Project Grant 2538522
- Federal Grant Award Summary The National Science Foundation (NSF) Directorate for Engineering awarded $224,996 to the New Jersey Institute of Technology (NJIT) on July 1, 2026, for a collaborative research project titled "Reinforcement Learning with High-Probability Safety Constraints: Theory, and Applications" (CFDA 47.041). The three-year project, concluding June 30, 2029, will deliver foundational theory, algorithms, and software tools that enable safe reinforcement learning (RL)...
- Federal Grant Award Summary The National Science Foundation's Division of Computer and Network Systems awarded a $450,000 Project Grant to the New Jersey Institute of Technology on May 15, 2026, under the Computer and Information Science and Engineering (CFDA 47.070) program. The project, titled "SATC: CORE: SMALL: Improving the Security of Large Language Model-Assisted Coding," will deliver research and development solutions to address security vulnerabilities in code generated by...
- Federal Grant Award Summary Award Title: Collaborative Research: SHF: Small: Scalable Algorithmic and Software Foundations for Subgraph Counting and Enumeration Funding Agency and Program: National Science Foundation (NSF), Division of Computing and Communication Foundations, Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Award Details: $270,000 | July 1, 2025 – June 30, 2028 New Jersey Institute of Technology will develop advanced computational methods and...
- Federal Project Grant Award Summary The National Science Foundation's Division of Computer and Network Systems awarded a CAREER grant of $395,842 to Princeton University effective August 1, 2025, through July 31, 2030, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The project delivers research and development services focused on enhancing the reliability and robustness of machine learning (ML) systems deployed in critical networking functions, such as...
- Federal Project Grant Award Summary Princeton University received a $295,099 Project Grant from the National Science Foundation (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025, through September 30, 2029. This collaborative research initiative focuses on developing theoretical foundations and algorithmic solutions for graph problems using quasi-polynomial time...
- Federal Grant Award Summary Rutgers, The State University received an $850,000 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), effective July 1, 2026 through June 30, 2030. The award funds research to develop an output-sensitive algorithm for efficient convex hull computation in high dimensions, addressing a critical computational bottleneck in formal...
- Project Grant Summary The New Jersey Institute of Technology received a $180,000 project grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for research on the dynamics of high-dimensional complex networks. The project, awarded September 1, 2025, with completion expected by August 31, 2028, will deliver rigorous mathematical characterizations of how microscopic interactions in large stochastic particle...
- Federal Project Grant Award Summary New York University received a $370,237 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), effective January 1, 2026 through June 30, 2028. This collaborative research initiative focuses on developing fast combinatorial algorithms for graph problems, specifically addressing maximum matching, maximum flow, and shortest path...
- Federal Grant Award Summary New York University received a $249,899 Project Grant from the National Science Foundation (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), awarded December 1, 2025, with completion targeted for September 30, 2026. The project, titled "SMALL: Towards New Relaxations for Online Algorithms," develops general-purpose algorithmic solutions for sequential decision-making...
- Federal Project Grant Award Summary The University of Michigan, Office of Research and Sponsored Projects, received a $150,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded on August 15, 2025, with completion targeted by July 31, 2028. The award supports fundamental research on robust data-driven decision-making systems that integrate human-AI alignment with algorithmic...
The National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) awarded New Jersey Institute of Technology a $350,355 Project Grant effective September 1, 2026, through August 31, 2031, to develop algorithmic frameworks for reliable online decision-making in automated systems. The project delivers a theoretical and practical framework for parameterized robustness that addresses real-world constraints often overlooked in traditional algorithm analysis. Key deliverables include: parameter-dependent analyses that characterize algorithm performance guarantees as functions of realistic structural factors such as bounded connectivity and constrained value ranges; a smoothed competitiveness framework for evaluating algorithms under structured stochastic environments; research on algorithms that integrate machine learning predictions while maintaining robustness when predictions are inaccurate; and variance-based analysis to quantify algorithm stability in digital platforms. These research products directly advance the reliability, stability, and transparency of automated decision systems deployed in contemporary digital platforms—including ride-hailing matching, online labor market task assignment, search engine advertisement allocation, and digital marketplace selection mechanisms. The work bridges the gap between theoretical algorithm design and practical deployment by developing analysis methodologies that account for geographic, market design, and behavioral constraints inherent in real systems, thereby producing more dependable algorithmic principles for resource allocation and online decision-making in operational environments.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $350.4k | 5/13/26 |