You are here
The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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.
SBC: TRITON SYSTEMS, INC. Topic: A18BT022
The U.S. Army routinely deploys personnel in malaria-endemic regions as part of normal operations. Preventative measures to malaria infection include a highly-effective daily oral prophylactic antibiotic which is provided to personnel prior to deployment. However, due to side effects including nausea and photosensitivity coupled with organizational culture, poor adherence to the prescribed regimen ...STTR Phase I 2019 Department of DefenseArmy
SBC: TRITON SYSTEMS, INC. Topic: A18BT025
Triton Systems Inc. will work in collaboration with an academic partner to develop a model for a system to dynamically calculate the Center of Gravity (CoG) of a wheeled Squad Multipurpose Equipment Transfer (SMET) vehicle. The Army has tested several SMET vehicles of varying widths and heights and arrived at the conclusion that they ALL roll over, particularly if the vehicle is traversing the ter ...STTR Phase I 2019 Department of DefenseArmy
SBC: SC SOLUTIONS, INC. Topic: A18BT011
In this Small Business Technology Transfer (STTR) Phase I project, SC Solutions, teaming with Sandia National Laboratories (SNL), will demonstrate the feasibility of a scalable Quantum Computing Validation & Verification (QCVV) tool that will allow quantum computing researchers to rapidly and conveniently test and benchmark their quantum computing systems. While several QCVV techniques have been d ...STTR Phase I 2019 Department of DefenseArmy
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared ImagerySBC: 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
SBC: PATHOVACS INCORPORATED Topic: CBD18A001
The focus of this STTR phase I component is on proof-of-concept studies demonstrating applicability of technical approaches for identificationof circulatory diagnostic markers for infectious disease. Therefore, the primary objective of this project is to determine feasibility of one suchtechnical approach called Proteomics-based Expression Library Screening (PELS), for identification of pathogen-d ...STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
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
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
SBC: Systems & Technology Research LLC Topic: SOCOM18A001
Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...STTR Phase I 2018 Department of DefenseSpecial Operations Command
SBC: MUKH Technologies LLC Topic: SOCOM18A001
Recognizing faces in low-light and nighttime conditions is a challenging problem due to the noisy and poor quality nature of the images.Thermal imaging is often used to obtain facial biometric in such conditions. Thermal face images, while having a strong signature at nighttime, are not typically maintained in biometric-enabled watch lists and so must be compared with visible-light face images to ...STTR Phase I 2018 Department of DefenseSpecial Operations Command
SBC: HVMN Inc. Topic: SOCOM17C001
In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...STTR Phase I 2018 Department of DefenseSpecial Operations Command