Project Grant 2617441
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $271,080 on January 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop AI models that reason constructively about complex mathematical problems and advance formal proof systems. The collaborative research project, spanning January 1, 2026, through December 31, 2028, and performed in Los Angeles, California, aims to synergize artificial...
- The National Science Foundation Division of Mathematical Sciences awarded California Institute of Technology $271,080 on January 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop artificial intelligence models that reason constructively about complex mathematical problems and advance mathematical discovery through AI-enhanced computational methods. The research focuses on endowing AI systems with the ability to tackle intricate mathematical reasoning tasks by...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $300,000 on August 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical foundations and scalable algorithms for high-dimensional sampling and generative modeling. The project develops a unified mathematical and computational framework for sampling and generative modeling applicable to high-dimensional problems in scientific...
- The National Science Foundation Division of Mathematical Sciences awarded $214,876 to the University of California, Los Angeles on October 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049). The project develops a rigorous theoretical foundation for multi-operator learning, establishing a mathematical framework to understand how neural networks can efficiently learn across collections of complex physical systems. The work addresses gaps between empirical advances in deep...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $120,000 on August 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to advance structural properties of the universe of mathematics through research in forcing, large cardinals, and descriptive set theory. The recipient will investigate three specific subjects: the tree property of cardinal numbers and its connection to large cardinal axioms and...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $1,263,600 on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to establish a Research Training Group in Statistics and Data Theory based in UCLA's Department of Statistics & Data Science. The award funds an integrated research and training ecosystem spanning high school through postdoctoral levels. Undergraduate students will participate in...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $139,995 on June 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop robust, scalable, and statistically principled methods for integrating and analyzing multimodal data with emphasis on uncertainty quantification. The research addresses the challenge of nonparametric estimation when multiple high-dimensional and heterogeneous data sources—such as...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $330,000 on January 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop randomized algorithms for operator learning in Sobolev spaces with application to parametric partial differential equations. The project addresses computational constraints in neural network-based operator learning by designing and analyzing randomized training algorithms...
- The National Science Foundation awarded The Leland Stanford Junior University $677,600 on September 15, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop artificial intelligence systems capable of proving graduate-level mathematical theorems and addressing unsolved problems. The project, titled "AIMING: AI Theorem Proving Beyond Limited Data: Efficient Learning of Mathematicians' Ecosystem," trains AI systems that mirror how mathematicians learn and...
- The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $270,000 on July 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) for a CAREER grant to develop theory and methods for nonparametric statistical estimation using neural networks. The project, running through June 30, 2031, establishes rigorous statistical foundations for pretraining in machine learning by characterizing when it improves efficiency in...
The National Science Foundation Division of Mathematical Sciences awarded the University of California, Los Angeles $1.08 million on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop a human-centered, AI-assisted framework for interactive mathematical reasoning and discovery. The project, running through August 31, 2029, establishes effective human-AI collaboration paradigms that adapt to user expertise while preserving interpretability and mathematical intent. UCLA will build robust mathematical reasoning models through curriculum learning and contrastive learning, using high-quality, research-aligned synthetic data generation to capture the diversity of proof styles and definition systems employed by mathematicians. The work includes developing interactive reasoning tools using formal theorem proving as a demanding use case that supports both exploration and verification through structured knowledge representations. Key innovations encompass adaptive collaboration interfaces that modulate AI assistance according to user expertise, an integrated human-AI data generation workflow producing high-fidelity training data through controllable blueprint construction and robustness testing of definitions, and an interactive theorem prover capable of reliably following human guidance via structured constraints. Performance occurs in Los Angeles, California.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.1m | 8/5/26 |