AI/ML for Nuclear Physics HUGS 2025#
The HUGS 2025 - Artificial Intelligence for Nuclear Physics
(May 27 - Jue 13, 2025)
This is the landing page of the AI lectures of HUGS 2025
Synopsis: The HUGS2025 lectures on Artificial Intelligence for Nuclear Physics are a focused 6-hour program designed to introduce physics graduate students to the fundamentals of artificial intelligence and machine learning (AI/ML), and their applications in nuclear physics (NP); many examples are taken from the Electron Ion Collider (EIC) project and Jefferson Lab (JLab) experiments.
The course aims to equip students with a basic understanding of AI/ML basics, and how these techniques can be utilized to interpret and analyze NP data.
The students will gain a practical understanding of AI/ML concepts through hands-on exercises using simulated NP data. The lectures serve as a launchpad for those aspiring to integrate AI/ML techniques into their NP research while also offering valuable insights into some of the latest AI/ML initiatives ongoing at both the JLab and EIC.
This course is based on the following references [ABLN22, BDS+22, Fan21, FN21, K+21, MBW+19]
📚 2025 Lectures#
⚠️ Note: Course material will appear below.
Lectures
Tutorials
(Old) Lectures
- (Lec 1) AI/ML for Nuclear Physics - A High-Bias, Low-Variance Introduction
- (Lec 2) Leveraging AI/ML for the future Electron Ion Collider
- (Lec 2, extra) AI/ML activities at Jefferson Lab - Paving the way for the Electron Ion Collider
- (Lec 3) ePIC at EIC – The First Large-Scale Experiment Designed with the AI Assistance
(Old) Tutorials
[Pre-flight]
Other References
Datasets / Modules
Additional resources
📚 Past Editions#
Credits: Material on git, VS-Code, and HPC from AID2E