Machine learning for Fundamental Symmetries, Neutron and Neutrinos

Nuclear physics experiments exploring fundamental symmetries using neutron and neutrinos (FSNN) probe the basic laws of nature. The significant advancements in artificial intelligence and machine learning (AI/ML) over the past decade have presented tremendous opportunities for advancing nuclear experiments in the FSNN program. In this talk, I will highlight the broad and growing applications of AI/ML in FSNN experiments, including detector simulation and design optimization, real-time control and optimization of experiments, and data analysis, that will facilitate scientific discoveries.