Shaping the Future of Self-Driving Autonomous Laboratories Workshop

Rafael Ferreira Da Silva, Rob Moore II, Ben Mintz, Rigoberto Advincula, Anees Alnajjar, Luke Baldwin, Craig A. Bridges, Ryan Coffee, Ewa Deelman, Christian Engelmann, Brian Etz, Millie Firestone, Ian Foster, Panchapakesan Ganesh, Leslie Hamilton, Dale Huber, Ilia N. Ivanov, Shantenu Jha, Ying Li, Yongtao LiuJay Lofstead, Anirban Mandal, Hector Garcia Martin, Theresa Mayer, Marshall McDonnell, Vijayakumar Murugesan, Sal Nimer, Nageswara Rao, Martin Seifrid, Mitra Taheri, Michela Taufer, Konstantinos Vogiatzis

Research output: Book/ReportCommissioned report

Abstract

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.
Original languageEnglish
Place of PublicationUnited States
DOIs
StatePublished - 2024

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