Project Grant 2512169
- 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 $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 $1,499,949 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance the safety of autonomous vehicle (AV) systems. The key focus areas include: Developing rational machine learning (ML) models that can accurately predict driving decisions based on valid rationales, rather than inappropriate extrapolations from common scenarios. Integrating hardware reliability into the...
- This $235,187 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research to develop principled algorithms and practical tools for systematically discovering and repairing unsafe behavior in multi-module autonomous vehicle systems. The key objectives are to: (1) create an automated method for constructing test scenarios that decouple high-level semantics and low-level details; (2) develop a search-based testing approach to efficiently...
- This Project Grant award for $227,673 was provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award aims to develop a hybrid, vision-centric framework that integrates intuitive and deliberate visual processing methods to create more robust visual intelligence. The project, led by New York University (NYU), will explore techniques like visual self-supervised learning, language guidance, and generative...
- This Project Grant award of $599,945 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program will fund research to develop a 3D computer vision framework that fuses multiple sensing modalities, including RGB cameras, depth sensors, LiDAR, and event cameras. The goal is to enhance feature extraction, tracking, and large-scale scene reconstruction, improving perception accuracy and adaptability in unstructured environments. This research...
- 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...
- 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 $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 University of Florida was awarded a $488,754 Project Grant from the National Science Foundation Division of Information and Intelligent Systems to develop a unifying stochastic framework for temporally consistent computer vision models. The four-year award, made on January 1, 2022 under the Computer and Information Science and Engineering federal grant program (CFDA #47.070), will support research to combine sequential Monte Carlo methods with neural networks. This will create a trainable...
This $550,199 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop specialized modeling, training, and adaptation techniques to ensure the safety and performance of vision-based autonomous systems subject to visual shifts, such as sun glares and seasonal changes. The project will leverage information-theoretic and statistical techniques to establish a robust framework for probabilistic verification and control synthesis, providing conservative models and safety estimates under latent shifts. The research will culminate in an end-to-end methodology, including a neuro-symbolic training process, to endow vision-based autonomous systems with high-performance behaviors and theoretical guarantees. The award was granted to the University of Florida and will run from October 1, 2025 to September 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 9/11/25 | ||
| Not listed | $550.2k | 8/18/25 |