2nd workshop on Artificial Intelligence for the Electron Ion Collider

Name: 2nd workshop on Artificial Intelligence for the Electron Ion Collider
Start: 2022-10-10T10:00:00-04:00
End: 2022-10-14T18:00:00-04:00
Location: William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall

10 Oct 2022, 10:00 → 14 Oct 2022, 18:00 US/Eastern

room 1019 (William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall )

room 1019

William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall

101 Ukrop Way, Williamsburg, VA 23185

Andrea Bressan (University of Trieste and INFN), Cristiano Fanelli (W&M), Markus Diefenthaler (Jefferson Lab), Tanja Horn (Cath), Torre Wenaus (BNL)

Description

This event follows the productive experience of the first AI4EIC workshop held in 2021 at CFNS and is organized by the EICUG AI WG. The scope of this second workshop is to cover all active and potential areas of applications of AI/ML for the EIC.

The workshop will include sessions on (i) accelerator and detector design (EPIC and potentially detector-2), (ii) connections to theory, (iii) analysis, (iv) reconstruction and particle identification, (v) infrastructure and frontiers in AI/ML and (vi) streaming readout, which will allow discussing different problems, perspectives and leading-edge solutions.

During the workshop we will have AI/ML tutorial sessions provided by experts (academia, national labs, industry). The workshop will also host a Hackathon event (on October 14, whole day event), and a cash prize will be given to the solution winning the competition.

During the first day, we will have talks with perspectives on AI/ML-related research from funding agencies.

AI/ML will be an essential part of all phases of the future EIC and is already contributing to its realization starting from the design and R&D phases. This workshop is a great opportunity to update the community on the progress of ongoing projects and future plans, with discussions on multiple cross-cutting topics that bring together theorists, experimentalists, and AI/ML practitioners.

Live document is here

Instructions on meeting coordinates will be sent via email using the information provided in the registration form.

Location:

