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 …

Date

December 13, 2025

Authors

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 Liu, Jay Lofstead, Anirban Mandal, Hector Garcia Martin, Theresa Mayer, Marshall McDonnell, Vijayakumar Murugesan, Sal Nimer, Nageswara Rao, Martin Seifrid, Mitra Taheri, Michela Taufer, Konstantinos Vogiatzis