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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. IA 2: Intent-Capturing Annotations for Isolation and Assurance

    SBC: Immunant, Inc.            Topic: HR001120S0019001

    Software and hardware flaws can be exploited to make programs perform unintended computations or leak sensitive data. We propose to counter these threats by isolating libraries and other program units inside a single process. The developer will insert source-level annotations that i) map code and data units to compartments and ii) capture how each compartment is intended to interact with others, i ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  3. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA18A001

    The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

    STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  4. Visual Relative Navigation

    SBC: TOYON RESEARCH CORPORATION            Topic: ST18C006

    As unmanned aircraft systems (UAS) become more prevalent there is an increasing desire to automate UAS navigation and control. To enable future UASs to perform a wider variety of missions, they must be able to complete autonomous relative navigation to accomplish missions. Current technologies rely heavily on GPS measurements, which are undesirable since GPS signals may be unavailable in many DoD ...

    STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
  5. Large Low-mass Achromatic Metalenses for Visible Imaging

    SBC: NANOHMICS INC            Topic: HR001119S003524

    Nanohmics, teaming with CUNY, proposes to develop high-performance, metamaterial-based lenses that can be scaled up to tens of centimeters of clear aperture for ISR and other imaging applications. These high-throughput achromatic metalenses will operate across all visible wavelengths, 400-700 nm, demonstrating polarization-independent, low-aberration f/2 imaging comparable to much bulkier conventi ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  6. Pathogen Classification Tool (PACT)

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: ST18C002

    Stottler Henke proposes PACT to address the threat posed by unknown/novel bacteria. Stottler Henke’s solution leverages AI/ML technologies to assess the pathogenic potential of unknown/novel bacteria for DARPA’s Biological Technologies Office. Threat assessment is inferred from phenotype as characterized by a series of assays developed by Harvard University as part of DARPA’s Friend or Foe p ...

    STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
  7. SWAT- Scalable W(R)ubber through Advanced Technology

    SBC: EnergyEne Inc.            Topic: ST18C001

    Opportunity: Guayule, a US native plant, is the only alternate rubber crop with an established, mechanized, agronomic system. Problem: Low rubber yields and lack of effective resin and bagasse coproduct valorization, have prevented widespread adoption by American farmers and processors. Rubber is only made when the cytoplasmic monomer pool (isopentenyl-pyrophosphate; IPP) is larger than that requi ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  8. Visual Relative Navigation via Intelligent Ephemeral Relationships (VRNIER)

    SBC: TOYON RESEARCH CORPORATION            Topic: ST18C006

    As unmanned aircraft systems (UAS) become more prevalent there is an increasing desire to automate UAS navigation and control. To enable future UASs to perform a wider variety of missions, the they must be able to complete autonomous relative navigation to accomplish missions. Current technologies rely heavily on GPS measurements, which are undesirable since GPS signals may be unavailable in many ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  9. Development of Autonomous Glycemic Control Mechanism for Patients Suffering Glycemic Abnormalities as a Result of Critical Illnesses

    SBC: PROFUSA, INC.            Topic: ST18C004

    The use of continuous glucose monitors can be an invaluable management tool for patients afflicted by glycemic variability due to critical illness or trauma. Maintaining stable glucose levels enhances health and lowers care costs, and individuals equipped with continuous glucose data have significantly improved outcomes. Profusa has developed highly miniaturized, injectable, tissue-like, glucose s ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  10. Pathogen Classification Tool (PaCT)

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: ST18C002

    Stottler Henke proposes PaCT, leveraging our related past work in computer vision and machine learning. Drawing from techniques used in ExPATSS, a Phase II SBIR effort slated for transition to the Naval fleet, PaCT will perform bacterial characterization using features derived from the phenotype of the bacteria. PaCT will predict bacterial characteristics such as pathogenicity, antibiotic resistan ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
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