Project Grant 2519216
- This federal Project Grant award of $493,388, awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, supports a collaborative research project titled "LANDS - Learning-Based Adaptive Networked Systems for Delivery of Short Videos." The project aims to improve the efficiency and understanding of short-video systems, which have become increasingly popular for delivering various types of content to billions of users globally....
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $496,895 over a 3-year period starting September 1, 2024 to develop a unified framework for simplifying and automating the development, optimization, and adaptation of video analytics pipeline (VAP) applications. The key products and services to be delivered under this grant include: A framework that enables domain experts to specify...
- This Project Grant award, valued at $341,618, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award was made to The Regents of the University of California, doing business as the University of California, Berkeley (UC Berkeley), with a performance period from June 15, 2025 to May 31, 2030. The project aims to develop a new foundational paradigm for understanding human behavior and...
- This $320,881 project grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program aims to improve the efficiency and understanding of short-video systems. The project, led by Brown University, will develop new video delivery techniques that use less compute and network resources, reduce energy consumption on user devices, and generate new analytical insights on short-video system behaviors. The expected outcomes include...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program provides $557,460 to the University of Texas at Austin (UT Austin) to advance the state of the art in generative visual AI systems. The key innovations include motion-adaptive cross-frame attention, pipelined frame scheduling for multi-GPU systems, formal verification of semantic consistency, and system-level validation on real hardware. These advancements are...
- This $660,000 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to advance multi-stream architectures in computer vision and artificial intelligence. The project aims to: (1) develop a suite of high-performance multi-stream foundation models for tasks like object detection, text-based image segmentation, and audio-video analysis; (2) optimize algorithms to enhance the efficiency of these...
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program totaling $174,604 is focused on advancing the field of robotic visual perception. The project aims to address critical limitations in current artificial intelligence systems, particularly their inability to generalize effectively to novel environments and human-centered interactions. To accomplish this, the project proposes two main thrusts: human-centered...
- This federal Project Grant award of $275,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, awarded on July 15, 2025, supports a collaborative research effort to develop advanced immersive video streaming technology. The project, led by the University of Illinois, explores techniques to enable users to see and interact with lifelike 3D environments, rather than just watching a flat video. By leveraging computer vision, computer...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, provides $499,556 to the University of Arkansas, Fayetteville to develop a trustworthy, robust, and efficient multimodal framework for video analytics. The project aims to tackle key challenges in artificial intelligence (AI) systems by creating a human-inspired AI framework that processes data similar to human perception. The framework will focus on...
- This $275,000 Project Grant was awarded on July 15, 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 a collaborative research project led by George Mason University that aims to revolutionize immersive video streaming technology using advanced neural content representation techniques. The key objectives of the project are to improve the resiliency, bandwidth optimization, and...
This Project Grant award of $600,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program aims to advance how machines interpret video content by developing new capabilities for analyzing extended video streams. The 3-year project, which runs from September 1, 2025 to August 31, 2028, will support research to address the extreme data volume inherent in long video sequences. The key technical focus is on a novel framework centered on token selection and context-aware representation to enable effective reasoning over long time horizons. The project integrates three core components: (1) a multi-resolution encoding strategy to balance detail and efficiency, (2) a content- and intent-aware selection process to filter out redundancy while preserving relevance, and (3) a reasoning module to enhance video understanding. This research is expected to drive progress in real-world applications such as interactive assistance, autonomous navigation, augmented reality, and content summarization.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 7/30/25 |