Project Grant 2312955
- This NSF Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Project Grant, awarded to Arizona State University in the amount of $598,123 on July 15, 2024, will develop new algorithms to enable AI systems to autonomously learn hierarchical world models and high-level actions. The goal is to create AI systems, such as hospital robots and disaster-recovery support systems, that can plan reliably and efficiently to accomplish complex user-desired tasks, without requiring...
- This $243,000 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at the University of Illinois to develop new understanding and control strategies for how robots can influence human behavior over long-term interactions. The key goals are to build theory and mathematical models explaining human adaptation to robot behaviors, devise robot control strategies to maintain influence as humans co-adapt, and formalize optimization...
- The National Science Foundation (NSF) awarded a $337,962 Computer and Information Science and Engineering (CFDA 47.070) Project Grant to the University of Illinois to expand its Breakthrough Tech AI program. The project, executed in collaboration with Cornell Tech and Hofstra University, aims to democratize access to high-quality AI education and significantly increase the number of underserved students, particularly women and other underrepresented groups, who receive training in artificial...
- This $474,838 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant, awarded to the University of Illinois, supports research addressing the triple challenges of accuracy, robust generalization, and interpretability in machine learning (ML) models. The key technical aims of the project include: (1) developing a unified framework for analyzing and optimizing the trade-offs...
- This $1.7 million project grant from the National Science Foundation's STEM Education program (CFDA 47.076) will fund the development of a novel AI-powered student support system to improve metacognitive calibration skills at the University of Illinois from August 2022 to July 2025. The project aims to research methods for enhancing students' ability to accurately estimate their own level of knowledge using short, personalized training exercises delivered through a decentralized AI framework....
- The University of Illinois was awarded a $500,000 Project Grant from the National Science Foundation Division of Information and Intelligent Systems to support research activities related to reinforcement learning in non-stationary environments. Specifically, the grant will fund the development of techniques for safe reinforcement learning with fast adaptation and disturbance prediction capabilities. The work advances the National Science Foundation's Computer and Information Science and...
- This Project Grant award of $200,000 from the National Science Foundation's STEM Education (47.076) program aims to promote AI readiness and democratize AI technologies for a broad spectrum of advanced cyberinfrastructure users and researchers. The key products and services provided under this 4-year award, which began on September 1, 2023, include: Developing a comprehensive suite of experiential learning modules, including flexible micro-modules and immersive extended reality experiences, to...
- This $299,999 Project Grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enhance the performance of reinforcement learning (RL) systems in completing complex tasks in challenging environments. The project aims to develop new task and environment representations to enable active learning strategies that optimize resource allocation and reduce the need for extensive physical interactions with the...
- This $506,819 project grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program focuses on developing innovative methods to efficiently evaluate the performance of artificial intelligence (AI) agents. The project aims to address the challenges of traditional AI evaluation approaches, which often require extensive live testing that can be resource-intensive and pose safety risks. To address these issues, the research will deliver...
- This $474,083 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research to develop embodied artificial intelligence (AI) agents capable of perceiving, reasoning, and interacting effectively with both the physical world and other agents in dynamic, evolving environments. The key objectives are to: (1) create paradigms for robotic agents to autonomously propose new tasks, generate environments, and...
This $799,368 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) will support the University of Illinois in developing AI systems that can learn from and exceed the capabilities of human demonstrations. The key products and services to be delivered through this 3-year award include: Reformulating imitation learning methods for AI systems that are more capable than human demonstrators, to enable the AI to perform better than the human. This will involve using maximum margin optimization to guide reinforcement learning of control/decision policies, with a focus on learning from heterogeneous demonstrations that vary in quality, difficulty, and structure. The project will also develop deep representation learning methods to learn performance metrics directly from the demonstrations and supplemental annotations. The resulting AI policies will be evaluated on a diverse set of applications including simulations, robotics tasks, and cancer treatment decisions. The grant will also support the training of graduate and undergraduate students in developing these advanced AI systems that are better aligned with safety and utility requirements for impactful future applications.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $799.4k | 6/26/23 |