This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, provides $598,448 to Cornell University to develop theoretical and algorithmic foundations for online learning and decision-making involving sequential data under unknown stochastic models. The key research activities are structured under three thrusts: (i) representation learning of nonlinear and nonparametric time series models, (ii) statistical...
This $1,100,000.00 Project Grant award from the U.S. Department of Energy's Grid Infrastructure Deployment and Resilience program (CFDA 81.254) will support Cornell University's "Improving Market Prices and Adequacy in the Clean Transition (IMPACT)" project. The project aims to modernize and enhance the U.S. electric grid infrastructure through investments in technology, infrastructure, and community resilience. Key focus areas include grid modernization, transmission line upgrades,...
Cornell University received a $305,824 Project Grant award from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering (47.041) federal grant program. The award will fund research from June 2023 through May 2026 to develop a general strategy for coordinating offline resource allocation decisions with real-time operational policies across industries. The research aims to provide a context-independent coordination mechanism that can be...
This $600,000 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to integrate federated learning with power systems to better predict electricity consumption and lower the cost of electricity generation. The project will develop machine learning methods, specifically recurrent neural networks, to forecast day-ahead electricity consumption using distributed data from smart meters while preserving consumer privacy. Key scientific...
This Project Grant award of $249,998 from the National Science Foundation Division of Electrical, Communications and Cyber Systems Engineering Directorate will fund research at Cornell University from September 2021 through August 2024. The research aims to advance co-design of prediction and control across data boundaries to improve efficiency, privacy, and markets. Specifically, the grantee will collaborate to develop techniques for coordinating predictive algorithms and controllers when...
The National Science Foundation awarded a $265,702 Project Grant to the Rochester Institute of Technology under the Engineering program (CFDA 47.041) to develop an integrated systems model linking consumer activities, expenditures, and energy use from April 1, 2023 to March 31, 2026. The research will construct a holistic model of U.S. energy demand considering how consumer actions simultaneously impact multiple sectors, including residences, vehicles, commercial buildings, server networks,...
This $300,000 federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences will fund research to develop new mathematical techniques for optimization in the context of big data and contemporary data science challenges. The principal investigator at Cornell University will lead this 3-year project, which aims to transform the design and analysis of optimization algorithms across diverse fields including machine learning, statistics, and control...
This $360,000 National Science Foundation project grant supports research to advance graph signal processing techniques for electric power distribution system monitoring and control from July 2022 through June 2025. Funded under the NSF Engineering program (CFDA 47.041), the awardee Cornell University will develop a novel mathematical approach incorporating physical grid modeling into machine learning algorithms. The approach interprets system states as graph signals to extract features...
This $240,000 Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) Federal Grant Program supports collaborative research on developing advanced topological modeling and machine learning techniques for integrating ultra-high-dimensional distributed energy resources into wide-area power transmission networks. The project aims to transcend the limitations of conventional grid topology models by creating a data-adaptive graph...
Cornell University was awarded a $299,999 Project Grant from the National Science Foundation Division of Mathematical Sciences on September 1, 2021 to complete the project by August 31, 2024. The grant falls under the Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in these fields and strengthen the nation's scientific enterprise through increasing knowledge and enhancing understanding of major problems. Specifically, the grant will fund NEW FRONTIERS...