ONHS Report: IARPA-OT-26-001

IARPA Solutions Marketplace

Solicitation ID: IARPA-OT-26-001

Agency: IARPA

Type: Special Notice

Deadline: 2027-07-31T16:00:00 ET

Eligibility: Maybe (OTA/Consortium)

Funding: N/A

Doc Type: BAA

Clearance: Maybe (Info Requested)

Program Manager: success@iarpamarketplace.us

Last Updated: 2026-07-17 16:03

Analyzed File: IARPA Announcement v1 August 2026C.pdf

Eligibility Reasoning

All US-based companies, traditional and nontraditional, large business and small business, new entrants, universities, non-profit companies, and individuals are welcome to participate... all submitted solutions that are deemed “awardable” by the Government Selecting Official (GSO) will be considered “post-competitive” pursuant to 50 U.S.C. § 3024(m)(6) (including exercise of 10 USC 4021, 10 USC 4022, and 10 USC 4022(f) authorities).

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

Summary

The Intelligence Advanced Research Projects Activity (IARPA), in partnership with The Applied Research Institute (ARI), manages the IARPA Solutions Marketplace, an open-call initiative for the Intelligence Community (IC). This program solicits solutions through a submission process requiring a 5-minute unclassified video pitch and a 5-slide package. Submissions are collected monthly and must address strategic focus areas including Secure Communications, Cyber and AI Security, Automating R&D, Biometric Recognition, or other IC-relevant topics. A peer panel of experts assesses submissions for technical merit, mission impact, and other criteria. Solutions deemed 'awardable' are placed in a digital marketplace for up to 24 months, making them eligible for rapid, post-competition acquisition by IC and other federal agencies. The program is open to a wide range of participants, including US and foreign entities, and provides feedback for non-awardable submissions to encourage resubmission.

Overall Technical Areas

Secure Communication ProtocolsAnonymous Data TransmissionLow Probability of Detection SystemsAdversarial AI DefenseAutonomous Cyber DefenseAI Model SecuritySecure Federated LearningAI-driven Vulnerability ManagementAutomated Test and EvaluationMultimodal Biometric RecognitionPrivacy-Enhancing TechnologiesBiometric Anti-SpoofingReal-time Speech AnonymizationStylometric Analysis and AnonymizationAI Red Teaming

Probable LBNL Areas

BSACSAEESAESAETA

Focus Areas

Example Priorities:

implementing non-attributable and secure communications between groups and individuals
allow users to transmit information anonymously, securely and with a low probability of detection
provide robust security measures to protect data and prevent tracking and monitoring of user activity, while also avoiding detection of security measures

Specific Technical Skills:

Secure CommunicationsCryptographyNetwork SecurityMobile SecurityLow Probability of Detection (LPD)Anonymity NetworksNon-attributable CommunicationsAnti-tracking TechnologiesCommodity Hardware IntegrationSecure Two-Way Communications

Potential PIs for this Area:

Name	Score	Organization
Christopher Tracy	0.70	CSA \| ESNET \| Tech Adv and Engagement
Amir Kamil	0.69	CSA \| AMCR \| Computer Science
Jason Lowe-Power	0.69	CSA \| SciData \| Data Science Applications
Prabal Dutta	0.69	ETA \| Building Tech. & Urban Sys. \| Bldg Technologies Dept
Dipak Ghosal	0.68	CSA \| ESNET \| Tech Adv and Engagement
Venkatesh Akella	0.68	CSA \| SciData \| Data Science Applications
Sung-Joo Yoo	0.68	CSA \| ESNET \| Tech Adv and Engagement
Zhi Yao	0.68	CSA \| AMCR \| Applied Mathematics
Michael Dopheide	0.68	CSA \| ESNET \| Security
Zhi Jackie Yao	0.67	CSA \| AMCR \| Applied Mathematics

Example Priorities:

prevent adversarial subversion and preserve model integrity, such as techniques for data poisoning detection, run-time evasion defense, and protection of model architecture and weights from distillation or unauthorized access
counter autonomous cyber operations, such as capabilities for polymorphic threat neutralization, detection of sophisticated phishing with synthetic content, and agentic cyber defense mechanisms
secure AI supply chain and infrastructure, such as methods for tamper-proof chain of custody in training routines, protection of compute clusters from advanced physical-layer threats, and federated learning to protect privacy sensitive data
ensure AI governance and policy enforcement, such as guardrail technology to provide oversight, provable containment, and operational trust

Specific Technical Skills:

AI SecurityAdversarial Machine LearningCybersecurityData Poisoning DetectionAutonomous Cyber OperationsAI GovernanceFederated LearningAI Red TeamingModel Integrity ProtectionAI Supply Chain Security

Potential PIs for this Area:

