The Self-Driving Labs GRC is a premier, international scientific conference focused on advancing the frontiers of science through the presentation of cutting-edge and unpublished research, prioritizing time for discussion after each talk and fostering informal interactions among scientists of all career stages. The conference program includes an array of speakers and discussion leaders from institutions and organizations worldwide, concentrating on the latest developments in the field. The conference is five days long and held in a remote location to increase the sense of camaraderie and create scientific communities, with lasting collaborations and friendships. In addition to premier talks, the conference has designated time for poster sessions from individuals of all career stages, and afternoon free time and communal meals allow for informal networking opportunities with leaders in the field.
The Self-Driving Labs Gordon Research Conference will bring together an interdisciplinary community advancing the integration of artificial intelligence, automation, and experimental science. Self-driving laboratories (SDLs), also known as autonomous experimentation, combine data-driven experiment selection with automated execution and real-time analysis in iterative, closed-loop workflows, creating new opportunities to accelerate discovery across chemistry, materials science, biology, and engineering. As these systems mature from individual demonstrations into increasingly capable research platforms, fundamental questions are emerging around how autonomous laboratories should be designed, operated, connected, and evaluated.
The conference will focus on the cross-cutting scientific and technical challenges that determine the capabilities of next-generation autonomous laboratories. Topics will span methods for experimental design and decision-making under uncertainty; open-source software and hardware platforms; data standards, reproducibility, and interoperability; automated synthesis, processing, and characterization; orchestration of complex experimental workflows; hardware interfaces and modular automation; integration of experiments with simulation and digital twins; and emerging roles for large language models and AI agents in experimental science. By considering these challenges across multiple scientific domains, the meeting will highlight both common principles and opportunities for transferring methods between fields.
A central goal of the conference is to connect communities that are often separated by disciplinary and institutional boundaries, including experimental scientists, machine-learning researchers, roboticists, software and instrumentation developers, and researchers from academia, national laboratories, and industry. The GRC format will provide an opportunity to discuss emerging and unpublished approaches, identify shared technical bottlenecks, and develop a common understanding of best practices for reliable and reusable autonomous experimentation. By bringing these communities together, the conference aims to strengthen the growing field of self-driving laboratories, catalyze new collaborations, and help establish the scientific foundations and enabling infrastructure needed for autonomous experimentation to have broad impact in discovery and innovation.
