A2SD: Advancing Autonomous Scientific Discovery Workshop
Friday, June 13, 2025 9:00 AM to 1:00 PM · 4 hr. (Europe/Berlin)
Hall X9 - 1st floor
Workshop
Application Workflows for DiscoveryBioinformatics and Life SciencesChemistry and Materials ScienceCommunity EngagementComputational Physics
Information
The A2SD Workshop (Advancing Autonomous Scientific Discovery) will convene leading experts from domain science, computing, and artificial intelligence (AI) to shape the future of scientific research. As modern instrumentation capabilities outpace human decision-making speeds and data analysis capabilities, there is an urgent need to revolutionize scientific experiments through autonomous, interconnected, AI-driven laboratories.
The workshop will address critical challenges in developing self-driving laboratories, including the seamless integration of AI/ML with scientific workflows, standardization of multi-modal data collection, implementation of autonomous decision-making systems, and modernization of user facilities. Through interactive sessions and an expert panel, participants will explore how recent breakthroughs at the intersection of domain science and computing can accelerate scientific discovery through an ecosystem of interconnected, intelligent research facilities. Key focus areas include the development of hybrid AI systems combining data-driven learning with fundamental scientific principles, creation of universal interfaces for laboratory equipment and data management, and integration of real-time decision-making capabilities in experimental workflows.
The workshop aims to establish a foundation for a global community that leverages experimental, observational, and computing facilities as anchors while fostering collaboration between academia, industry, and government partners. This timely initiative will bring together scientists, researchers, and professionals from national laboratories, universities, and industry to define the roadmap for a research infrastructure that can accelerate scientific discovery at an unprecedented pace and scale. The advancement of autonomous laboratories, AI/ML integration in scientific workflows, and cross-facility collaboration represents a critical step toward transforming the future of experimental research.
Organizers:
The workshop will address critical challenges in developing self-driving laboratories, including the seamless integration of AI/ML with scientific workflows, standardization of multi-modal data collection, implementation of autonomous decision-making systems, and modernization of user facilities. Through interactive sessions and an expert panel, participants will explore how recent breakthroughs at the intersection of domain science and computing can accelerate scientific discovery through an ecosystem of interconnected, intelligent research facilities. Key focus areas include the development of hybrid AI systems combining data-driven learning with fundamental scientific principles, creation of universal interfaces for laboratory equipment and data management, and integration of real-time decision-making capabilities in experimental workflows.
The workshop aims to establish a foundation for a global community that leverages experimental, observational, and computing facilities as anchors while fostering collaboration between academia, industry, and government partners. This timely initiative will bring together scientists, researchers, and professionals from national laboratories, universities, and industry to define the roadmap for a research infrastructure that can accelerate scientific discovery at an unprecedented pace and scale. The advancement of autonomous laboratories, AI/ML integration in scientific workflows, and cross-facility collaboration represents a critical step toward transforming the future of experimental research.
Organizers:
Format
On Site
Targeted Audience
The workshop targets researchers, scientists, and technical leaders from national laboratories, universities, and industry who work at the intersection of experimental sciences, automation, and artificial intelligence. Of particular interest are professionals focused on laboratory modernization, AI/ML integration in scientific workflows, computing continuum, and autonomous systems development.
Intermediate Level
60%
Advanced Level
40%
Speakers
Rosa Badia
ManagerBarcelona Supercomputing Center
Benjamin Mintz
Director of Interconnected Science EcosystemsOak Ridge National Laboratory
Ewa Deelman
Research ProfessorUSC
Michela Taufer
Dongrarra ProfessorUniversity of Tennessess Knoxville
Milad Abolhasani
ProfessorNorth Carolina State University
Ryan Coffee
Senior Staff Research ScientistSLAC National Accelerator LaboratoryRM
Rob Moore
DirectorOak Ridge National Laboratory