William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall

Room 1019

101 Ukrop Way, Williamsburg, VA 23185

Break-out rooms (available all time for AI4EIC participants) 1021-1022-1023

Participants

Abdel Nasser Tawfik
Abhay Deshpande
Abid Malik
Abigail Fagan
Abishek Karki
Aditya Prasad Dash
Aiqi Cheng
Alberto Accardi
Alexey Aparin
Allison Chevis
Ananya Paul
Andrey Tarasov
Andrzej Siodmok
Angela Marotta
Anja Butter
Anselm Vossen
Apurva Narde
Artem Korobitsin
Arun Saini
ashish Jalotra
Astrid Hiller Blin
Azizah Mahmood
Balazs Ujvari
Benjamin Nachman
Bhasitha Dharmasena
Bidyut Roy
Bishnu Karki
Brandon Kriesten
Cameron Dean
Carlos Salgado
Cesar Fernandez Ramirez
Chao Peng
Charles-Joseph NAIM
Chong Shik Park
Christopher Dilks
Churamani Paudel
Claude Turner
Connor Pecar
Connor Pecar
Corentin Allaire
Cristiano Fanelli
Damien Douglas
Daniel Richford
Daniel Whiteson
David Kapukchyan
David Renteria
David Shih
Denis Furletov
Dennis Perepelitsa
Derek Glazier
Deven Misra
Diana McSpadden
Diptanil Roy
Dmitri Smirnov
Dmitry Kalinkin
Dulitha Jayakodige
E. C. Aschenauer
Eaglekumar Tarpara
Ejiro Umaka
Elena Fol
Eliezer Colina Morles
Emrul Hasan
Ethan Cline
Evaristo Cisbani
Evgeny Shulga
Fernando Torales Acosta
Fidele Twagirayezu
Frank Liu
GABRIEL CEZAR DE BIASE
Gabriel Perdue
Gage Tustin
Gagik Gavalian
German Sborlini
Gloria Montana
Gregory Matousek
Grigorii Tolkachev
Hamlet Mkrtchyan
Hangil Jang
Harish R
He Zhang
Huan Huang
Huey-Wen Lin
Ibrahim Chahrour
Isurumali Neththikumara
Ivan Kisel
Jagbir Singh
James Giroux
Jan Bernauer
Jan Strube
Janusz Oleniacz
Jared Reiten
Jaydeep Datta
Jennefer Maldonado
Jin Huang
Joe Osborn
Jonathan Zarling
Joo Balint
Jordan Lang
Joseph Niestroy
Justin Stevens
Kajal Samanta
Karthik Suresh
Kevin Adkins
Kevin Brown
Kiel Hock
Kishansingh Rajput
Klaus Dehmelt
Lanie suarez
Latiful Kabir
Lekha Reddy
Linh Nguyen
Love Preet
Malachi Schram
Manal Almaeen
Manoj Jadhav
Marco Battaglieri
Maria Paula Palhares
Maria Zurek
Mariangela Bondi
Marissa Joseph
Mark Baker
Mark Serena
Markus Diefenthaler
Martin Purschke
Matt Posik
Matthew Cheng
Matthew McEneaney
Matthieu Valette
Max Balandat
Maxim Potekhin
Meifeng Lin
Michael Finger
Miguel Arratia
Mike Williams
Miroslav Finger
Mriganka Mouli Mondal
Muhammad Junaid
Narbe Kalantarians
Nathan Branson
Nathan Kolling
Nhan Tran
Nicholas Zachariou
nobuo sato
Nuwan Chaminda Gunawardhana Waduge
Oliver Suranyi
Omar Hassan
Oscar Moreno
Patrick Stone
Pia Zurita
Pierre Chatagnon
Piyush Karande
Pooja Tanty
Prabhakar Palni
Prashanth Shanmuganathan
Prateek Hegde
Prithwish Tribedy
Rachel Montgomery
Raghav Kunnawalkam Elayavalli
Rahul Nair
Rajat Aggarwal
Rajeev Singh
Rakesh Naik
Reynier Cruz Torres
Richard Trotta
Richard Tyson
Robert Edwards
Roberto Ammendola
Roger Hernandez-Pinto
Rolf Ent
Ron Soltz
Ross Corliss
Sadie Cherry
Sakib Rahman
Salvador Alejandro Ochoa Oregon
Samuel Clark
Sanghoon Lim
Sergey Furletov
Seth Nemesure
Shang Wu
Shubha Kharel
Simon Gardner
simonetta liuti
Stefano Iovieno
Stjepan Oresic
Subashini De Silva
Svitlana Volkova
Tanja Horn
Tareq Alghamdi
Thomas Britton
Thomas Marshall
Tia Miceli
Todd Satogata
Tolga Erbora
Tony Menzo
Torre Wenaus
Torri Jeske
Tucker Hwang
Varun Neelamana
Vignesh kumar Suresh
Vinicius Mikuni
Vitalii Okorokov
Walter Wittmer
Wei Liu
Wei Xie
William Phelps
Wouter Deconinck
Xiaodong Jiang
Xiatong Wu
Xinxin Mei
Yaohang Li
Yasir Alanazi
Yihui Ren
Yossathorn Tawabutr
Yuan Gao
Yue Hao
Yulia Furletova
Yunshan Cheng
Zhenyu Ye
Zhiwan Xu
Zhongbo Kang
Zhongling Ji
Zisis Papandreou

Contacts

support@eic.ai

Monday, 10 October
- Welcome & Intro to AI4EIC
  
  AI4EIC_2nd_WS_intro_2.pdf
- Overview
  
  Conveners: Cristiano Fanelli (W&M), Tanja Horn (Cath)
  - 1
    
    EIC schedule and overview
    
    Speakers: Elke-Caroline Aschenauer (BNL), Rolf Ent (Jefferson Lab)
    
    EIC_AI4EIC_101022.pptx
  - 11:05
    
    Discussion
- 11:20
  
  Coffee break
- Opportunities for AI in NP and EIC
  
  Conveners: Cristiano Fanelli (W&M), Tanja Horn (Cath)
  - 2
    
    DOE perspective on opportunities for AI in nuclear physics
    
    Speaker: Manouchehr Farkhondeh (US Department of Energy, Office of Nuclear Physics)
    
    NP AI-ML Program-Farkhondeh-10102022 workshop -Final - submitted.pptx
  - 12:10
    
    Discussion
- 12:30
  
  Lunch (on your own)
- Opportunities for AI in NP and EIC
  
  Conveners: Cristiano Fanelli (W&M), Tanja Horn (Cath)
  - 3
    
    NSF perspective on opportunities for AI in nuclear physics
    
    Speaker: Bogdan Mihaila (National Science Foundation)
- AI/ML for Design
  
  Conveners: Evaristo Cisbani (Italian National Institute of Heath and Italian Institute of Nuclear Physics), Wouter Deconinck (University of Manitoba)
  - 4
    
