The National Science Foundation (NSF) awarded a 5-year, $214,287 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Research Foundation For The State University Of New York (RF SUNY), doing business as Stony Brook University. The goal of this research is to advance the foundations of formal methods in order to make formal verification of AI-based cyber-physical systems (CPS) practical. The project investigates approximation approaches where an...
This Project Grant award, valued at $600,000 and spanning from December 2024 to November 2027, is funded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The key objectives of this project are to: Develop a comprehensive framework for end-to-end verification of control systems, encompassing high-level hybrid models down to the verification of embedded C code. This includes designing an end-to-end process to...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, aims to simplify and automate the verification of high-performance distributed systems. The $375,000 award to the Regents of the University of Michigan, to be completed by September 2027, will develop new techniques such as message invariants and distributed ownership types to make formal verification of complex, real-world distributed systems more...
This Project Grant award, totaling $213,679, was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award supports the development of a novel methodology for the design and verification of learning-enabled cyber-physical systems (CPS) that rely on machine learning algorithms. The project aims to create a compositional framework that can reason about the uncertainty and approximation introduced by...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, totaling $299,392, aims to build a collaborative mechanism for academia, industry, and the public sector to co-design research and development (R&D) directions for data systems and artificial intelligence (AI) to address scientific and societal challenges. The project, led by the Regents of the University of Michigan, will bring together data science and...
This National Science Foundation (NSF) grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,200,000 to The Washington University to develop new theoretical and algorithmic capabilities for ensuring the robust and safe deployment of AI-enabled cyber-physical systems (CPS). Specifically, the project aims to design certification, verification, and robust training algorithms for multi-agent reinforcement learning (MARL) control policies. This will...
This $149,343 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program supports the development of a new quantitative verification approach for temporal properties of learning-enabled cyber-physical systems (LE-CPS). The key objectives are to: Develop a qualitative and quantitative verification approach for LE-CPS at the system level based on Probstar reachability, providing the precise probability of...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program award, with a total funding of $175,000, supports the development of novel verification methodologies to enhance software quality, safety, and security for safety-critical and security-critical applications such as self-driving cars and digital medical services. The project aims to develop verification techniques based on first-order assertions and auxiliary logical variables,...
The National Science Foundation (NSF) awarded a $260,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Illinois for the project "COLLABORATIVE RESEARCH: SLES: VERIFYING AND ENFORCING SAFETY CONSTRAINTS IN AI-BASED SEQUENTIAL GENERATION". This 3-year project aims to develop formal verification methods and constrained generation techniques to ensure the safety and reliability of AI models used for sequential data processing...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $209,421 to the New Jersey Institute of Technology (NJIT) aims to develop a framework that integrates real-time safety verification and assurance into the performance optimization process of AI-driven safety-critical systems. The project will devise innovative real-time scheduling strategies to handle the dynamic computational workloads of these systems...