Project Grant FA23862414017

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 collaborative research project, funded by the National Science Foundation's Division of Social, Behavioral and Economic Sciences (CFDA 47.075) with $264,480 obligated to Duke University, develops advanced macroeconomic modeling frameworks that incorporate artificial intelligence and experiential learning mechanisms. Rather than assuming economic decision-makers possess perfect information, the research models how individuals and organizations learn optimal decision-making through two...

This Project Grant award from the National Science Foundation's STEM Education (CFDA 47.076) program provides $450,000 to Princeton University to develop "Differentiable Logic Networks" - an interpretable and energy-efficient approach to implementing artificial intelligence (AI) and machine learning frameworks. The project aims to address the key challenge of making AI-based decisions more transparent and explainable, particularly for applications in domains like medical and legal...

This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research by the Texas A&M Engineering Experiment Station (Tees) to develop machine learning models for learning structural frameworks of an agent's dynamic decision-making behavior. The project aims to advance state-of-the-art methodologies for learning structural models of control by considering diverse data types, including...

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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) grant award (CFDA 47.070) for $299,524 will fund a project titled "EAGER: NAIRR PILOT: ENABLING PARAMETRIC SWEEPS ON EXASCALE AI-INTEGRATED SIMULATIONS THROUGH FEDERATED LEARNING." The project aims to develop an innovative framework that integrates advanced AI techniques with traditional numerical methods to enable efficient and accessible parameter space exploration for exascale multiphysics...

This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program, totaling $209,267, will fund research to close the simulation-to-reality (sim-to-real) gap in reinforcement learning (RL). The research will develop new techniques using randomization, alignment, and derivation mechanisms to improve the applicability and generalization of RL systems from simulated to real-world environments. The goal is to...

This National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) Project Grant award to the Regents of the University of Michigan, through its Office of Research and Sponsored Projects, provides $250,000 in funding from September 1, 2024 to August 31, 2027. The award supports research to develop new theoretical tools and algorithm design techniques for the emerging area of operator learning - the use of statistical machine learning to find fast approximations for solving...

This $349,427 CAREER grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at The Leland Stanford Junior University (Stanford University) to develop machine learning (ML) techniques to improve the performance of discrete optimization algorithms. The project aims to address challenges in efficiently solving complex combinatorial optimization problems, such as those encountered in supply chain logistics and...

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...