    Tutorial on Ax/Botorch: Multi-Objective Optimization
    
    Speaker: Max Balandat (Meta/AI Facebook )
    
    2021010 - AI4EIC workshop Ax BoTorch MOO tutorial.pdf
    
    2022010 - AI4EIC workshop Ax BoTorch MOO tutorial stagebuild_pdf.pdf
  - 14:45
    
    Discussion
  - 5
    
    Adaptive experimentation to assist detector design at EIC: from ECCE to ePIC and beyond
    
    Speaker: karthik suresh (University of Regina)
    
    Ksuresh_AI4EIC_Talk.pdf
  - 15:15
    
    Q/A
  - 6
    
    AI-driven detector design for the EIC
    
    Speaker: Benjamin Nachman
    
    EICDetectorDesign_ai4eic2022.pdf
  - 15:40
    
    Q/A
  - 15:45
    
    Coffee Break
  - 7
    
    ML application for beam optics control in the LHC
    
    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 beams on the example of the LHC and give a short outlook on the ML application to accelerator design. Main focus of the presentation will be the application of decision tree - based methods to instrumentation faults detection, reconstruction and correction of magnet
    errors, and supervised learning for virtual diagnostics, which enables to obtain accurate information of beam properties without time-costly measurements.
    
    Speaker: Elena Fol (CERN)
    
    MLforLHC_EICWorkshop.pdf
  - 16:20
    
    Q/A
  - 8
    
    AI/ML overview for accelerator design activities
    
    Speaker: Todd Satogata (Jefferson Lab)
    
    2022-10-10-AI4EIC-Satogata.pdf
  - 16:45
    
    Q/A
  - 16:50
    
    Discussion
Tuesday, 11 October
- Experiment/Theory Connections
  
  Conveners: Maria Zurita (University of Regensburg), Markus Diefenthaler (Jefferson Lab)
  - 9
    
    ML for QCD Analysis - 3D Imaging
    
    Speaker: simonetta liuti (university of virginia)
    
    Liuti_AI_W&M.pdf
    
    Liuti_AI_W&M.pptx
  - 10:20
    
    Q/A
  - 10
    
    Modeling Hadronization Using ML and the Lund String Model
    
    Speaker: Tony Menzo (U. Cincinnati)
    
    [Menzo]MLHAD_AI4EIC.pdf
  - 10:45
    
    Q/A
  - 11
    
    Modeling Hadronization Using ML and the Cluster Model
    
    Speaker: Siodmok Andzrej (Jagiellonian U.)
    
    ML4EIC_Modeling_Hadronization_Using_ML_Cluster_Model-1.pdf
  - 11:10
    
    Q/A
  - 11:15
    
    Coffee Break
  - 12
    
    A(I)DAPT
    
    Speaker: Astrid Hiller Blin (Thomas Jefferson National Accelerator Facility)
    
    Astrid-Hiller-Blin_AI4EIC (1).pdf
  - 11:50
    
    Q/A
  - 13
    
    Femtoscale Imaging of Nuclei using ML and Exascale Platforms
    
    Speaker: nobuo sato (Jefferson Lab)
    
    AI4EIC.pdf
  - 12:15
    
    Q/A
  - 14
    
    Differentiable Simulations
    
    Speaker: Benjamin Nachman
    
    DifferentiableSimulation_ai4eic.pdf
  - 12:40
    
    Q/A
  - 15
    
    Discussion
- 13:00
  
  Lunch (on your own)
- Experiment/Theory Connections
  
  Conveners: Benjamin Nachman, Justin Stevens (William & Mary)
  - 16
    
    Fast Detector Simulations with Machine Learning
    
    Speaker: David Shih (Rutgers)
    
    AI4EIC workshop Oct 2022_Shih.pdf
  - 14:20
    
    Q/A
  - 17
    
    Machine Learning in Spectroscopy and Partial Wave Analysis
    
    Speaker: William Phelps (Christopher Newport University/Jefferson Lab)
    
    ai4eic_pwa_2022_phelps.pdf
  - 14:45
    
    Q/A
  - 18
    
    Reconstructing DIS and SIDIS properties
    
    Speaker: Connor Pecar (Duke University)
    
    AI4EIC_pecar_final.pdf
  - 15:10
    
    Q/A
  - 15:15
    
    Coffee break
  - 19
    
    overview talk on ML-based unfolding
    
    Speaker: Anja Butter (Heidelberg U.)
    
