FFRDCs, including the Department of Energy National Laboratories and Centers, are eligible to respond to this LRBAA individually or as team members with eligible principal sources, if they are permitted to respond to such announcements by their sponsoring agency.
Note: This is an AI-generated summary...
Summary
The Department of Homeland Security (DHS) Science and Technology (S&T) Directorate's Long Range Broad Agency Announcement (LRBAA) 24-01 is a five-year funding opportunity, open until May 31, 2029, soliciting scientific and technical projects to improve DHS capabilities. The announcement details a three-step submission process: an initial Industry Engagement (abstract, quad chart, optional video), followed by an invitation-only Virtual Pitch, and a final invitation-only Written Proposal. The BAA seeks three types of R&D: Type I (near-term solutions for component needs), Type II (foundational science), and Type III (emerging threats). Key technical topic areas include Counter Terrorism (e.g., machine learning for threat detection, explosives characterization), Border Security (e.g., 'Screening at Speed,' Counter-UAS technology, detection canine R&D), and Cybersecurity (e.g., supply chain assurance, trustworthy AI, advanced data analytics). Awards may be structured as contracts, grants, cooperative agreements, or other transaction agreements (OTAs).
Overall Technical Areas
Machine Learning AlgorithmsAI Test & EvaluationSynthetic Data GenerationExplosives Performance CharacterizationCounter-Unmanned Aircraft SystemsAdvanced Screening TechnologiesCanine Olfaction ResearchCyber-Physical Systems SecurityHardware & Software Supply Chain AssuranceAdvanced CryptographyTrustworthy & Responsible AILarge-Scale Data AnalyticsDigital Twin DevelopmentPrivacy Enhancing Technologies
Probable LBNL Areas
BSACSAEESAESAETALDPSA
Focus Areas
Example Priorities:
DHS S&T seeks development of cost-effective methodologies and tools for training and testing of Machine Learning-based (ML-based) algorithms for detecting explosives and contraband in Computed Tomography (CT) and Millimeter Wave (MMW) images.
This includes methods to synthesize training and testing data, methods to perturb empirical data in order to explore and explain algorithm performance characteristics, and tools to assess the completeness and diversity of training and test data sets.
Innovative tools and methods are needed to provide improvements in evaluating legacy approaches to characterization, adapting state of the art technologies in related disciplines, and integrating emerging innovations.
This research topic will likely include novel experimental design approaches, development of innovative test articles, development of new technologies for modeling or physical measurement of explosives performance, new research analyses appropriate for test and evaluation, and new testing site locations suitable for conducting explosives performance testing.
Specific Technical Skills:
Machine LearningComputed Tomography (CT)Millimeter Wave (MMW) ImagingSynthetic Data GenerationAlgorithm Test & EvaluationExplosives CharacterizationExperimental DesignSensor TechnologyPhysical Measurement ModelingRisk Assessment
Potential PIs for this Area:
Name
Score
Organization
Shawn Tornga
0.73
LD | LD | ONHS
Daniela Ushizima
0.72
CSA | AMCR | Applied Math & Computational Sciences Div Office
Nicolas Abgrall
0.71
PSA | NSD | ANP
Hannah Parrilla
0.71
PSA | NSD | ANP
Emil Rofors
0.71
PSA | NSD | ANP
Zhe Bai
0.71
CSA | AMCR | Computer Science
Jayson Vavrek
0.71
PSA | NSD | ANP
Marco Salathe
0.71
PSA | NSD | ANP
Alexander Sim
0.71
CSA | SciData | Data Science Research
Edward Bethel
0.70
CSA | SciData | Data Science Research
Example Priorities:
Screening at Speed seeks to mature transformative technologies that increase aviation security effectiveness from curb-to-gate while dramatically reducing wait times and improving passenger experiences.
Capabilities of particular interest include accessible property (carry-on baggage) screening systems, components, and algorithms; on-person screening systems, components, and algorithms; curb-to-gate screening capabilities and integration architectures.
The primary objective of this LRBAA is to develop enhanced technologies and methods that allow for the detection, tracking, identification, and mitigation of unmanned aircraft systems under varied terrains and environmental conditions.
Canine Research and Development (R&D) Structure and Function - understanding of canine behavior, genetics, olfaction, and cognition to improve operational efficiencies and training methods.
Development and Testing of Canine Training Aids - targeting the creation of low cost, non- hazardous emerging threat and conventional explosive training aids, with state-of-the-art laboratory technology for odor validation.