Name	Score	Organization
Steven Hofmeyr	0.68	CSA \| AMCR \| Computer Science
Anna Giannakou	0.68	CSA \| SciData \| Data Science Applications
Aditi Krishnapriyan	0.67	CSA \| AMCR \| Computer Science
Cary Whitney	0.67	CSA \| NERSC \| Data Center Department
Jason Lowe-Power	0.67	CSA \| SciData \| Data Science Applications
Lavanya Ramakrishnan	0.67	CSA \| SciData \| Data Science Applications
Arpit Gupta	0.67	CSA \| ESNET \| Tech Adv and Engagement
Satyarth Praveen	0.66	CSA \| SciData \| Data Science Applications
Ana Kupresanin	0.66	CSA \| Computing
Charuleka Varadharajan	0.66	EESA \| EG \| Geochemistry Dept

Example Priorities:

solutions addressing administrative and operational bottlenecks commonly associated with Federal research and development
automate the Test & Evaluation cycle
monitor and assess technical, programmatic, and financial health of research portfolios
automate the declassification and sanitization of information for public consumption

Specific Technical Skills:

Business Process AutomationNatural Language Processing (NLP)Program Management SoftwarePortfolio AnalyticsAutomated Technology AssessmentAutomated Test and EvaluationAcquisition Process AutomationInformation DeclassificationScientific Impact TrackingFinancial Health Monitoring

Potential PIs for this Area:

Name	Score	Organization
Anna Giannakou	0.68	CSA \| SciData \| Data Science Applications
Oluwamayowa Amusat	0.68	CSA \| SciData \| Data Science Applications
Silvia Crivelli	0.68	CSA \| AMCR \| Computer Science
Eric Pouyoul	0.67	CSA \| ESNET \| Tech Adv and Engagement
Cary Whitney	0.67	CSA \| NERSC \| Data Center Department
Han Li	0.67	ETA \| Building Tech. & Urban Sys. \| Bldg Technologies Dept
Joshua Apte	0.67	ETA \| Energy Analysis \| Systems & Energy Tech Analysis
Kirch Czarina Quijano	0.67	BSA \| Biological Systems & Engineering \| Process Engr & Analytics
Ta-Hsuan Chang	0.67	BSA \| Biological Systems & Engineering \| Process Engr & Analytics
Jenny Duong	0.67	BSA \| Biological Systems & Engineering \| Process Engr & Analytics

Example Priorities:

reliably recognize individuals in unconstrained, multimodal data (imagery, video, text, audio, etc.) while simultaneously deploying robust privacy-enhancing technologies to mask, anonymize, and protect identities
identify individuals in unconstrained imagery or video where traditional facial recognition is not possible
detect attempts to spoof recognition systems, both with synthetic content and physical measures
anonymize speech in real-time

Specific Technical Skills:

Biometric RecognitionComputer VisionPrivacy-Enhancing Technologies (PETs)Multimodal Data AnalysisFacial RecognitionSpeaker RecognitionAuthorship AttributionAnti-spoofingData AnonymizationSpeech Anonymization

Potential PIs for this Area:

Name	Score	Organization
Hang Chang	0.67	BSA \| Biological Systems & Engineering \| Department of BioEngineering and BioMedical Sciences
Lavanya Ramakrishnan	0.67	CSA \| SciData \| Data Science Applications
Anna Giannakou	0.67	CSA \| SciData \| Data Science Applications
Xiaoya Chong	0.66	ESA \| ALS \| PS Computing staff
Gilberto Pastorello	0.66	CSA \| SciData \| Data Science Applications
Dmitriy Morozov	0.66	CSA \| AMCR \| Computer Science
Tanny Andrea Chavez Esparza	0.66	ESA \| ALS \| PS Computing staff
Arpit Gupta	0.66	CSA \| ESNET \| Tech Adv and Engagement
Steven Hofmeyr	0.66	CSA \| AMCR \| Computer Science
Ben Erichson	0.66	CSA \| SciData \| Data Science Research

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
Koushik Sen	0.75	CSA \| AMCR \| Computer Science · Automated Test and Evaluation
Daniel Arnold	0.73	ETA \| ESDR \| Energy Storage & Dist Dpt · Adversarial AI Defense
Dipak Ghosal	0.72	CSA \| ESNET \| Tech Adv and Engagement · Anonymous Data Transmission
Tiffany Connors	0.72	CSA \| NERSC \| Data Center Department · Autonomous Cyber Defense
Vern Paxson	0.72	CSA \| SciData \| Data Science Applications · Stylometric Analysis and Anonymization
Alexandre Bayen	0.72	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Low Probability of Detection Systems
Suren Byna	0.71	CSA \| SciData \| Data Science Research · Real-time Speech Anonymization
Abdelilah Essiari	0.71	CSA \| SciData \| Data Science Applications · Secure Communication Protocols
Sean Peisert	0.71	CSA \| SciData \| Data Science Applications · Privacy-Enhancing Technologies
Satyarth Praveen	0.70	CSA \| SciData \| Data Science Applications · Multimodal Biometric Recognition

Fundamental Research Exemption (FRE)

In addition, foreign universities, research institutions, and entities may submit video pitches for their related solutions provided that such submissions are compliant with international law, including export laws for both the country of origin of the technology provider and the United States.