    UnfoldingAI4EIC_Anja.pdf
  - 15:55
    
    Q/A
  - 20
    
    Tutorial on Unfolding
    
    Speakers: Fernando Torales - Acosta, Vinicius Mikuni (Other@lbl.gov;Staff@lbl.gov;Member@lbl.gov)
    
    AI4EIC_Omnifold.pdf
    
    Unfolding Tutorial --- Colab
  - 16:45
    
    Discussion
Wednesday, 12 October
- Reconstruction and Particle Identification
  
  Conveners: Anselm Vossen (member@duke.edu;faculty@duke.edu), Rachel Montgomery, Sadhana Dash
  - 21
    
    Interpretable Networks for Identifying Leptons
    
    Speaker: Daniel Whiteson (UC Irvine)
    
    ML_leptons_oct2022.pdf
  - 10:25
    
    Q/A
  - 22
    
    Tagging heavy flavor jets @ RHIC
    
    Speaker: Raghav Kunnawalkam Elayavalli (Vanderbilt University)
    
    deep_learning_jet_tagging_raghav_AI4EIC.pdf
  - 10:55
    
    Q/A
  - 23
    
    Muon Identification with Deep Learning at EIC
    
    Speaker: William Phelps (Christopher Newport University/Jefferson Lab)
  - 11:15
    
    Q/A
  - 11:18
    
    Coffee break
  - 24
    
    Machine Learning in ACTS
    
    Speaker: Corentin Allaire (IJCLAB)
    
    ACTS-ML_Corentin.pdf
  - 11:45
    
    Q/A
  - 25
    
    ML particle identification with measured shower profiles from calorimetry
    
    Speaker: Chao Peng (Argonne National Laboratory)
    
    AI4EIC_Chao.pdf
  - 12:03
    
    Q/A
  - 26
    
    Lambda event tagging at CLAS12
    
    Speaker: Matthew McEneaney (Duke)
    
    McEneaney_AI4EIC_10_12_22.pdf
  - 12:21
    
    Q/A
  - 27
    
    ML for calorimetry
    
    Speaker: Nathan Branson (Messiah U.)
    
    Branson_N_AI4EIC_10-12-22_Presentation.pdf
  - 12:39
    
    Q/A
  - 28
    
    Data-driven learning: Flux+Mutability
    
    Speaker: James Giroux (U. Regina)
    
    FluxMutability_Giroux.pdf
  - 12:57
    
    Q/A
- 13:00
  
  Lunch (on your own)
- Infrastructure and Frontiers
  
  Conveners: Gabriel Perdue (Fermilab), Joe Osborn (Brookhaven National Laboratory), Malachi Schram (Thomas Jefferson National Accelerator Facility), Yihui Ren (BNL)
  - 29
    
    Tutorial on MLFlow
    
    Speaker: Kishansingh Rajput (Jefferson Lab)
    
    MLFlow tutorial
  - 14:45
    
    Q/A
  - 14:50
    
    Coffee break
  - 30
    
    Foundation Model Infrastructure
    
    Speaker: Svitlana Volkova
    
    Volkova_AI4EIC.key
  - 15:13
    
    Q/A
  - 31
    
    AI/ML hardware co-design
    
    Speaker: Frank Liu (ORNL)
  - 15:31
    
    Q/A
  - 32
    
    Machine Learning with FPGA
    
    Speaker: Nhan Tran (Fermilab)
    
    ai4eic-tran-mlfpga.pdf
  - 15:48
    
    Q/A
  - 33
    
    AI/Ml with HPC
    
    Speaker: Joo Balint (ORNL)
    
    AIAndEICTalkBjoo.key
    
    AIAndEICTalkBjoo_pdf.pdf
  - 16:05
    
    Q/A
  - 16:10
    
    break
  - 34
    
    Panel Discussion
    
    Speakers: Jin Huang (Brookhaven National Lab), Mike Williams (MIT), Tia Miceli (Fermilab)
Thursday, 13 October
- Streaming
  
  Conveners: Jan Bernauer (Stony Brook University and RIKEN-BNL Research Center), Marco Battaglieri (Jefferson Lab)
  - 35
    
