Ben Nachman receives DOE grant to automate and optimize detector design using machine learning

December 14, 2021

BIDS Research Affiliate Ben Nachman has received a grant as part of the US Department of Energy's (DOE) recent investments in Research on Artificial Intelligence and Machine Learning (AI/ML) for Nuclear Physics Accelerators and Detectors. The goal of this grant — a $1M collaboration among Berkeley Lab, Lawrence Livermore National Laboratory, and UC Riverside — is to use machine learning to automate and optimize detector design for the upcoming Electron Ion Collider, a new particle accelerator being built at Brookhaven National Laboratory in upstate New York. If successful, this could be the first particle/nuclear physics experiment optimized with machine learning. "I am particularly excited about this project," says Nachman, "because it is at the intersection of particle and nuclear physics, using machine learning as a unifying tool to help bridge this traditional division." Find more information on DOE Nuclear Physics webpage.

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Benjamin Nachman

Physics Division, LBNL
Research Affiliate