Project Grant 2522202
- This $483,129 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports research to advance understanding of human visual perception and scene processing. The project seeks to test whether state-of-the-art AI vision-language models can generate plausible visual scenes that mimic how the human brain perceives objects in peripheral vision during everyday activities. The research aims to provide insights into the...
- This Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $378,352 to Barnard College to conduct research on how the brain uses visual and linguistic information to achieve specific goals. The project aims to understand the cognitive processes underlying goal-directed perception, using a combination of methods from visual AI, language AI, neuroscience, and cognitive science. Key activities include training deep neural...
- This $234,610 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports collaborative research at Colgate University to study how the brain uses visual and linguistic information to achieve specific goals. The research aims to advance theories of human cognition and develop more adaptive, human-aligned artificial intelligence (AI) systems. Key project activities include training deep neural networks to predict...
- 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 $1,090,678 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop computational algorithms that align deep neural networks (DNNs) with human visual processing. The project aims to rectify the growing "misalignment" between the behavior of large-scale DNNs and human cognition as AI systems become more capable. Researchers at Brown University will combine human...
- This federal Project Grant award of $301,800.00 from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports a research project led by Yale University to study the neural mechanisms of object cognition using multilevel computational modeling. The overarching hypothesis is that the brain implements object cognition by building and manipulating generative models of physical scenes, their dynamics, and sensory inputs. The project aims to develop...
- This federal Project Grant award, valued at $399,999.00 and awarded on July 15, 2025, was provided by the Division of Information and Intelligent Systems (IIS), a civilian agency within the National Science Foundation (NSF). The grant supports a collaborative research project titled "Perception-Augmented Databases for Efficient and Robust Visual Analytics" under the NSF's Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The research aims to develop...
- This Project Grant award, valued at $325,000.00, was provided by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Washington. The project develops powerful new tools for understanding complex data, leveraging cutting-edge artificial intelligence (AI) techniques to help data analysts across diverse fields make informed, automated decisions. The research introduces novel approaches to analyze messy, heterogeneous, and large...
- The National Science Foundation (NSF) awarded a $600,000 Project Grant to Carnegie Mellon University under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The 3-year project, running from June 1, 2025 to May 31, 2028, aims to investigate the computational mechanisms underlying a recently discovered neural process in the brain - the ability of neurons in the early visual cortex to rapidly form local recurrent circuits. The project seeks to...
- This $400,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The project aims to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models, in order to increase the accountable and safe use of these advanced AI systems and mitigate potential harms. The key research thrusts involve: 1) new...
This federal Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $443,888 to the Research Foundation of the City University of New York (RFCUNY) to test theories of perceptual valuation using advanced machine learning and artificial intelligence (AI) techniques. The project aims to: 1) determine if deep neural network machine learning models can serve as proxies for people's internal models of visual objects, 2) use generative AI to create novel images to probe these internal models, and 3) test the hypothesis that perceptual value is highest when objects are similar to but also offer the opportunity to learn something new compared to existing knowledge. The award period runs from Sep 1, 2025 to Aug 31, 2028 and the research will be conducted by RFCUNY, a non-profit educational institution that serves as the fiscal administrator for sponsored research and programs across the City University of New York system.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $443.9k | 8/15/25 |