NSLS-II AI Campaign Pilot
Call for Proposals
Submission Deadline: Sunday, May 31, 2026, at 11:59 PM ET.
The National Synchrotron Light Source II (NSLS-II) at Brookhaven National Laboratory invites proposals for an AI Campaign Pilot Program to develop collaborative experiments for AI-enabled scientific discovery. This pilot is intended to bring together research teams with NSLS-II staff to tackle high-impact research questions through coordinated experimental campaigns that generate AI-ready datasets. By integrating advanced experimental methods at NSLS-II with AI/ML, the pilot aims to accelerate the development and deployment of AI-enabled experimentation and data analysis and to establish a new model for user access and collaboration. Selected teams will benefit from coordinated beam time access, collaboration with NSLS-II teams on data and AI workflows, and increased visibility for their AI-enabled research.
In this context, AI-ready datasets are structured, well-curated datasets with standardized formats, machine-readable metadata, and sufficient documentation to support automated analysis, reproducibility, and reuse. These datasets should be suitable for training, validation, or application of AI/ML models. AI-enabled discovery refers to the use of AI/ML methods to accelerate data interpretation, guide experiments, identify patterns, and generate new scientific insights.
What are AI Campaigns?
AI Campaigns are coordinated, multi-user efforts centered on a shared scientific objective. Teams will conduct experiments at one or more NSLS-II beamlines, complemented by synthesis and/or characterization at their home institutions and, where appropriate, other user facilities. A central requirement for participation in the pilot is the production of well-curated datasets with rich machine-readable metadata to support AI/ML analysis. Participants are expected to collaboratively develop and/or apply AI/ML tools for data acquisition, interpretation, and/or discovery. This may include selection of appropriate models and definition of training/validation strategies.
Example: Optimization of a catalyst's performance through a coordinated campaign combining spectroscopy at NSLS-II with synthesis and/or complementary characterization in the home lab to generate an integrated dataset for training, validating, and/or applying AI models.
The pilot will use NSLS-II's existing Block Allocation Group (BAG) proposal framework. Proposals must follow standard BAG requirements and address additional AI Campaign criteria listed below. Each proposal should address an overarching science question requiring NSLS-II experiments and AI/ML approaches. Teams must commit to data sharing within the BAG and with NSLS-II, including relevant data from home institutions and partner facilities. Data should include sufficient metadata to enable reuse and AI/ML analysis. NSLS-II will not share these data beyond the BAG and NSLS-II.
Proposals should clearly describe:
- The scientific question and its broader impact and the compelling need or advantage for the research anticipated through the application of AI/ML methods.
- The experimental plan at NSLS-II and complementary efforts in the proposers' home labs and at other user facilities
- The data to be generated and shared, including structure, metadata, and accessibility for AI/ML use
- The AI/ML methods and tools to be used and/or developed by the team
AI/ML approaches may range from the application of established methods to the development of new tools for data analysis and discovery. Proposals should clearly articulate how AI/ML will contribute to the scientific goals.
Submissions will be evaluated based on scientific merit, experimental design, and the strength of the data and AI integration strategy including the appropriateness of the proposed AI/ML approach and how well the data support its use. Participation by beamline staff is strongly encouraged. Proposals will be reviewed by the NSLS-II Proposal Review Panels, with final selections within the framework of this pilot made by NSLS-II management.
This pilot emphasizes the generation of AI-ready datasets, the development of robust data and AI workflows, and strong collaboration and data sharing within the BAG. Selected teams are expected to begin in the September–December 2026 beamtime cycle and showcase initial outcomes during or shortly after beamtime has been used. NSLS-II will provide support for data-sharing infrastructure and workflows, including pilot platforms for data management and access.
Researchers interested in advancing their science through coordinated, AI-enabled experimentation are encouraged to apply.
Submission details and deadlines
The deadline for submission of AI Campaign Pilot proposals is Sunday, May 31, 2026, at 11:59 PM ET. Proposals should be submitted through the NSLS-II PASS system following the guidelines for BAG proposals. Users may find the BAG Proposal template (.docx) handy for writing their proposal and then copying/pasting the information into PASS.
For questions or to discuss potential proposals, please contact the beamline scientist(s) or the NSLS-II User Administration Office.
