Cooperative Agreement 2026404

Semiotic AI, Inc. received a $256,000 Small Business Innovation Research Phase I Project Grant from the National Science Foundation to accelerate machine learning on encrypted data from July 1, 2021 to March 31, 2022. Funded through the NSF's Engineering program (CFDA #47.041), which seeks to improve quality of life and economic strength through engineering innovation and excellence, the project aims to develop techniques that enable machine learning to be performed directly on encrypted data...

This SBIR Phase II Cooperative Agreement award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $1,250,000 to Crypto Tutors LLC, a SBA-certified economically disadvantaged women-owned small business, to develop an AI-enhanced career assessment tool that will accelerate student and professional access to emerging technologies in Web3. The goal is to create new career pathways that empower individuals to enter high-demand industries like...

This Project Grant award of $250,924 from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports early-concept research on a private blockchain-enabled federated learning framework for distributed manufacturing networks. The framework aims to enhance the resiliency, transparency, and cybersecurity of global manufacturing networks, particularly for small and medium-sized manufacturers, by enabling secure and private data sharing and collaboration through blockchain and...

This $255,837 National Science Foundation project grant funds the development of a blockchain-driven, distributed memory computational platform for industrial analytics by Blockalytics LLC. The platform will enable predictive analytics on geographically distributed industrial data without data movement or reliance on cloud-based solutions. Blockalytics will integrate blockchain smart contracts with distributed memory frameworks to design primitives similar to MapReduce for blockchain and develop...

This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $291,703 to the Regents of the University of Minnesota to accelerate the development of practical and scalable privacy-preserving machine learning (ML) solutions. The project aims to create efficient, crypto-friendly neural architectures and algorithm-hardware co-design methodologies to significantly speed up privacy-preserving ML on hardware platforms like...

This $1,000,000 cooperative agreement from the National Science Foundation (NSF) will fund the development of a blockchain ecosystem and artificial intelligence to optimize prior authorization processes in the pharmaceutical industry. Red Oak Strategic LLC will leverage distributed ledger technology to create an encrypted, decentralized patient data sharing network among prescribers, payers, and patients. Smart contracts will automate criteria fulfillment, facilitate machine learning-based...

This Project Grant award of $600,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will develop a hybrid solution that integrates multi-party computing (MPC) and specialized secure hardware to enable secure and efficient artificial intelligence (AI) offloading for user privacy protection. The project aims to address the privacy risks associated with users sharing sensitive data, such as resumes or biomedical signals, with AI...

Moka Blox LLC received a $255,916 Project Grant award from the National Science Foundation under the Engineering federal grant program (CFDA 47.041) to develop a distributed ledger technology machine learning platform for blockchain warehousing. The award aims to create a new framework to overcome limitations in centralized data storage, homogeneous data formats, and tightly coupled workflows that challenge large-scale databases and data warehouses used in applications such as machine learning...

This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) to Texas A&M University-Central Texas, totaling $349,009, aims to develop a database architecture that integrates privacy regulations and compliance processes with artificial intelligence (AI) and machine learning (ML) workflows. The key objectives of this 3-year project are to: (1) create a database system that coordinates data privacy policies, AI/ML processes, and...

This Project Grant award of $432,485 from the National Science Foundation (CFDA 47.070 Computer and Information Science and Engineering) to the University of Maryland Baltimore County aims to address challenges in integrating confidential computing into scientific workflows. The key products and services to be delivered under this award include: A scientist-friendly development framework for confidential computing to enable domain scientists to easily adopt best practices in confidential...