Specific Technical Skills:
Counter-UAS (C-UAS)RF Signal ProcessingAutonomous NavigationSensor FusionBaggage Screening SystemsOn-Person ScreeningCanine OlfactionAnimal BehaviorGeneticsOperational Test & Evaluation
Potential PIs for this Area:
Name
Score
Organization
Emil Rofors
0.68
PSA | NSD | ANP
Shawn Tornga
0.68
LD | LD | ONHS
Jennifer Stokes-Draut
0.67
ETA | Energy Analysis & Environmental Impacts | Sustainable Energy Dept
Gazi Mahmud
0.66
BSA | Environmental Genomics & Systems Biology | Molecular Ecosystems Bio
Edward Bethel
0.66
CSA | SciData | Data Science Research
Andre Santos
0.66
EESA | CESD | Integrated Ecosystem Sciences
Boris Faybishenko
0.66
EESA | EG | Hydrogeology Dept
John Wu
0.66
CSA | Scientific Networking (ESNET) | Tech Adv and Engagement
Hannah Parrilla
0.66
PSA | NSD | ANP
Rohan Adwankar
0.66
BSA | Biological Systems & Engineering | Process Engr & Analytics
Example Priorities:
The research and development of improved models of resilience across networked hardware and software systems and organizations.
Areas of interest include: automated cyber attack design and mitigation technologies; automated mechanisms for sharing mitigation policies and technical solutions across systems and organizational boundaries; resilient machine learning approaches...
The research and development of tools and techniques to ensure the resilience of the data, software, and hardware used to execute homeland security mission functions.
Areas of interest include: novel applications of post quantum cryptography; homomorphic encryption... and supply chain assurance techniques such as software and hardware bill of materials, static and dynamic analysis tools for commercial and open source software, automated secure code development and vulnerability remediation, and integration into DevSecOps pipelines.
Specific Technical Skills:
Cyber ResilienceData-Centric SecurityCyber Physical Systems (CPS)Operational Technology (OT)Post-Quantum CryptographyHomomorphic EncryptionSupply Chain SecuritySoftware Bill of Materials (SBOM)Static/Dynamic Code AnalysisDevSecOps
Potential PIs for this Area:
Name
Score
Organization
Sean Peisert
0.71
CSA | SciData | Data Science Applications
Thomas Hendrickson
0.68
ETA | Energy Analysis & Environmental Impacts | Sustainable Energy Dept
Anand Krishnan Prakash
0.68
ETA | Building Technology & Urban Systems | Bldg Technologies Dept
Alex Newkirk
0.68
ETA | Building Technology & Urban Systems | Bldg & Industrial App Dpt
Tiffany Connors
0.67
CSA | NERSC | Data Center Department
Gazi Mahmud
0.67
BSA | Environmental Genomics & Systems Biology | Molecular Ecosystems Bio
Jeetika Malik
0.67
ETA | Building Technology & Urban Systems | Bldg Technologies Dept
Neel Rajeshbhai Vora
0.67
PSA | ATAP | BACI
Sunhee Baik
0.67
ETA | Energy Analysis & Environmental Impacts | Energy Markets & Policy
Hannah Cohoon
0.67
CSA | SciData | Data Science Applications
Example Priorities:
The research and development of creating or enhancing technologies to enable DHS to effectively assess the performance of Artificial Intelligence/Machine Learning (AI/ML) systems against technical and mission metrics, provide operators making critical decisions an appropriate level of trust and confidence...
Develop methods, processes and technologies for explainable AI for mapping AI and ML decision process reasoning to human-understandable terms.
Develop risk analysis framework for malicious or unintentional misuse, accidents, or other errors and failures of AI technology; identifying and managing bias in AI.
This topic focuses on novel computational and analytic methods and capabilities for large-scale data sets for DHS missions.
Quickly producing high fidelity digital twins for critical-infrastructure applications (e.g., power, chemical, water, etc.); new capabilities in privacy enhancing computations that are scalable to DHS operations.
BSA | Biological Systems & Engineering | Department of BioEngineering and BioMedical Sciences · Counter-Unmanned Aircraft Systems
Fundamental Research Exemption (FRE)
International Traffic in Arms Regulations (ITAR) may apply to one or more of the Topics in this announcement. Foreign nationals must meet the requirements for participation set by those regulations, if required.
ONHS Funding Opportunity Report