Project Grant 2348330
- This Project Grant award of $300,000.00 from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure supports the development of a novel zero-trust and traceable data-sharing infrastructure called WEB3DB. The project aims to address limitations of the current centralized data ecosystem by empowering individuals to control and manage access to their personal health IoT data. Key research outcomes include: (1) novel decentralized identity management and access control...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program project grant award (CFDA 47.070) provides $249,867 to New York University (NYU) from October 1, 2023 to September 30, 2027. Under this award, NYU will develop a prototype distributed database called VDDB and a new verification framework called PHLOX to formally specify and verify the correctness of VDDB. The goal is to demonstrate the feasibility of using formal verification to improve the...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) project grant (CFDA 47.070) awarded $160,493 to the Georgia Tech Research Corporation to conduct collaborative research at the intersection of distributed cryptography and blockchain technologies. The key objectives are: (1) developing a common framework and language to bridge the gap between cryptography and distributed computing research on emerging technologies like blockchain; (2) investigating the...
- 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 of $500,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the development of scalable software to enable "data polymorphism" - a novel paradigm for fast and adaptable scientific data retrieval with reduced data movement costs. The project aims to bridge the gap between the vast amounts of data generated by scientific simulations/instruments and the limited...
- The Research Foundation For The State University Of New York (SUNY at Binghamton) received a $100,000 Project Grant award from the National Science Foundation Division of Information and Intelligent Systems to support research activities under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will fund work on decentralized data assurance through fair proof of work consensus federated ledgers from October 1, 2021 to September 30, 2022. The...
- This Project Grant award of $299,999 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development and optimization of a log-structured-merge tree-based key-value store system called Decoupled-LSM. The project aims to redesign the architecture of this critical data storage system to improve performance, resource utilization, and manageability within disaggregated computing infrastructures, which are...
- This $599,996 National Science Foundation project grant supports research at Augusta University Research Institute, Inc. to develop new techniques for securely querying massive scientific datasets in cloud environments. Specifically, the grant funds research to extend the state-of-the-art in encrypted data querying methods to better support the distinct characteristics of scientific data and typical queries. Key areas of focus include developing new encryption and query processing techniques...
- This National Science Foundation Project Grant of $600,000 supports research to improve the performance of database management systems that use log structured merge tree storage technology. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the award will support development of novel data organization and flow patterns within log structured merge tree storage to boost read and write capabilities. Key activities include designing algorithms to store...
- This $256,710 National Science Foundation award under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project led by the University of Texas at Austin. The project investigates full-stack implementation methodologies for developing expressive programming systems that bridge the gap between high-level specifications and high-performance implementations of complex reasoning tasks at scale. Key focus areas include extending declarative...
This Project Grant award in the amount of $165,000, provided by the National Science Foundation (NSF) under its Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to enhance eventual data consistency in large-scale, multidimensional scientific computing through the development of a lightweight in-memory distributed ledger system. The project, led by Augusta University Research Institute, Inc. (dba Georgia Health Sciences), a non-profit research organization, will focus on two core modules: refining data modeling strategies to optimize workload distribution, and establishing a scalable in-memory distributed ledger for improved caching and processing efficiency. This interdisciplinary research, spanning distributed databases, systems, and high-performance computing, is expected to advance scientific research and data management practices, particularly for complex, large-scale datasets. The award has a period of performance from April 1, 2024 to March 31, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $165.0k | 12/30/23 |