ADAPTIVE FUSION, & REASONING OF MULTI-SOURCE DATA (AFAR)

Solicitation ID: FA875023S7008

Agency: AFRL/Information Directorate

Eligibility Reasoning

Federally Funded Research and Development Centers (FFRDCs) and Government entities (e.g., Government/National laboratories, military educational institutions, etc.) are subject to applicable direct competition limitations and cannot propose to this BAA in any capacity unless they meet the following conditions:

Note: This is an AI-generated summary...

Summary

The U.S. Air Force Research Laboratory (AFRL) Information Directorate is seeking innovative approaches for the fusion, analysis, and reasoning of multi-source data through the Adaptive Fusion, Analysis & Reasoning of multi-source data (AFAR) Broad Agency Announcement (BAA FA8750-23-S-7008). With a total estimated funding of $99.9 million, the program aims to advance analytical operations for Command, Control, Communications, Computers and Intelligence (C4I) and Cyber Science missions. The BAA is open until August 29, 2028, and follows a two-step process, starting with white papers. Key research areas include: (A) Adaptive Knowledge and Information for Target Analysis (AKITA) for automated knowledge graph generation; (B) Enhancing Moving Target Engagement at Scale (EMoTES) for high-value target nomination and sensor management; (C) Publicly Available Information (PAI) Ensemble Fusion (PEF) for veracity analysis and fusion of PAI with traditional intelligence; and (D) Agentic AI Workflows for Dynamic Operational Contexts (AWARD) to accelerate kill chains. Individual awards are anticipated to range from $500K to $3M over a period of up to 36 months, with various award instruments possible, including contracts, grants, and Other Transactions.

Overall Technical Areas

Probable LBNL Areas

Focus Areas

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

Name	Score	Organization
Talita Perciano Costa Leite	0.75	CSA | SciData | Data Science Research · AI / Machine Learning
Anna Giannakou	0.75	CSA | SciData | Data Science Applications · Agentic AI Workflows
Prabal Dutta	0.75	ETA | Building Tech. & Urban Sys. | Bldg Technologies Dept · Autonomous Sensor Orchestration
Josh North	0.75	EESA | CESD | Earth System Sciences · Spatio-Temporal Analysis
Zachary Needell	0.75	ETA | Energy Analysis | Systems & Energy Tech Analysis · Modeling and Simulation
Satyarth Praveen	0.73	CSA | SciData | Data Science Applications · Multi-Modal Data Fusion
Xiaoya Chong	0.72	ESA | ALS | PS Computing staff · Recommender Systems
Victor Negut	0.72	PSA | NSD | ANP · Multi-Source Data Fusion
Alexandre Bayen	0.72	ETA | Energy Analysis | Systems & Energy Tech Analysis · Target Tracking & Custody
Harry Caufield	0.72	BSA | Env. Genomics & Sys. Biology | BioSystems Data Science · Knowledge Graph Generation

Fundamental Research Exemption (FRE)

As of the date of publication of this BAA, the Government cannot identify whether work proposed under this BAA may be considered fundamental research and may award both fundamental and non-fundamental research. Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to select award instrument type and to negotiate all instrument terms and conditions with selectees. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate.