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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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.

  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. Automated In-situ Large-area De-processing of ICs with High Throughput

    SBC: MICRONET SOLUTIONS INC.            Topic: DMEA18B001

    Phase II is the continuing effort to demonstrate the feasibility of producing an automated delayering and imaging system with end point detection, material density detection with built in neural network error correction. This process, coined fast Automated Delayering-Image Capture System (ADICS) leverages off of the existing Pix2Net which is a proven automated imaging 3D microchip reconstruction s ...

    STTR Phase II 2020 Department of DefenseDefense Microelectronics Activity
  3. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Through this STTR contract, we propose to evaluate the efficacy of our vaccine, FlowVax Marburg, in nonhuman primates (NHPs). This will be achieved through four Tasks. In Task 1, we will manufacture the vaccine in a quantity sufficient for the animal studies. In Task 2, we will perform MHC genotyping on a representative population of NHPs and, based on results, select a set of MHC-matched NHPs for ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  4. Marburg Virus Prophylactic Medical Countermeasure

    SBC: MAPP BIOPHARMACEUTICAL, INC.            Topic: CBD18A002

    There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  5. 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
  6. ACADIANA (Annotating Code for Assured Data Intent to Avoid Novel Attacks)

    SBC: ASSURED INFORMATION SECURITY, INC.            Topic: HR001120S0019001

    In the ACADIANA effort we will address the inability of modern programming language, operating system, and architectural abstractions to provide a baseline level of adequate confidentiality protections.  Until now, developers and users of software have largely relied on their programming language and operating system to ensure that confidential data isn’t leaked out of a process’ memory space ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  7. 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
  8. 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
  9. Sparse Information Orbit Estimation for Proliferated LEO

    SBC: A-TECH CORPORATION            Topic: HR001119S003522

    Texas A&M University (TAMU) and Applied Technology Associates (ATA) propose to develop and characterize a set of orbit determination and estimation algorithms for closely-spaced objects in low Earth orbit. The algorithms will span existing state-of-the-art-in-practice and possible state-of-the-art-in-research approaches. These algorithms will seek to extract maximal information out of existing spa ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  10. Sparse Information Orbit Estimation for Proliferated LEO

    SBC: TAU TECHNOLOGIES LLC            Topic: HR001119S003522

    The current Space Surveillance Network (SSN) is projected to soon be unable to track all manmade Low Earth Orbit (LEO) objects at the current rate of observation. Very large constellations of satellites will exponentially grow the number of LEO objects, and simply adding more sensors to the SSN to keep pace with the proliferation in LEO is a cost-prohibitive proposition. This research proposes to ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
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