Project Grant 2439971
- This CAREER award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $525,009 to support research at the University of Southern California (USC) that attempts to model service interactions at a granular level rather than relying on traditional system-level queuing models. The research aims to address operational problems in the service sector, recover wasted time, and improve customer outcomes without additional resources. Additionally, the project plans to...
- The National Science Foundation (NSF) awarded a Project Grant of $515,000.00 to Northeastern University under the Engineering program (CFDA 47.041). The grant, titled "CAREER: Foundations of Scalable, Fast, and Online Decentralized Manifold Optimization in Multi-Agent Networks," aims to advance the state-of-the-art in decentralized manifold optimization (DMO) for large-scale, multi-agent systems. The research focuses on addressing three key challenges: scalability, efficiency, and...
- The National Science Foundation (NSF) awarded a $562,194 Faculty Early Career Development (CAREER) grant to the Texas A&M Engineering Experiment Station (Tees) to support research on efficient, scalable methods for characterizing and optimizing large-scale non-stationary stochastic systems. The project will contribute to scientific progress and national prosperity by developing novel data analytics and optimization approaches to improve the efficiency of mental health resources on university...
- The National Science Foundation (NSF) Engineering program awarded a $562,234 Faculty Early Career Development (CAREER) grant to the University of California, Berkeley to conduct research on new models and algorithms for dynamic allocation of resources in applications such as shared mobility, battery swapping for electric vehicles, and online advertising. The 5-year project aims to develop practical algorithmic solutions that can accommodate complex features, objectives, and constraints in...
- The National Science Foundation (NSF) awarded a $517,612 CAREER grant to the University of Texas at Austin to develop new foundations of scalable and resilient distributed reinforcement learning for real-time autonomous cooperation in open multi-agent systems. This project, funded under the NSF's Engineering program (CFDA 47.041), aims to design new learning and control methods that enable agents to interact effectively in open systems, adapt to time-varying environments, and be resilient to...
- This five-year, $500,000 National Science Foundation project grant will support research at Arizona State University to develop innovative solutions for time-synchronized estimation in power systems. Funded through NSF's Engineering program (CFDA 47.041), this CAREER award reflects the agency's mission to advance fundamental engineering research and education. The grantee will create new mathematical techniques in convex programming, interval-theoretic learning, and distributed optimization to...
- This is a $500,000 National Science Foundation (NSF) CAREER project grant awarded to the University of Texas at Austin on March 1, 2025. The project aims to advance the autonomy of power grids by developing fundamental theory to enhance decision speed, resilience, and societal/sustainability awareness of distributed grid management models and algorithms. Key technical approaches include developing novel machine learning-assisted optimizers, using AI and generative modeling to improve resilience,...
- This National Science Foundation (NSF) CAREER grant, awarded under the Engineering program (CFDA 47.041), aims to enhance power system stability and safety in the presence of large-scale inverter-based resources (IBRs) by leveraging their emerging grid-forming control (GFM) mode. The $500,167 project, awarded on October 1, 2025 and running through September 30, 2030, will develop a set-theoretic analysis framework with sparsity formulations to increase scalability and sample guidance to reduce...
- The National Science Foundation awarded a $823,480 project grant to the University of Connecticut under the Engineering program (CFDA 47.041) for work titled "CAREER: BRIDGING THE GAP BETWEEN DETERMINISTIC AND STOCHASTIC STRUCTURES FOR MIXED STOCHASTICITY SYSTEM DESIGN." This five-year award beginning January 1, 2022 will support research to improve techniques for designing systems with both deterministic and stochastic components. The Engineering program aims to foster innovation in...
- This $500,000 National Science Foundation (NSF) CAREER award, under the Engineering program (CFDA 47.041), aims to improve the computational efficiency of economics-driven transmission planning for electric power systems by up to three orders of magnitude. The project, awarded to the University of Missouri System's Missouri University of Science & Technology, will develop a multi-faceted framework that integrates innovations in modeling, simulation, computing, and design to transform lengthy...
This National Science Foundation (NSF) CAREER award, titled "EFFICIENT ALGORITHMS FOR GENERALIZED QUASI-VARIATIONAL INEQUALITIES IN STOCHASTIC AND DISTRIBUTED NETWORKS," aims to develop foundational mathematical tools to address emerging challenges in distributed and uncertain systems. The $512,830 award, effective October 1, 2025 through September 30, 2030, is funded under the NSF's Engineering program (CFDA 47.041). The project will contribute to more reliable, efficient, and scalable decision-making tools for real-world applications in areas such as energy infrastructure, machine learning, and wireless communication. Additionally, the educational plan includes engaging undergraduates in hands-on research experiences and outreach activities in middle and high schools.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $512.8k | 8/18/25 |