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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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. Aberration-correcting Topologically Optimized Metasurface (ATOM)

    SBC: Physical Sciences Inc.            Topic: HR001119S003524

    Metalenses, with their ability to arbitrarily control the amplitude and phase of light across a band of wavelengths, have the potential to disrupt imaging and communication systems which rely on traditional lenses to focus, collimate, and otherwise manipulate optical signals, and are under increasing pressure to operate with reduced size and weight. We propose to design, develop, and demonstrate a ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  2. 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
  3. Adaptive Distributed Allocation of Probabilistic Tasks (ADAPT II)

    SBC: APTIMA INC            Topic: A18BT007

    The future success of military teams operating in dynamic and uncertain environments will require the incorporation of artificial intelligence (AI) to help structure those teams, create plans of actions, execute those plans, and adapt plans as the environment and goals change. Successfully combining human of AI team members can achieve better results than either could on their own, but an uninform ...

    STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
  4. Context-driven Active-sensing for Repair Tasks II (CART II)

    SBC: DYNAMIC OBJECT LANGUAGE LABS, INC.            Topic: ST14B003

    Existing machine perception systems are too inflexible, and are not robust enough to environmental uncertainty. In existing systems, perception components are statically (and manually) configured to process sensor data. The parameters of components in such a system are also statically tuned to operate optimally under very specific conditions. Information flow in such systems is bottom up, and gene ...

    STTR Phase II 2016 Department of DefenseDefense Advanced Research Projects Agency
  5. Development of an Autonomous Glycemic Control Mechanism for Patients Suffering Glycemic Abnormalities as a Result of Critical Illnesses

    SBC: Beta Bionics, Inc.            Topic: ST18C004

    It is well established that hyperglycemia of critical illness, general glucose intolerance, and insulin resistance are common among critically ill patients, including those without a diagnosis of diabetes mellitus upon hospital admission. Such glycemic dysregulation has been linked to increased patient morbidity and mortality, and longer recovery times. Furthermore, tight glycemic control has been ...

    STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
  6. Human-Machine Teaming with Machine Learning Algorithms

    SBC: KITWARE INC            Topic: SOCOM18B001

    Characterizing and understanding the interactions between human and machine plays an important role in extracting the most out of our machine learning algorithms while reducing human workload. We propose to develop a software prototype system that reduces user workload of exploiting AI algorithms for imagery exploitation. We will design a user-friendly system for content matching with interactive ...

    STTR Phase II 2020 Department of DefenseSpecial Operations Command
  7. Hybrid Analog-Digital Co-Processor for Scientific Computation

    SBC: ALLEGORY LABS LLC            Topic: ST15C002

    We propose to use a hybrid analog-digital electronic computer to solve partial differential equations (PDEs) arising in scientific simulations and high performance computing (HPC). The simulation of PDEs has extensive applications in commerce, research, and defense. Analog computation potentially decreases the time and energy needed to reach a solution by providing an ability to carry out iterativ ...

    STTR Phase I 2016 Department of DefenseDefense Advanced Research Projects Agency
  8. Memristor-CMOS Analog Co-Processor for Efficient Computation of PDEs

    SBC: SPERO DEVICES, INC.            Topic: ST15C002

    Spero Devices is proposing design of a memristor-CMOS co-processor to implement analog Discrete Fourier Transforms (DFTs). The analog co-processor invokes spectral methods to solve a class of linear and non-linear partial differential equations (PDEs) arising in the scientific simulation of complex systems. Current PDE solution methods are inefficient and often intractable due to limitations assoc ...

    STTR Phase I 2016 Department of DefenseDefense Advanced Research Projects Agency
  9. Patterned, Responsive Cellular Therapies Using Novel Mammalian Cellular Regulator Systems

    SBC: General Biologics, Inc.            Topic: HR001119S003516

    We propose to design, build and test genetic circuits and DNA constructs that will be expressed in human cells and that will ultimately have applications for the health of warfighters. The circuits will have physiological inputs representing, for example, (1) infection/sepsis, (2) altitude sickness or blood loss, and (3) radiation exposure; which will be mediated through signal transduction pathwa ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  10. REsilience & Stability In DENse Terrains (RESIDENT)

    SBC: BOSTON FUSION CORP            Topic: ST17C003

    Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-modal, multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematica ...

    STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
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