Project Grant 2331881
- The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $600,000 Project Grant to the University of California, Berkeley (UC Berkeley) to develop new techniques for autonomous systems to learn effective behaviors while always respecting strict safety constraints. The 3-year project (1/1/2026 - 12/31/2028) will tackle a core challenge in making intelligent machines like self-driving cars and delivery robots reliable and trustworthy by...
- 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,...
- 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 federal Project Grant award of $800,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is supporting research to develop methods for certifying the safety of autonomous systems that use deep learning-enabled perception, prediction, and control components. The key goals of the project are: (1) to develop techniques for learning safety certificates and control policies for these types of learning-enabled autonomous...
- 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 $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 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...
- The National Science Foundation (NSF) awarded a $194,000 Project Grant under the Engineering program (CFDA 47.041) to Georgia Tech Research Corp to conduct research on safe reinforcement learning. The project aims to develop new approaches for training, improving, and evaluating reinforcement learning policies that are robust to distribution shift and non-stationarity, with the goal of ensuring safety in applications such as robotics, autonomous driving, and power systems. Key innovations...
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 systems. The research will focus on advancing techniques for uncertainty representation, safety-aware learning and control, and online safety monitoring to handle both known and unknown environmental factors. The project outcomes will be incorporated into undergraduate and graduate courses, and the research team plans to organize workshops to foster a community around safe learning-enabled systems. No sub-awards are planned for this grant, which has a performance period from October 1, 2023 to September 30, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $266.6k | 9/12/23 |