Project Grant 2542188
- Federal Project Grant Award Summary Purdue University received a $357,921 CAREER Project Grant from the National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070: Computer and Information Science and Engineering) effective July 1, 2026, through June 30, 2031. The award funds research and development of algorithmic advances in structure-aware learning that enhance artificial intelligence (AI) system reliability, data efficiency, and safety. The primary...
- Federal Project Grant Award Summary The National Science Foundation (NSF), Division of Information and Intelligent Systems, is awarding $866,530 to Purdue University under the Computer and Information Science and Engineering program (CFDA 47.070) for a four-year project running from September 1, 2026, through August 31, 2030. The project will develop foundational advances in type-based reasoning methods that integrate both over-approximate and under-approximate verification techniques to enhance...
- Federal Project Grant Award Summary Purdue University received a $401,546 CAREER award from the National Science Foundation's Division of Information and Intelligent Systems (Computer and Information Science and Engineering, CFDA 47.070) effective June 1, 2026, through May 31, 2031. The project, "PTM-SEER: Software Engineering Foundations for Re-Using Pre-Trained Neural Models," delivers research and practical tools addressing the emerging challenge of reusing and adapting...
- Federal Project Grant Award Summary Purdue University received a $326,628 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant, awarded July 1, 2026, with a completion date of June 30, 2031. This CAREER award supports research on distributed large-scale machine learning (ML) with security guarantees, addressing the concentration of ML development among resource-rich organizations by enabling secure, transparent participation from...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Computing and Communication Foundations, awarded Purdue University a $339,075 Project Grant (CFDA 47.070, Computer and Information Science and Engineering) effective August 1, 2026, through July 31, 2031. This CAREER award supports the development of data-centric vision models that enhance the interpretability, accountability, and maintainability of computer vision systems. The research addresses limitations of...
- Federal Project Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a CAREER grant totaling $396,112 to the University of Massachusetts Amherst on July 1, 2026, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This five-year project, extending through June 30, 2031, develops practical formal specification methods to improve software reliability and AI-driven autonomous systems. The award funds...
- Federal Project Grant Award Summary Purdue University received a $600,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) effective August 1, 2025, through July 31, 2028. The award funds research and development of gradient-based discrete Markov Chain Monte Carlo (GD-MCMC) algorithms designed to improve sampling efficiency and statistical reliability for machine...
- 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 Project Grant Award Summary The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a five-year CAREER grant totaling $424,806 to the University of Michigan, effective May 1, 2026 through April 30, 2031, under the Computer and Information Science and Engineering program (CFDA 47.070). The project delivers domain-specific programming languages and embedded verification libraries for mathematical proof of correctness and security in parsing systems....
- Federal Project Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a $366,820 CAREER Project Grant to Purdue University (Award Date: July 1, 2026; Completion Date: June 30, 2031) under the Computer and Information Science and Engineering program (CFDA 47.070). The award funds research and development of efficient and scalable neuro-symbolic cognitive computing platforms on three-dimensional (3D) integrated circuits and systems. The...
Purdue University received a $391,123 CAREER award from the National Science Foundation (NSF), Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), with performance period September 1, 2026 through August 31, 2031. The project delivers research and development of novel formal methods techniques and a general-purpose framework designed to help software developers rigorously examine and understand the behavior of potentially flawed programs, particularly those generated by large language models (LLMs). The core technical innovation involves developing underapproximate refinement types—a new type abstraction that soundly identifies execution paths leading to errors while pruning irrelevant paths—to enable principled reasoning about incorrect or partially understood programs that existing formal verification tools cannot effectively address. The deliverables support increased trustworthiness and accountability in AI-assisted software development by creating tools that allow developers to confidently explore and understand AI-generated code prior to deployment in safety- and security-critical applications. This addresses the critical gap between LLM code generation capabilities and the rigorous program verification methods currently available, which are designed for well-understood, correct programs rather than for exploration and debugging of potentially flawed generated code. The project's impact extends to responsible integration of AI code generation tools into broader software development toolchains and environments.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $391.1k | 4/1/26 |