Name: AI4EIC 2023 Annual Workshop
Start: 2023-11-28T09:00:00-05:00
End: 2023-12-01T17:00:00-05:00
Location: Catholic University of America, Washington D.C.

AI4EIC 2023 Annual Workshop

from Tuesday 28 November 2023 (09:00) to Friday 1 December 2023 (17:00)

Monday 27 November 2023
Tuesday 28 November 2023

09:30

09:30 - 10:00
10:00
10:00 - 13:00
Contributions

10:00 Introduction: ePIC Overview - John Lajoie (Iowa State University)

10:15 Performance optimization for a scintillating glass electromagnetic calorimeter at EIC - Dmitrii Kalinkin (University of Kentucky)

10:40 Object Condensation for Track Building in a Backward Electron Tagger at the EIC - Simon Gardner (University of Glasgow)

11:20 The Optimal use of Segmentation for Sampling Calorimeters - Fernando Torales Acosta (Staff@lbl.gov;Member@lbl.gov;Other@lbl.gov)

11:45 AID(2)E: AI-Assisted Detector Design at EIC - Cristiano Fanelli (W&M)

12:10 Flash Talks

12:55 Discussion
13:00 Lunch
Lunch
13:00 - 14:00
14:00
14:00 - 17:00
Contributions

14:00 LHCb Calibration/Alignment - Biljana Mitreska (Dortmund Tech. U.)

14:23 ML-based Calibration and Control of the GlueX Central Drift Chamber - David Lawrence (Jefferson Lab)

14:46 Towards Fast Calibration with the ePIC Barrel Hadronic Calorimeter - Derek Anderson (Iowa State University)

15:29 Hydra: Computer Vision for Data Quality Monitoring - Thomas Britton (JLAB)

15:52 Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data - Yi Huang (Brookhaven national lab)

16:15 Autonomous selection of physics events: A RHIC demonstrator for EIC physics - Cameron Dean (MIT)

16:38 Discussion
Wednesday 29 November 2023
09:00
09:00 - 10:00
Contributions

09:00 Tutorial: Continual Learning - Andrea Cossu (University of Pisa)
10:00
10:00 - 13:00
Contributions

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
13:00 Lunch
Lunch
13:00 - 14:00
14:00
14:00 - 17:05
Contributions

14:00 The EXCLAIM collaboration approach to deeply virtual exclusive processes - simonetta liuti (university of virginia)

14:25 Decoding inverse problems in QCD with ML-based algorithms - Yaohang Li (Old Dominion University)

14:50 What can AI do for lattice-QCD parton distribution calculations? - Huey Wen (MSU)

15:30 Interpretable Machine Learning applications to Jet Background Subtraction - Charles Hughes (Iowa State University)

15:55 High Dimensional Unfolding using Machine Learning - Benjamin Nachman

16:20 Hadronization Models Using Machine Learning - Manuel Szewc (University of Cincinnati)

16:45 Discussion
Thursday 30 November 2023
09:00
09:00 - 10:00
Contributions

09:00 Tutorial: Reinforcement Learning
10:00
10:00 - 13:00
Contributions

10:00 Introduction and Overview of Foundation Models - Kazuhiro Terao (SLAC National Accelerator Laboratory)

10:30 The Trillion Parameter Consortium - Rick Stevens (ANL)

10:50 A Large Language Model-based Assistant for the Electron Ion Collider - Karthik Suresh (William & Mary )

11:10 Chatlas - the ATLAS AI Assistant - Daniel Murnane (LBL)

11:45 TrackBERT - Generalist Learning of Trackers for Downstream Tasks - Xiangyang Ju (Lawrence Berkeley National Laboratory)

12:05 Adversarial Methods for Generative Data Understanding - Eric Yeats (Duke)

12:25 Toward a generative modeling analysis of CLAS exclusive 2π photoproduction - Tareq Alghamdi (ODU)

12:45 Discussion
13:00 Lunch
Lunch
13:00 - 14:00
14:00
14:00 - 17:00
Contributions

14:00 Machine learning as a service for HEP using cloud - Luca Giommi (University of Bologna)

14:20 Particle identification with machine learning from incomplete data in the ALICE experiment - Maja Karwowska (CERN, Warsaw U. of Tech.)

14:40 Scalable AI/ML Workflow Management Across Distributed Heterogeneous Resources With PanDA - Wen Guan (BNL)

15:05 The Exa.TrkX Project - Xiangyang Ju (Lawrence Berkeley National Laboratory)

15:45 ATLAS data analysis using a parallelized workflow on distributed cloud-based services with GPUs - Jay Sandersara (CERN)

16:10 Online Track Reconstruction and Physics Analysis in CLAS12 - Gagik Gavalian (Jefferson Lab)

16:30 MLaaS4HEP, Machine Learning for Columnar High Energy Physics Analysis - Elliott Kaufman (Princeton University)

16:50 Discussion
17:00

17:00 - 17:30
Room: Caldwell auditorium
Friday 1 December 2023
09:00
09:00 - 10:00
Room: Caldwell auditorium
Contributions

09:00 Tutorial: Hackathon - James Giroux (William & Mary ) Karthik Suresh (William & Mary ) Patrick Moran (William & Mary )
10:00

10:00 - 17:00
Room: Caldwell auditorium