Project Grant 2453378
- This $218,771 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to develop new theoretical tools to enhance flow-based generative artificial intelligence (AI) models. The research aims to elucidate how these models, including diffusion models, produce novel outputs and extend their capabilities to handle complex data types beyond the Euclidean setting, such as graphs and point clouds. The project,...
- The National Science Foundation (NSF) awarded a $900,000 Project Grant to Cornell University under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The project, titled "Understanding and Supporting the Effectiveness of Groups Working with Generative AI," aims to investigate how generative AI tools like ChatGPT and Microsoft Copilot affect team dynamics, relationships, and individual well-being in collaborative work settings. Leveraging...
- This federal Project Grant award, titled "CAREER: BRINGING STRUCTURE TO THE UNSTRUCTURED: ROBUST CAUSAL AND STATISTICAL MODELING OF HIGH-DIMENSIONAL UNSTRUCTURED DATA", is provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The $329,020 grant, awarded to the University of Michigan on June 15, 2025, focuses on developing new analytical tools to extract meaningful insights from complex, high-dimensional...
- This federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program provides $594,753 to Cornell University to develop new methods for controlling generative artificial intelligence (AI) systems that produce text and images. The research aims to improve the reliability and safety of these AI technologies, especially in sensitive applications like healthcare, customer service, and education. The project will...
- This federal Project Grant award of $381,276.00 was made on June 15, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The grant supports research at the University of California, San Diego (UCSD) to develop next-generation machine reasoning capabilities by systematically incorporating the concept of "world model" into the design, training, and application of new reasoning models. The research aims...
- This $599,877 federal Project Grant was awarded on December 1, 2024 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant is funding a 3-year research project at Clemson University to study the opportunities and challenges that generative AI technologies like ChatGPT and Midjourney present for end-user driven creative workforces in industries such as entertainment. The key objectives are to: (1) empirically...
- This $300,000 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, awarded on April 1, 2025, aims to develop a foundation model for predicting rare events in atomistic simulations. The research, conducted by the University of Maryland, College Park, leverages advanced AI techniques like equivariant transformers, generative models, and multimodal learning to enhance prediction accuracy and generalization across...
- This $150,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of foundational principles, algorithms, and tools for causal decision-making systems. Researchers at Columbia University will enrich traditional artificial intelligence formalism with causal modeling to enable more efficient, robust, and explainable decision-making by autonomous systems. Key deliverables include integrating...
- This $245,190 Project Grant awarded by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to advance the integration of modern machine learning tools, such as deep learning and Bayesian additive regression trees, into statistical modeling frameworks. The research program has two key objectives: Developing a novel Bayesian inferential framework for "generative models" - statistical models where data is viewed as stochastic outputs of...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with the CFDA number 47.070, provides $155,000.00 to the University of Michigan to develop methods for generative artificial intelligence (GenAI) tools to create synthetic but useful data for network and application security tasks. The goal is to enhance the performance of security classifiers, which use machine learning to identify cyberthreats like malware or...
This $545,359 Project Grant was awarded on August 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant supports the development of a new generation of generative artificial intelligence (AI) models designed to learn causal models and enable robust causal reasoning and meaningful abstraction. The research aims to deliver interpretable, verifiable, and robust generative AI systems that can generalize more reliably, predict results of actions, and offer deeper understanding across real-world scenarios. By integrating principles from causality with advances in deep learning, the project seeks to address shortcomings of current generative AI models that struggle with causal reasoning. The University of Chicago, a leading research institution, is the primary awardee and will execute the research over the grant period from August 1, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $545.4k | 7/30/25 |