Autonomous Workflows interconnecting AI/ML, Modeling & Simulation + Experimental Instruments

Recent advancements in edge computing, automation, and artificial intelligence (AI) have spurred the development of "smart" autonomous laboratories and facilities that integrate complex workflows across experimental instruments and distributed heterogeneous computational resources. The primary objective of our minisymposium is to showcase recent advances aimed at establishing research ecosystem capabilities that seamlessly integrate real-time experiment and computational workflows across edge devices, cloud computing, and high-performance computing (HPC) resources. While edge computing enables laboratories to rapidly process data at its source to reduce latency and improve real-time decision-making, AI/ML and HPC simulations are fundamental components that allow autonomous laboratories to rapidly learn, adapt, and optimize workflow processes. Our minisymposium presentations offer a distinct perspective that highlight common smart autonomous science workflows that transcend disciplinary boundaries to seamlessly foster cross-disciplinary collaboration and knowledge exchange. The full integration of AI/ML, modeling and simulation, and experimental instruments is an impossible task for a single group. Hence, our minisymposium is intended to both inform attendees of recent complex workflow efforts and build new collaborations to tackle future challenges with building an interoperable ecosystem for complex workflows that enable autonomous laboratories and facilities.