The University of Pittsburgh received a $316,000 Project Grant award from the National Science Foundation Division of Computer and Network Systems to support research titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: TOWARDS UNSUPERVISED LEARNING ON RESOURCE CONSTRAINED EDGE DEVICES WITH NOVEL STATISTICAL CONTRASTIVE LEARNING SCHEME." The three-year award, issued on October 1, 2021 with a completion date of September 30, 2024, will fund research into unsupervised learning techniques...
This $299,964 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to enhance computer vision capabilities for shape understanding and object recognition. The project at Stony Brook University seeks to develop deep learning models that can focus on the critical parts of an image that constitute an object, while disregarding background distractions. This will be achieved by extending recent...
The National Science Foundation (NSF) awarded a $174,967 EAGER (Early-concept Grants for Exploratory Research) Project Grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Trustees of Indiana University. This 2-year project, running from October 1, 2024 to September 30, 2026, aims to study how well machine language tools can grasp cultural nuances to enhance cross-cultural communication. The project will focus on developing a new knowledge base...
The National Science Foundation awarded $755,098 under the Computer and Information Science and Engineering federal grant program to the University of Pittsburgh to advance deep learning methods towards spatial fairness from June 2022 to May 2025. The University will develop new statistical formulations and machine learning frameworks to explicitly preserve spatial fairness when applying artificial intelligence to geospatial problems. It will investigate challenges in partitioning spatial data...
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 $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...
The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $119,999 Project Grant to the University of Baltimore, a minority-serving institution, and Florida A&M University, an HBCU, to develop tailored educational materials for digital forensics professionals and students. The project aims to harness the capabilities of large language models to create visually informative representations of the digital forensic investigation process,...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) 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 advancing vision-centric parametric knowledge, incorporating human-like non-parametric mechanisms, and...
This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $600,000 over 3 years to the University of South Carolina to develop techniques for detecting and mitigating harm in AI-generated vision and language models. The key technical objectives include: Developing a prompting framework to identify the provenance of harmful content in AI-generated multimodal content using knowledge graphs and techniques...
The National Science Foundation (NSF) awarded a $449,795 Project Grant under the Engineering program (CFDA 47.041) to the University of Pittsburgh. The 5-year award, effective May 1, 2024, aims to develop a bio-inspired sensing, computing, and learning framework for next-generation computer vision (CV) systems. The proposed research will focus on three key areas: 1) creating retina-inspired vision sensors that outperform existing cameras, 2) modeling and implementing scalable corticomorphic...