Project Grant 2510307
- The National Science Foundation (NSF) awarded a $163,000 Project Grant under the Mathematical and Physical Sciences grant program (CFDA 47.049) to The Trustees of Columbia University in the City of New York. The goal of this 3-year research project is to build mathematical foundations for understanding the behavior and limitations of modern machine learning systems, with a focus on how AI models represent and learn from data. The research aims to develop general principles for how features...
- This federal Project Grant award of $100,000.00, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports research on advanced probabilistic models and their application to cutting-edge machine learning techniques. The research aims to bring mathematical rigor and develop new methods related to complex systems in areas such as image processing, reinforcement learning, and generative AI. Key focus areas include: 1) extracting...
- This $300,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to develop innovative Artificial Intelligence (AI) tools to study polyhedra, which are fundamental geometric shapes with wide-ranging applications. The key objectives of the project include: Leveraging AI techniques like diffusion methods and reinforcement learning to generate diverse, high-quality polyhedral samples Integrating large language...
- This Project Grant award, funded by the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049), aims to develop innovative artificial intelligence (AI) tools to enhance the study of polyhedra. The $400,000 award, with a performance period from September 15, 2024 to August 31, 2027, will support the creation of new methods for data generation, knowledge discovery, and formal reasoning in polyhedral...
- This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) supports research to develop novel mathematical models and efficient algorithms for deep learning on large-scale graph-structured data. The $249,999 award, spanning September 2024 to August 2027, aims to produce innovations in areas like graph convolutional networks, graph matching, and graph clustering. The research will involve graduate...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
- This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $100,000 to the University of Wisconsin System to conduct research on the mathematical foundations of advanced generative AI models. The project aims to characterize the mathematical principles that underpin the effectiveness of frontier AI models, such as large language models, and identify key mathematical quantities driving their...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to advance artificial intelligence (AI) by investigating the mathematical foundations and practical applications of deep learning models. The $600,000 award, with a performance period from December 2024 to November 2027, will support research focused on understanding the properties of neural networks, the function spaces and data representations that emerge...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $187,000.00 to the Massachusetts Institute of Technology (MIT) to develop mathematical foundations for understanding and improving graph neural networks (GNNs), which are widely used machine learning models for analyzing graph-structured data. The project aims to address key theoretical challenges with GNNs, including limited expressivity, suboptimal performance...
- The National Science Foundation (NSF) awarded a $225,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Leland Stanford Junior University. The 3-year grant, effective July 1, 2024, aims to gain a deeper theoretical understanding of the statistical properties of neural networks, which have revolutionized science and engineering. Key research directions include studying the distinguishing features of deep neural networks compared to classical statistical...
This Project Grant award of $150,000.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program aims to enhance the development and understanding of machine learning and artificial intelligence through techniques from applied algebraic geometry, specifically in the context of polynomial neural networks. The research will analyze polynomial neural networks to provide global insights that can inform a priori design choices and improve the learning process for these neural networks. The project will involve graduate student participation to enhance their training at the intersection of mathematics and AI. This award reflects NSF's mission to advance scientific knowledge and has been deemed worthy of support through the foundation's review criteria of intellectual merit and broader impacts.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $150.0k | 8/14/25 |