The National Science Foundation awarded a $400,000 Project Grant to the University of Washington under the Engineering program (CFDA 47.041) to develop data-guided system-theoretic techniques for control of dynamic systems from August 15, 2022 to July 31, 2025. Specifically, the award will support research to extend the current data-guided control paradigm to nonlinear systems and networked systems through novel data-parameterized analysis and synthesis methods. The research will also examine...
This Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under the NSF Directorate for Engineering (CFDA 47.041) provides $441,162 to the University of Washington to develop innovative variational optimal transport methods for nonlinear filtering algorithms to improve the reliable and safe operation of autonomous systems. The research objectives include computational development and evaluation of the proposed algorithms,...
The National Science Foundation (NSF) awarded a $271,362 Project Grant to the University of Washington under the Engineering program (CFDA 47.041) with a performance period from January 1, 2024 to June 30, 2025. The grant will fund the development of efficient surrogate modeling methods to predict discontinuous design performance in complex engineering systems, such as smart factories and autonomous material handling systems. The research aims to facilitate the solution of challenging...
This $147,212 federal Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) supports research to enable the development of a framework for safe control in autonomous systems in the presence of sensor and actuator faults and cyber attacks. The research combines techniques from control theory, machine learning, and system security to provide provable safety guarantees across a range of autonomous systems and fault/attack scenarios. Key focus areas include...
This National Science Foundation (NSF) Engineering Program (CFDA 47.041) $150,000 Project Grant award to the University of Wisconsin-Madison funds a 2-year exploratory research project titled "EAGER: Collaborative Research: Real-Time Heterogeneous Transfer Active Learning to Bridge Knowledge Gaps in System Integration Under Environmental Uncertainty." The project aims to develop a real-time transfer learning framework to enhance uncertainty quantification and quality control for...
This $522,592 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to create a data-driven autonomy framework that enables everyday workers to safely and effectively teach robots. The research will advance the state-of-the-art in dynamical systems and control through three interconnected thrusts: 1) developing a novel framework for data-driven control of complex, hard-to-model systems; 2) introducing methods for teaching robots through...
This $994,988 National Science Foundation project grant through the Engineering program (CFDA 47.041) will fund research at the University of New Mexico from May 1, 2023 through April 30, 2028. The research aims to develop an algorithmic framework for integrating knowledge of human perception and reasoning about uncertainty into the design and control of autonomous dynamical systems. New mathematical theory and computational algorithms will be created based on control theory, machine learning,...
This Project Grant award of $588,751 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to address computational challenges in real-time analysis of high-throughput sensor data for collaborative autonomous vehicles. The University of Maryland, College Park is developing a novel large-scale machine learning and edge computing framework to integrate emerging techniques like fast deep learning optimization, federated...
This National Science Foundation (NSF) CAREER award under CFDA 47.041 (Engineering) provides $522,786 in funding to the University of Georgia Research Foundation, Inc. over a 5-year period from September 2024 to August 2029. The project aims to advance fundamental research in uncertainty-aware sensing and management for Internet-of-Things (IoT) systems, with a focus on addressing key challenges in safety-critical IoT applications such as healthcare, transportation, and environmental...
This $599,943 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop techniques for more efficient and resilient real-time communications in critical cyber-physical systems like aircraft, automobiles, and industrial control networks. The key innovations include creating holistic models, algorithms, and software designs to achieve the scalability, adaptability, and resiliency...