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, November 28, 2023 (9:00 AM) to Friday, December 1, 2023 (5:00 PM)

Monday, November 27, 2023
Tuesday, November 28, 2023

9:30 AM

9:30 AM - 10:00 AM
10:00 AM
10:00 AM - 1:00 PM
Contributions

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

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

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

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

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

12:10 PM Flash Talks

12:55 PM Discussion
1:00 PM Lunch
Lunch
1:00 PM - 2:00 PM
2:00 PM
2:00 PM - 5:00 PM
Contributions

2:00 PM LHCb Calibration/Alignment - Biljana Mitreska (Dortmund Tech. U.)

2:23 PM ML-based Calibration and Control of the GlueX Central Drift Chamber - David Lawrence (Jefferson Lab)

2:46 PM Towards Fast Calibration with the ePIC Barrel Hadronic Calorimeter - Derek Anderson (Iowa State University)

3:29 PM Hydra: Computer Vision for Data Quality Monitoring - Thomas Britton (JLAB)

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

4:15 PM Autonomous selection of physics events: A RHIC demonstrator for EIC physics - Cameron Dean (MIT)

4:38 PM Discussion
Wednesday, November 29, 2023
9:00 AM
9:00 AM - 10:00 AM
Contributions

9:00 AM Tutorial: Continual Learning - Andrea Cossu (University of Pisa)
10:00 AM
10:00 AM - 1:00 PM
Contributions

10:00 AM Bayesian Optimization Techniques for Accelerator Control and Characterization - Ryan Roussel (SLAC National Laboratory)

10:20 AM Machine learning for digital twin development and polarization optimization at BNL hadron injectors - Lucy Lin (Cornell University)

10:40 AM Beam Condition Forecasting with non-destructive measurements at FACET-II - Matt Kilpatrick (RadiaSoft)

11:00 AM 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 AM Anomaly detection at an X-ray FEL - Daniel Ratner (staff@stanford.edu;member@stanford.edu)

11:55 AM Uncertainty estimation and RL applications at JLab - Malachi Schram (Thomas Jefferson National Accelerator Facility)

12:15 PM Using Machine Learning to Improve Dynamic Aperture Estimates - Frederik Van der Veken (CERN)

12:35 PM Discussion
1:00 PM Lunch
Lunch
1:00 PM - 2:00 PM
2:00 PM
2:00 PM - 5:05 PM
Contributions

2:00 PM The EXCLAIM collaboration approach to deeply virtual exclusive processes - simonetta liuti (university of virginia)

2:25 PM Decoding inverse problems in QCD with ML-based algorithms - Yaohang Li (Old Dominion University)

2:50 PM What can AI do for lattice-QCD parton distribution calculations? - Huey Wen (MSU)

3:30 PM Interpretable Machine Learning applications to Jet Background Subtraction - Charles Hughes (Iowa State University)

3:55 PM High Dimensional Unfolding using Machine Learning - Benjamin Nachman

4:20 PM Hadronization Models Using Machine Learning - Manuel Szewc (University of Cincinnati)

4:45 PM Discussion
Thursday, November 30, 2023
9:00 AM
9:00 AM - 10:00 AM
Contributions

9:00 AM Tutorial: Reinforcement Learning
10:00 AM
10:00 AM - 1:00 PM
Contributions

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

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

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

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

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

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

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

12:45 PM Discussion
1:00 PM Lunch
Lunch
1:00 PM - 2:00 PM
2:00 PM
2:00 PM - 5:00 PM
Contributions

2:00 PM Machine learning as a service for HEP using cloud - Luca Giommi (University of Bologna)

2:20 PM Particle identification with machine learning from incomplete data in the ALICE experiment - Maja Karwowska (CERN, Warsaw U. of Tech.)

2:40 PM Scalable AI/ML Workflow Management Across Distributed Heterogeneous Resources With PanDA - Wen Guan (BNL)

3:05 PM The Exa.TrkX Project - Xiangyang Ju (Lawrence Berkeley National Laboratory)

3:45 PM ATLAS data analysis using a parallelized workflow on distributed cloud-based services with GPUs - Jay Sandersara (CERN)

4:10 PM Online Track Reconstruction and Physics Analysis in CLAS12 - Gagik Gavalian (Jefferson Lab)

4:30 PM MLaaS4HEP, Machine Learning for Columnar High Energy Physics Analysis - Elliott Kaufman (Princeton University)

4:50 PM Discussion
5:00 PM

5:00 PM - 5:30 PM
Room: Caldwell auditorium
Friday, December 1, 2023
9:00 AM
9:00 AM - 10:00 AM
Room: Caldwell auditorium
Contributions

9:00 AM Tutorial: Hackathon - James Giroux (William & Mary ) Karthik Suresh (William & Mary ) Patrick Moran (William & Mary )
10:00 AM

10:00 AM - 5:00 PM
Room: Caldwell auditorium

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