Data Science

Experimental Nuclear Physics


Cristiano Fanelli, James Giroux, Patrick Moran, Hemalata Nayak, Karthik Suresh, Eric Walter [2404.05752v1]

Information on the corresponding hackathon event can be found at 

K. Suresh, N. Kackar, L. Schleck, C. Fanelli, arXiv:2403.15729v1 [cs.CL]

The app can be accessed through


Link to 2023 Hackathon: Physics Event Classification Using Large Language Models (organized by C. Fanelli, J. Giroux, P. Moran, K. Suresh)

Our Data Science team will collaborate in this project with W&M co-PI (Prof. Mordijck) to organize a yearly summer school on AI/ML for fusion energy at William & Mary. 




Prof. Fanelli at W&M will be lead PI of the project AIDE (AI-assisted Detector design at the Electron Ion Collider). EIC is an accelerator project under construction at Brookhaven National Laboratory (BNL) that will probe the internal structure and forces of protons and neutrons that compose the atomic nucleus. This collaborative project involves co-PIs of national labs at Brookhaven National Lab and Jefferson Lab, as well as of other universities, Catholic University of America, and Duke University.

More info at: 

Prof. Fanelli will be co-PI of the project AI-Optimized Polarization, led by Jefferson Lab.  W&M will collaborate to provide a continuous AI/ML control for the polarized beam at the GlueX experiment in Hall D.
More info at: 
Lectures on AI/ML for Nuclear Physics and the Electron Ion Collider 
More info at: 

Organizer of the AI4EIC workshop (W&M, 2022) – included sessions are (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. 
During the workshop we had AI/ML tutorial sessions provided by experts (academia, national labs, industry). 
Organizer of the AI4EIC Hackathon (October 14, whole day event).
More info: