10/2022, 10:30
20. Muon Identification with Deep Learning at EIC
William Phelps (Christopher Newport University/Jefferson Lab)
12/10/2022, 11:00
19. Machine Learning in ACTS
Corentin Allaire (IJCLAB)
12/10/2022, 11:28
21. ML particle identification with measured shower profiles from calorimetry
Chao Peng (Argonne National Laboratory)
12/10/2022, 11:48
22. Lambda event tagging at CLAS12
Matthew McEneaney (Duke)
12/10/2022, 12:06
43. ML for calorimetry
Nathan Branson (Messiah U.)
12/10/2022, 12:24
44. Data-driven learning: Flux+Mutability
James Giroux (U. Regina)
12/10/2022, 12:42
24. Tutorial on MLFlow
Kishansingh Rajput (Jefferson Lab)
12/10/2022, 14:00
25. Foundation Model Infrastructure
Svitlana Volkova
12/10/2022, 15:00
26. AI/ML hardware co-design
Frank Liu (ORNL)
12/10/2022, 15:18
27. Machine Learning with FPGA
Nhan Tran (Fermilab)
12/10/2022, 15:35
28. AI/Ml with HPC
Joo Balint (ORNL)
12/10/2022, 15:52
29. Panel Discussion
Jin Huang (Brookhaven National Lab), Mike Williams (MIT), Tia Miceli (Fermilab)
12/10/2022, 16:15
30. INDRA-ASTRA
Markus Diefenthaler (Jefferson Lab)
13/10/2022, 10:00
31. Fast ML for FPGA
Sergey Furletov (JLab)
13/10/2022, 10:22
32. AI for streaming readout: an architectural perspective
Roberto Ammendola (INFN/Roma2)
13/10/2022, 10:44
33. AI-based data reduction for streaming DAQ
Jin Huang (Brookhaven National Lab)
13/10/2022, 11:16
34. Streaming Readout for Next Generation Electron Scattering Experiments
Mariangela Bondi (INFN/Catania)
13/10/2022, 11:38
35. ML for Heavy Flavor Identification
Cameron Dean (MIT)
13/10/2022, 12:00
36. AI for Experimental Controls
Thomas Britton (JLAB)
13/10/2022, 12:22
37. Tutorial on Graph Neural Networks
Yihui Ren (BNL)
13/10/2022, 14:00
38. Hackathon on October 14
13/10/2022, 14:50
39. Summaries
13/10/2022, 15:30
40. Future
Cristiano Fanelli (W&M)
13/10/2022, 16:15
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