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Award Data
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.
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Optimizing Human-Automation Team Workload through a Non-Invasive Detection System
SBC: STOTTLER HENKE ASSOCIATES, INC Topic: ST16C003We propose to investigate, in collaboration with MGH Voice Center and Altec, Inc., application of surface electromyography (sEMG) to assessing cognitive workload, strain, and overload. Specifically, sEMG sensors placed on the face and neck will detect emotional/motor responses to workload strain. The proposed effort will build on the substantial sEMG experience of our partner, MGH (including resea ...
STTR Phase II 2018 Department of DefenseDefense Advanced Research Projects Agency -
Human Performance Optimization
SBC: HVMN Inc. Topic: SOCOM17C001During altitude-induced hypoxia, operator cognitive and physical capacity degrades, compromising individual and team performance. Cognitive degradation is linked to falling brain energy levels, increased reliance on anaerobic energy production and lactate accumulation. Ketones are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies demonstrated that ...
STTR Phase II 2019 Department of DefenseSpecial Operations Command -
Computational Biology Platform Technology for Cell Conversion and Differentiation
SBC: IREPROGRAM, LLC Topic: ST17C001Methods 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 II 2019 Department of DefenseDefense Advanced Research Projects Agency -
Human Performance Optimization
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special OperationsForces (SOF)are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S.military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the funct ...
STTR Phase II 2019 Department of DefenseSpecial Operations Command -
Pathogen Classification Tool (PaCT)
SBC: STOTTLER HENKE ASSOCIATES, INC Topic: ST18C002Stottler 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 -
Visual Relative Navigation via Intelligent Ephemeral Relationships (VRNIER)
SBC: TOYON RESEARCH CORPORATION Topic: ST18C006As 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 -
Development of Autonomous Glycemic Control Mechanism for Patients Suffering Glycemic Abnormalities as a Result of Critical Illnesses
SBC: PROFUSA, INC. Topic: ST18C004The 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 -
Cognitive Bias in Online Communication Activities (C-BOCA)
SBC: SOAR TECHNOLOGY INC Topic: N13AT024This effort will analyze publicly available online communication data, uniquely applying empirical results from the cognitive bias literature, to quantify the impact of cognitive biases on exposure to, use of, and propagation of online information. SoarTech, with its partners, will develop and evaluate methods to identify and measure cognitive biases in online information environments. The team wi ...
STTR Phase II 2018 Department of DefenseDefense Advanced Research Projects Agency -
Complex Networks for Computational Urban Resilience (CONCUR)
SBC: Perceptronics Solutions, Inc. Topic: ST17C003CONCUR 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 -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On 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