Machine learning in nuclear physics experiments

While machine learning methods have been applied to data analysis in experimental physics since the 1990s, the development of flexible, advanced computational tools have allowed for vast innovation in recent years. This talk will discuss the current status of machine learning applications in experimental nuclear physics, highlighting examples of recent work at various nuclear physics facilities. Visions of the future of Artificial Intelligence technology in nuclear physics will also be presented, drawing from work done by the community in preparation for the AI for Nuclear Physics whitepaper.