Project Grant 2400541

Award Date 6/15/24
Completion Date 5/31/27
Dollars Obligated $1.2M
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Cambridge, MA 02139, USA
Similar Awards
This $127,658 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) project grant awarded to Trustees of Boston University aims to develop new computational approaches and hardware designs to enable faster and more efficient motion planning for autonomous systems, such as robots. The key technical objectives are to: (1) create a library of hardware design flows for common motion-related computations, (2) establish intermediate representations and...
The Massachusetts Institute of Technology (MIT) received a three-year, $600,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070). The grant funds collaborative research to develop robotic perception and manipulation capabilities using full-spectral wireless sensing technologies. Specifically, the grant supports three interconnected research thrusts. First, MIT researchers will develop new terahertz frequency sensing...
The Massachusetts Institute of Technology (MIT) received a three-year, $175,000 Project Grant award from the National Science Foundation (NSF) to support research titled "COLLABORATIVE RESEARCH: CIF: SMALL: LOW-COMPLEXITY ALGORITHMS FOR UNSOURCED MULTIPLE ACCESS AND COMPRESSED SENSING IN LARGE DIMENSIONS" under the NSF's Computer and Information Science and Engineering program (CFDA #47.070). The grant will fund MIT investigator-initiated research from October 1, 2021 to September...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $202,082 to support a research project at Boston University that introduces a novel approach for robots to navigate unknown environments. The key technical aspects include: Developing compact, interpretable representations of the environment using structured elements extracted from sensor measurements and optimized over time. Synthesizing local and global...
The Massachusetts Institute of Technology (MIT) received a $1.2 million project grant award from the National Science Foundation Office of Advanced Cyberinfrastructure to support research activities under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will fund a collaborative research project between Aug 1, 2021 and Jul 31, 2025 to develop frameworks that converge Bayesian inverse methods and scientific machine learning in Earth system models...
This $622,431 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 energy-efficient computing systems for artificial intelligence (AI) and machine learning applications. The key technical aims include: Creating a vertical memcapacitor device that can be integrated into the backend of CMOS chip manufacturing for 3D integration; Developing memcapacitor-based in-memory computing...
This $330,000 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) supports collaborative research at the Massachusetts Institute of Technology (MIT) to accelerate the execution of large graph problems on large, distributed computing systems. The project aims to develop new algorithms, software frameworks, and specialized hardware to enable more efficient processing of graph...
The Massachusetts Institute of Technology (MIT) received a three-year $600,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) to develop algorithms that leverage structural properties in distribution testing. MIT will extend the reach of distribution testing through more efficient solutions that capitalize on known data structures. The university will also design sample-efficient methods to ascertain if data...
This $731,058 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop an energy-efficient hardware/software framework for on-chip implementation of deep neural networks (DNNs). The primary objectives are to: 1) Design and evaluate a radically innovative energy-efficient architecture that integrates processing elements within memory chips to significantly reduce DNN energy...
The National Science Foundation (NSF) awarded a $174,229 Project Grant under the Computer and Information Science and Engineering (CISE) program to Michigan Technological University. The grant, awarded on October 1, 2023, with a completion date of September 30, 2025, is focused on developing a self-learning neuromorphic robot system that can operate efficiently in resource-constrained environments. The key objectives of this research project are to: 1) create a neuromorphic robot that utilizes...

The National Science Foundation (NSF) awarded a $1,200,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the Massachusetts Institute of Technology (MIT) to develop energy-efficient computing hardware and algorithms for localization and mapping tasks in constrained cyber-physical systems. The project aims to design specialized chips that can perform these fundamental tasks in a fraction of the size, weight, and power of current state-of-the-art solutions. This research will enable greater autonomy for a diverse range of resource-constrained applications, including consumer electronics, robotics, and medical devices. The project also plans to create a new graduate course at the intersection of computer architecture, integrated circuits, and robotics, as well as an outreach program for high school students. The grant period runs from June 2024 to May 2027.

Generated 3/18/25, 4:36 AM