JLab AI Town Hall

Monday Jul 26, 2021, 12:00 PM → 7:45 PM US/Eastern

David Lawrence (Jefferson Lab), Malachi Schram (Thomas Jefferson National Accelerator Facility)

Live notes:

 https://docs.google.com/document/d/1ijlhohSAc9pLmCJwpMKKj4VJfYLEtMXG20WRM58W7eU/edit?usp=sharing

2:00 PM → 2:10 PM Welcome

Speaker: David Lawrence (Jefferson Lab)

2021.07.26.AI_TownHall.pdf

Google Slides

2:10 PM → 2:15 PM Deeply Learning deep inelastic scattering kinematics

Speaker: Markus Diefenthaler (Jefferson Lab)

2:15 PM → 2:20 PM INTRA-ASTRA

Speaker: Markus Diefenthaler (Jefferson Lab)

Diefenthaler-AITownHall.pdf

2:20 PM → 2:25 PM InclAI

Speaker: Gabriel Niculescu (JMU)

2:25 PM → 2:30 PM AI/ML for TRD

Speaker: Yulia Furletova (JLAB)

GEMTRD-ML_Jul2021.pptx

2:30 PM → 2:35 PM AI/ML on FPGA

Speaker: Sergey Furletov (Jefferson Lab)

MLFPGA_TownHall_2021_07_26.pdf

2:35 PM → 2:40 PM HYDRA

Speaker: Thomas Britton (JLab)

AITownHall_2021.pdf

2:40 PM → 2:45 PM Exp. Controls using AI

Speaker: Torri Jeske (JLAB)

AI_TownHall2021-5.pdf

2:45 PM → 2:50 PM Track ID for Clusters

Speaker: Gagik Gavalian (Jefferson Lab)

2:50 PM → 2:55 PM De-noisingDrift Chamber using Autoencoders

Speaker: Gagik Gavalian (Jefferson Lab)

2:55 PM → 3:00 PM CLAS12 Level-3 trigger

Speaker: Gagik Gavalian (Jefferson Lab)

3:00 PM → 3:05 PM AI for reweighting MC di-hadron events for CLAS and CLAS12

Speaker: Sebouh Paul (UC Riverside)

3:05 PM → 3:10 PM Training Classifiers with Autoencoder Event Generators in GlueX

Speaker: Sean Dobbs (Florida State University)

3:10 PM → 3:15 PM μ/π/e PID

Speaker: David Lawrence (Jefferson Lab)

3:15 PM → 3:20 PM Solving the inverse problem at the event level

Speaker: Nobuo Sato (Jefferson Lab)

JLab AI-town hall.pdf

3:20 PM → 3:25 PM Physics-Aware Generative Adversarial Networks for Physics Event Generation

3:25 PM → 3:30 PM Neural Network Simulation of Detector Efficiency

3:30 PM → 3:35 PM Unfolding of the CLAS detector with OmniFold

Speaker: Luca Marsicano (INFN Genova)

3:35 PM → 3:40 PM ML to access multi-d xsection in hadron physics

Speaker: Marco Battaglieri (JLab/INFNGE)

ML-crosssect.pdf

3:40 PM → 3:45 PM Validation of 2 pion cross section extraction

Speaker: Evgeny Isupov (Moscow State U.)

validAItownHall.pdf

3:45 PM → 3:50 PM GAN uncertainty quantification in CLAS 2pi channel data analysis

3:50 PM → 3:55 PM Validation of event generators with extraction of physics observables

Speaker: Astrid Hiller Blin (Jefferson Lab)

3:55 PM → 4:00 PM t-SNE analysis

4:00 PM → 4:05 PM Application of t-SNE analysis to 2 pion data analysis

Speaker: Marco Battaglieri (JLab/INFNGE)

ML-tSNE.pdf

4:05 PM → 4:10 PM SAUCER: a VAE-based generative algorithm

4:10 PM → 4:15 PM Detector Design Optimization for ECCE

Speaker: Fanelli Cristiano (MIT)

AI_Town_Hall_JLab_2021_Detector_Design_Optimization_for_ECCE.pdf

4:15 PM → 4:20 PM AIPWA

Speaker: William Phelps (Christopher Newport University/Jefferson Lab)

ai_townhall_pwa_07_26_21_phelps.pdf

4:20 PM → 4:25 PM Anomalous Resonance Identification with Autoencoders

Speaker: William Phelps (Christopher Newport University/Jefferson Lab)

Anomalous Resonance Identification with Autoencoders Andru Quiroga.pdf

4:25 PM → 4:30 PM Modeling Magnetic Fields with deep neural networks

Speaker: William Phelps (Christopher Newport University/Jefferson Lab)

Modeling Magnetic Fields with deep neural networks Andru Quiroga.pdf

4:30 PM → 4:35 PM Modern extraction of Compton Form Factors using global fits with artificial neural networks.

Speaker: Zulkaida Akbar (University of Virginia)

Zulkaida_AITownHall.pptx

4:35 PM → 4:40 PM Further constraints with simultaneous fitting in DVCS

Speaker: Liliet Calero Diaz

4:40 PM → 4:45 PM Improvement in polarization measurements using artificial intelligence

4:45 PM → 4:50 PM Machine Learning for FCAL-II Shower Classification

4:50 PM → 4:55 PM A.I.-supported Research and Development of Novel Composite Aerogel Materials for Nuclear Physics Detectors

Speaker: Fanelli Cristiano (MIT)

AI_Town_Hall_JLab_07.26.2021_aerogel_UPL.pdf