Project Grant 2543660
- Federal Project Grant Award Summary The University of Pennsylvania received a $400,807 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070), effective June 1, 2026 through May 31, 2031. This CAREER award supports research to develop design patterns, interaction techniques, and software toolkits that enhance the comprehension of scientific notation, equations, and formal proofs through interactive digital engagement. The...
- Federal Grant Award Summary The Pennsylvania State University received a $379,224 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective July 15, 2025, with completion by June 30, 2030. This CAREER award funds research to develop privacy auditing frameworks and defensive mechanisms for machine learning (ML) models trained on tabular data. The...
- Federal Project Grant Award Summary The Pennsylvania State University received a $100,000 Project Grant award dated July 15, 2025, from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The project, titled "Accelerating LLM Safety Research with Self-Evolving Evaluation Infrastructure," aims to develop an open, community-driven evaluation framework to assess Large Language...
- Federal Grant Award Summary The Pennsylvania State University received a $115,380 Project Grant from the National Science Foundation's Division of Undergraduate Education under the STEM Education program (CFDA 47.076), effective July 1, 2025, through June 30, 2028. This Level 2 Engaged Student Learning project builds upon a prior prototype to develop and enhance the Automated Feedback for Computing Theory (AFCT) tool, which provides immediate feedback to students designing computational models...
- Federal Project Grant Award Summary The Pennsylvania State University received a $685,588 Project Grant award, effective July 1, 2026 through June 30, 2031, from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This CAREER award supports the development of artificial intelligence techniques, specifically scaling deep reinforcement learning (DRL) methodologies, to optimize the...
- Federal Project Grant Award Summary The Pennsylvania State University received a $250,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) effective August 1, 2025, through July 31, 2028, to develop and deliver a comprehensive cybertraining program addressing the security vulnerabilities associated with Large Language Models (LLMs) in advanced cyberinfrastructure systems. The project delivers a structured educational...
- Federal Grant Award Summary The Pennsylvania State University received a $199,444 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), effective October 1, 2025, with completion scheduled for September 30, 2027. This Engineering Research Initiation (ERI) award supports the development of retrieval-augmented generation (RAG)-empowered extended reality (XR) systems that integrate large language...
- Federal Grant Award Summary The Pennsylvania State University received a $167,000 Project Grant award dated October 1, 2025, from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This collaborative research project, scheduled for completion by September 30, 2028, develops an information-theoretic framework for creating explainable and trustworthy Graph Neural Networks (GNNs)....
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computer and Network Systems awarded the University of Maryland, College Park a Project Grant of $331,428 (CFDA 47.070 – Computer and Information Science and Engineering) commencing October 1, 2025, with a completion date of September 30, 2030. This CAREER award supports research focused on secure code generation with large language models (Code LLMs), addressing critical security vulnerabilities in AI-driven...
- Federal Grant Award Summary Rutgers, The State University received a $344,821 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) beginning June 1, 2026 through May 31, 2031. This CAREER award supports foundational research on memory-constrained machine learning, addressing a critical gap in theoretical computer science regarding the memory requirements for...
The Pennsylvania State University received a $424,193 Project Grant award 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 June 1, 2026, through May 31, 2031. This CAREER award supports research to develop grid-based code representations that enable blind and low-vision (BLV) individuals to access and participate in programming through existing assistive technologies such as screen readers. The primary deliverables include the creation of new program representation methodologies, accessible programming tools, and educational materials that will be made widely available to increase BLV participation in programming-related employment and education. The project centers on two main research objectives. The first aim, Grid-Coding, transforms source code into an explicit two-dimensional grid structure where rows represent code lines, columns represent scope, and spacing becomes meaningful structural information. This representation supports non-traditional navigation strategies including right-to-left, bottom-up, and level-based traversal, enabling learners to inspect code hierarchy through multiple pathways, recognize code patterns, identify code quality issues, and utilize padding cells as active learning surfaces for hints and annotations. By addressing the loss of visual information when code representations are converted to linear synthesized speech, this research will advance inclusive programming education and workforce development for individuals with visual disabilities.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $424.2k | 4/17/26 |