Abstract
The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.
| Original language | English |
|---|---|
| Title of host publication | High Performance Computing - ISC High Performance 2025 International Workshops, Revised Selected Papers |
| Editors | Sarah Neuwirth, Arnab Kumar Paul, Tobias Weinzierl, Erin Claire Carson |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 668-674 |
| Number of pages | 7 |
| ISBN (Print) | 9783032076113 |
| DOIs | |
| State | Published - 2026 |
| Event | 40th International Conference on High Performance Computing, ISC High Performance 2025 - Hamburg, Germany Duration: Jun 10 2025 → Jun 13 2025 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Volume | 16091 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 40th International Conference on High Performance Computing, ISC High Performance 2025 |
|---|---|
| Country/Territory | Germany |
| City | Hamburg |
| Period | 06/10/25 → 06/13/25 |
Funding
We gratefully acknowledge all A2SD-2025 workshop participants for their valuable presentations, insights, and discussions. This research used resources of the Oak Ridge Leadership Computing Facility, and is sponsored by the INTERSECT Initiative as part of the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725 and Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. The material presented in the workshop is based on work supported by the National Science Foundation under Grant No. #2449103, #2513101, #2331152, #2223704, #2138811, #2103845. BSC authors acknowledge the partial support of projects PID2019-107255GB, CEX2021-001148-S, and PID2023-147979NB-C21 from the MCIN/AEI and MICIU/AEI /10.13039/501100011033 and by FEDER, UE, and by the Departament de Recerca i Universitats de la Generalitat de Catalunya, research group MPiEDist (2021 SGR 00412).
Keywords
- AI-Driven Workflows
- Autonomous Scientific Discovery
- Cyberinfrastructure Interoperability