    INDRA-ASTRA
    
    Speaker: Markus Diefenthaler (Jefferson Lab)
    
    Diefenthaler-INDRA-ASTRA.pdf
  - 10:20
    
    Q/A
  - 36
    
    Fast ML for FPGA
    
    Speaker: Sergey Furletov (JLab)
    
    MLFPGA_AI4EIC_2022_WM.pdf
  - 10:42
    
    Q/A
  - 37
    
    AI for streaming readout: an architectural perspective
    
    Speaker: Roberto Ammendola (INFN/Roma2)
    
    AI4EIC_Roberto_Ammendola.pdf
  - 11:04
    
    Q/A
  - 11:06
    
    Coffee break
  - 38
    
    AI-based data reduction for streaming DAQ
    
    Speaker: Jin Huang (Brookhaven National Lab)
    
    AI-based data reduction for streaming DAQ.pdf
  - 11:36
    
    Q/A
  - 39
    
    Streaming Readout for Next Generation Electron Scattering Experiments
    
    Speaker: Mariangela Bondi (INFN/Catania)
    
    Streaming_AI4EIC_bondi-2.pdf
  - 11:58
    
    Q/A
  - 40
    
    ML for Heavy Flavor Identification
    
    Speaker: Cameron Dean (MIT)
    
    ML4HF_C_Dean_20221013.pdf
  - 12:20
    
    Q/A
  - 41
    
    AI for Experimental Controls
    
    Speaker: Thomas Britton (JLAB)
    
    AI4EIC_10_2022.pdf
    
    AI4EIC_10_2022.pptx
  - 12:42
    
    Q/A
  - 12:44
    
    Discussion
- 13:00
  
  Lunch (on your own)
- Summary and Future
  
  Conveners: Cristiano Fanelli (W&M), Tanja Horn (Cath)
  - 42
    
    Tutorial on Graph Neural Networks
    
    Speaker: Yihui Ren (BNL)
    
    AI4EIC_yren_GNN_2022.pdf
    
    GCN Tutorial Colab Link
  - 14:45
    
    Q/A
  - 43
    
    Hackathon on October 14
    
    Hackathon Event on October 14 --- Information and Team Formation
  - 15:15
    
    Coffee break
  - 44
    Summaries
    
    a) Design Report
    
    Speakers: Evaristo Cisbani (Italian National Institute of Heath and Italian Institute of Nuclear Physics), Wouter Deconinck (University of Manitoba)
    
    ai4eic-design_summary_v1.pdf
    
    b) Q/A
    
    c) Theory/Experiment Connections
    
    Speakers: Maria Pia Zurita (University of Regensburg), Maria Zurita (University of Regensburg), Markus Diefenthaler (Jefferson Lab)
    
    Zurita-Diefenthaler-AI4EIC-Summary.pdf
    
    d) Q/A
    
    e) Theory/Experiment Connections
    
    Speakers: Benjamin Nachman, Justin Stevens (William & Mary)
    
    3_AI4EIC_ThyExpAnalysis.pdf
    
    f) Q/A
    
    g) Reco&PID
    
    Speakers: Anselm Vossen (Duke University), Rachel Montgomery, Sadhana Dash
    
    AIML_PID_RecSummary_new.pdf
    
    h) Q/A
    
    i) Infrastructure and Frontiers
    
    Speakers: Gabriel Perdue (Fermilab), Joe Osborn (Brookhaven National Laboratory), Malachi Schram (Thomas Jefferson National Accelerator Facility), Yihui Ren
    
    Infrastructure and frontiers
    
    j) Q/A
    
    k) Streaming
    
    Speakers: Jan Bernauer (Stony Brook University and RIKEN-BNL Research Center), Jan Bernauer (Stony Brook University and RBRC), Marco Battaglieri (Jefferson Lab)
    
    6_AI for Streaming readout.key
    
    6_AI for Streaming readout_pdf.pdf
    
    l) Q/A
  - 16:12
    
    Q/A
  - 45
    
    Future
    
    Speaker: Cristiano Fanelli (W&M)
    
    AI4EIC Future
  - 16:30
    
    Closing
Friday, 14 October
- Hackathon
  
  Conveners: Cristiano Fanelli (W&M), Diana McSpadden (Jefferson Lab), Kishansingh Rajput (Jefferson Lab), Wouter Deconinck (University of Manitoba)