Project Grant 2331880
- 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...
- The Trustees of the University of Pennsylvania received a $500,000 Project Grant award from the National Science Foundation Division of Electrical, Communications and Cyber Systems on February 15, 2021 to support research titled "CAREER: TOWARDS A THEORY OF ROBUST LEARNING & CONTROL FOR SAFETY-CRITICAL AUTONOMOUS SYSTEMS" through January 31, 2026. This award will fund research under the NSF Engineering program (CFDA #47.041) to develop a theoretical framework for robust learning...
- 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...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) will support research to establish a framework for designing and implementing safe learning-enabled systems. The $399,965 award to Cornell University, with a period of performance from October 1, 2024 to September 30, 2027, aims to develop methods for ensuring the safety of learning-enabled systems, even in complex operating environments,...
- 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,"...
- 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 $800,000 Project Grant award to The Trustees of Princeton University, Department of Research and Project Administration, was provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award aims to develop new techniques for constructing a vision-based safety supervisor that can endow autonomous robotic systems, such as self-driving cars and home robots, with the safety property of "graceful degradation."...
- This Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems supports research to develop low-complexity, safe learning-enabled algorithms for partially observable nonlinear systems with uncertain dynamics. The $400,000 award to Michigan State University aims to accomplish two key objectives: 1) Propose direct data-driven learning approaches for backup safe control policies in partially observable nonlinear systems, and 2) Introduce...
- The National Science Foundation (NSF) awarded a $969,060 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Illinois to develop a novel solution called "Data-Enabled Simplex" or "DESIMPLEX" to address the urgent need for end-to-end safety in learning-enabled autonomous systems. The project aims to: (i) improve high-performance autonomy with reliable uncertainty quantification methods to ensure data-driven...
- This National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems award, CFDA 47.041 Engineering, will provide $193,000 from September 1, 2024 to August 31, 2027 to New York University (NYU) to develop new theories and methodologies for safe reinforcement learning in domains such as robotics, autonomous driving, and power systems. The key products and services to be delivered under this Project Grant include: 1) Formulating safety measures as general objectives...
This NSF CISE program Project Grant awarded to The Trustees of the University of Pennsylvania, doing business as the Clinical Practices of the University of Pennsylvania, is providing $533,411 to fund collaborative research focused on maintaining the safety of learning-enabled systems that navigate in unknown environments. The key objectives are to: (i) develop a two-phase design and deployment process that integrates offline robustness synthesis with online safety monitoring and adaptation, (ii) ensure safety with respect to both known and unknown uncertainties, and (iii) create techniques to identify and learn about novel sources of uncertainty. This research addresses major challenges in representing, characterizing, and accounting for uncertainty in learning-enabled components using streaming data. The project outcomes will be incorporated into academic coursework and shared through workshops at major conferences to foster an interdisciplinary community focused on safe learning-enabled systems. No sub-awards are planned for this 3-year grant, which commenced on October 1, 2023.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $533.4k | 9/12/23 |