Project Grant 2502377
- The National Science Foundation (NSF) awarded a $1,323,521 Project Grant under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) to Auburn University. The purpose of this 5-year collaborative research project is to train undergraduate students, graduate students, and postdoctoral researchers to conduct advanced research at the intersection of mathematics, artificial intelligence (AI), and data science. The project centers on three integrated research modules: (1)...
- The National Science Foundation (NSF) awarded a $275,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to The Johns Hopkins University. The grant supports collaborative research on "Geometric Properties of Stationary Measures for Smooth Iterated Function Systems" in the field of dynamical systems. The research aims to study the regularity and dimension of stationary measures arising from nonlinear actions, such as self-conformal...
- This $160,118 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program will support The Johns Hopkins University in developing fast and accurate machine learning algorithms with interpretable mechanisms for learning from complex datasets. The project aims to close the theoretical and computational gap between data-independent and data-adaptive random partitioning methods in machine learning, by utilizing and expanding the toolkit of...
- The Johns Hopkins University received a $340,128 Project Grant award from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The award will support research from July 2023 through June 2026 focused on developing new data science approaches and computational models for large-scale shape and image registration analysis. Specifically, the university will conduct theoretical, numerical, and...
- 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...
- The National Science Foundation awarded The Johns Hopkins University a $900,000 Project Grant under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to conduct collaborative research focused on understanding robustness in machine learning via parsimonious structures from October 1, 2022 to September 30, 2025. Specifically, the University will research conditions under which one can detect adversarial attacks on networks or data poisoning and reconstruct...
- The National Science Foundation (NSF) awarded Carnegie Mellon University a $567,000 Project Grant under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant, which runs from September 1, 2025 to August 31, 2028, supports the "AIMING: A NEURO-SYMBOLIC APPROACH TO MECHANIZED MATHEMATICAL REASONING" project. This project aims to develop novel AI techniques that combine machine learning and symbolic AI methods to advance mathematical reasoning and the...
- 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 Project Grant award of $479,660, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049), will support a collaborative research project between Auburn University and Tuskegee University. The project aims to train undergraduate students, graduate students, and postdoctoral researchers to conduct advanced research at the intersection of mathematics, artificial intelligence (AI), and data science. Through...
- 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) awarded a $350,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to The Johns Hopkins University. The grant supports a research program to develop "Any-Dimensional Equivariant Learning" algorithms that can effectively handle input data of varying sizes, addressing a key limitation of modern artificial intelligence (AI) systems. The project aims to create parameterized families of solution mapping algorithms that can gracefully scale to inputs of any dimension, enabling more flexible and versatile AI applications across domains such as imaging, signal processing, recommendation systems, and partial differential equations. The award period runs from August 1, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $350.0k | 7/21/25 |