Project Grant 2534237
- The National Science Foundation Division of Computer and Network Systems awarded Rensselaer Polytechnic Institute $600,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a function encoder framework for transferable and adaptive cyber-physical intelligence in metal additive manufacturing. The research develops learning-enabled control systems that generalize knowledge across tasks, adapt to changing operating conditions in real...
- The National Science Foundation Division of Computer and Network Systems awarded the University of Texas at Austin $500,000 on July 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for research on cloud robotics systems that dynamically balance edge computation and cloud inference under network constraints. The project develops algorithmic foundations enabling robotic fleets to continuously learn and adapt while managing the inherent trade-off between...
- The National Science Foundation Division of Computer and Network Systems awarded the University of Texas at Austin $650,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop continual learning methods enabling mobile manipulation robots to acquire, refine, and reuse household skills over time without full retraining when encountering new environments, objects, or tasks. The research will create a continual learning framework organized...
- The National Science Foundation (NSF) awarded a $1,200,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the University of Texas at Austin. The grant, running from June 1, 2024 to May 31, 2027, aims to develop theoretical frameworks and practical algorithms for learning data-driven models and control strategies in networked cyber-physical systems, with a focus on power distribution systems. Key areas of work include designing...
- The National Science Foundation Office of Advanced Cyberinfrastructure awarded the University of Texas at Austin a $1.2 million Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) from September 1, 2022 to August 31, 2025. The grant funds research to develop a rigorous and reliable scientific deep learning framework for forward, inverse, and uncertainty quantification problems in computational science and engineering. Specific objectives include...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Texas at Austin $349,323 on a Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070), with an award date of June 1, 2026. The award funds research developing a unified framework for learning physically grounded models of three-dimensional human-world interactions from real-world video. The project reconstructs physically consistent...
- The National Science Foundation Division of Information and Intelligent Systems awarded the University of Texas at Arlington $408,211 on July 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop an artificial intelligence-driven framework for proactive wireless network resource management in next-generation networks. The project creates deep learning models using multi-headed transformer architecture to translate raw sensor data from cameras and...
- The University of Texas at Austin has been awarded a $298,878 EAGER grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The grant, titled "NON-TRADITIONAL IN NEXT-GENERATION SYSTEMS (TNTS) -TECHNOLOGY TRAINING FOR NON-TRADITIONALS (TNT)", is an exploratory project that aims to increase the cybersecurity workforce by providing mentoring, hands-on training, and support to participants from diverse socioeconomic...
- This project grant award of $600,000 from the National Science Foundation's (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA #47.070) program will support the development of hybrid models that combine deep neural networks and high-fidelity partial differential equation (PDE) solvers. The goal is to create a system that maintains the accuracy of PDE models while leveraging the speed of neural networks to enable accelerated solutions for...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the University of Texas at Dallas $514,916 on July 15, 2026, under the NSF CAREER program (CFDA 47.041 Engineering). The award funds development of adaptive and scalable resilience methods for complex networked systems such as robot teams, infrastructure networks, and distributed learning systems that must operate reliably under corrupted information, imprecise measurements, and partial network...
The National Science Foundation Division of Computer and Network Systems awarded the University of Texas at Austin $600,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a function encoder framework for transferable and adaptive cyber-physical intelligence in metal additive manufacturing. The award funds research developing learning-enabled control systems that generalize knowledge across tasks, adapt to changing operating conditions in real time, and integrate physical principles governing the systems they control. The central innovation uses function encoders—neural representations that learn compact function-space bases reusable across tasks, environments, and system configurations. The research comprises three thrusts: foundations for transfer learning using function-space representations including generalization guarantees and uncertainty quantification; real-time adaptation mechanisms; and physics-informed modeling in cyber-physical systems. While motivated by robotic and hybrid manufacturing systems combining additive and subtractive operations, the resulting methods apply broadly across diverse cyber-physical domains. The project also supports workforce development through research training, curriculum development, and STEM outreach. Performance takes place in Austin, Texas, with an ultimate completion date of July 31, 2029. The University of Texas System is the parent organization.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 8/5/26 |