Project Grant 2331878
Award Date
1/1/24
Completion Date
12/31/27
Dollars Obligated
$969K
Funding Federal Agency
Division of Computer and Network Systems
Awarding Federal Agency
Division of Information and Intelligent Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Urbana, IL 61801, USA
Similar Awards
This $500,000 project grant, awarded on January 1, 2024 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to address the urgent need for end-to-end safety in learning-enabled autonomous systems across various application scenarios, such as self-driving cars and urban air mobility. The project, titled "COLLABORATIVE RESEARCH: SLES: GUARANTEED TUBES FOR SAFE LEARNING ACROSS AUTONOMY ARCHITECTURES,"...
This $316,963 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research to enhance the safety and reliability of autonomous vehicles. The project aims to thoroughly examine and improve the controller and machine learning components of autonomous driving systems through a combination of model-based and data-driven approaches. The research will focus on identifying spatial and temporal vulnerabilities that...
The National Science Foundation (NSF) has awarded a $266,589 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of California, Berkeley to develop safe learning-enabled systems that can navigate uncertain environments. The project aims to create a two-phase design process that combines an offline robust synthesis phase with an online safety monitoring and adaptation phase, enabling provable end-to-end safety guarantees for learning-enabled...
This $270,913 federal Project Grant award, funded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program, supports research to develop qualitative and quantitative methodologies for assessing the safety of learning-enabled autonomous systems. The project, led by the Augusta University Research Institute, Inc. (AURI), will target foundational challenges in capturing uncertainties from environments and providing timely, comprehensive, and...
The National Science Foundation (NSF) awarded a $793,065 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Wisconsin System for the project "SLES: Foundations of Safety-Aware Learning in the Wild." The project aims to develop novel machine learning algorithms and theoretical guarantees that can reliably detect and handle out-of-distribution data encountered by AI models deployed in dynamic, unpredictable environments. This...
This $272,238 Project Grant, awarded on July 15, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enhance the safety and reliability of autonomous vehicles. The project aims to identify vulnerabilities in the software and machine learning components of autonomous vehicle systems, and develop mitigation techniques to improve their overall resilience. The research will combine model-based and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $1,499,949 to the University of Delaware focuses on developing safe learning-enabled systems for autonomous vehicles (AVs). The key innovations include: Developing rational machine learning (ML) models to produce accurate predictions based on valid rationales, Integrating hardware reliability into ML model design to tolerate runtime faults, and...
This $800,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop new techniques to certify the safety of autonomous systems using learning-enabled perception and prediction components. The key goals are: (i) learning safety certificates and control policies, and (ii) certifying the learned system. The project is addressing challenges in scaling the computation of safety certificates by...
This $218,165 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) project grant aims to create new formal methods and tools to enhance the safety, reliability, and explainability of learning-enabled autonomous systems. The key research thrusts involve: Developing a generic graph-based modeling approach for complex, learning-enabled autonomy systems, including new set-based algebra and specification language to represent system behaviors and...
This $425,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a framework for ensuring the safety of future robotic systems. The research project, led by The Trustees of Princeton University, aims to lay the foundation for safe robot autonomy by enabling robots to continually prove the safety of their actions under a wide range of operating conditions, from complex physical...