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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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. 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. 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
  4. 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
  5. 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
  6. Complex Networks for Computational Urban Resilience (CONCUR)

    SBC: PERCEPTRONICS SOLUTIONS, INC.            Topic: ST17C003

    CONCUR develops a computational framework for assessing and characterizing urban environments stability or fragility in response to volatility and stress, identifying specific weaknesses as well as key tipping points which could lead to rapid systemic failure. CONCUR explicitly models urban environments as emergent complex systems, focusing attention on the critical triggers that could lead to rap ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  7. 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 terriblemorbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditionalvaccines have proven to be a huge contribution to public health, they do have some limitations especially in the cont ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  8. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  9. Computational Biology Platform Technology for Cellular Reprogramming

    SBC: IREPROGRAM, LLC            Topic: ST17C001

    Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  10. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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