Rice University was awarded a $213,216 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research from October 2021 through February 2024 to develop methods for measuring and mitigating biases in generic image representations produced by computational visual recognition models. Specifically, the university will work to disentangle biases introduced during visual representation learning,...
This $207,737 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to develop a new class of machine learning models called "Programmatic Foundation Models" that can efficiently analyze large-scale satellite, aerial, and ground imagery. The goal is to create interpretable, robust AI models that can understand global and local phenomena from images, providing insights...
Rice University was awarded a $615,994 project grant from the National Science Foundation's Computer and Information Science and Engineering program. The three-year award will support collaborative research on thermal computational imaging from October 1, 2021 to September 30, 2024. The Computer and Information Science and Engineering program aims to advance computing and communication technologies through investigator-initiated research and education. This project aligns with those goals by...
This Project Grant award of $450,626.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop a computer vision framework that learns and understands the physical world in a compositional manner. The key products and services to be delivered include: Establishing a unified framework for representing, parsing, and learning the compositionality of physical objects through disentangled modeling of large shape...
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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $300,000 to Temple University to enhance computer vision capabilities through shape configuration learning. The 3-year project aims to develop new deep learning techniques that allow computers to better recognize and comprehend objects as interconnected shapes, rather than just individual parts. This includes improving attention mechanisms to focus on relevant...
This four-year, $400,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new techniques for 3D scene understanding. Specifically, the Stanford University researchers will explore implicit neural representations to model scene structure and details from raw images and videos. They will integrate findings into course development and partner with organizations to teach artificial intelligence, computer vision, and...
This Project Grant award, funded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop a hybrid, vision-centric framework that integrates intuitive and deliberate visual processing to create more robust visual intelligence. The $111,878 award to New York University (NYU) supports research focused on three primary directions: 1) advancing vision-centric parametric knowledge through techniques like visual...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will provide $600,000 to the University of Wisconsin-Madison to advance the understanding and applications of deep learning models that underpin modern artificial intelligence (AI) systems. The research aims to deepen the theoretical foundations of deep learning by exploring vector-valued, multi-output mappings, compositional function spaces, and the...
The National Science Foundation Division of Information and Intelligent Systems awarded Yale University $550,000.00 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the project "CAREER: FROM FAIRNESS TO JUSTICE IN AI SYSTEMS" from October 1, 2021 to September 30, 2026. This five-year project grant will support Yale University's investigator-initiated research and education efforts aimed at advancing the development of fair, just and...