COLLECTION OF PAPERS

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC  (link to JINST 17 C07003)

AI4EIC proceeding, Sep 2021

Machine learning on FPGA for event selection  (link to JINST 17 C06009)

AI4EIC proceeding, Sep 2021

Frontiers in computing for artificial intelligence  (link to JINST 17 C03037)

AI4EIC proceeding, Sep 2021

AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider (link to arXiv:2205.09185 [physics.ins-det])

New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering (link to 2201.12197 [hep-ph])

JHEP 04 (2022) 084 DOI: 10.1007/JHEP04(2022)084

Reconstructing the Kinematics of Deep Inelastic Scattering with Deep Learning (link to arXiv:2110.05505)

NIM-A 1025 (2022) 166164, 10.1016/j.nima.2021.166164

Artificial Intelligence for Imaging Cherenkov Detectors at the EIC (link to arXiv:2204.08645,; link to JINST 17 C07011)

AI4EIC proceeding, Sep 2021

AI for Experimental Controls at Jefferson Lab, (link to 2022_JINST_17_C03043)

AI4EIC proceeding, Sep 2021

Machine learning for track reconstruction at the LHC (link to 2022 JINST 17 C02026)

AI4EIC proceeding, Sep 2021

EIC Detector Overview (link to 2022 JINST 17 C02018, arXiv:2202.13970)

AI4EIC proceeding, Sep 2021

 Design of Detectors at the Electron Ion Collider with Artificial Intelligence (link to arXiv:2203.04530v2)

AI4EIC proceeding, Sep 2021

Machine Learning for the LHCb Simulation (link to arXiv:2110.07925

AI4EIC proceeding, Sep 2021

Accelerator and detector control for the EIC with machine learning (link to 2022 JINST 17 C02022)

AI4EIC proceeding, Sep 2021

Deeply Learning Deep Inelastic Scattering Kinematics (link to arXiv:2108.11638v2)

Revealing the structure of light pseudoscalar mesons at the electron–ion collider (link to arXiv:2102.11788v1, paper)

AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case (link to arXiv, paper)

DeepRICH: learning deeply Cherenkov detectors (link to arXiv:1911.11717, paper)

AI-based Monte Carlo event generator for electron-proton scattering, Alanazi, Y. et al., (link to arXiv:2008.03151v1 [hep-ph])

Nuclear Parton Distributions from Lepton-Nucleus Scattering and the Impact of an Electron-Ion Collider (link to arXiv 1904.00018, EPJ C)