Project Grant 2535783
- This Project Grant award, valued at $503,930.00 and awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), supports the development of a wearable sensor network with distributed computing capabilities for advanced health monitoring and biomechanics analysis. The research aims to address key challenges associated with wearable technologies, such as limited computational power, battery capacity, data...
- The National Science Foundation awarded a $249,631 Project Grant to Temple University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support a three-year collaborative research project from July 2021 to June 2024 to develop graphical models for analyzing multivariate functional data. The Computer and Information Science and Engineering program aims to advance computing and communications research. This award will further those goals...
- 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...
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $200,000 Project Grant to Temple University to develop transformative machine learning and data analytics technologies for enabling AI-based applications on resource-constrained edge computing devices. The project aims to address gaps between the complexity of data and the limited computing resources on edge devices, as well as the need for robust predictive models across heterogeneous edge...
- This $227,886 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a novel deep sensor array decoding system for high-fidelity remote health monitoring. The project will leverage data-driven deep learning algorithms to decode weak and noisy signals captured remotely from the human body, without requiring a reference signal. By leveraging multi-sensor spatial information, the system will recover the signal of interest from...
- This $1,139,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop innovative dataflow processors that can enhance the energy efficiency and security of edge computing systems. The key technical innovations include a parallel dataflow representation of programs and a simplified, scalable spatial architecture for dataflow processors. The research will be conducted by a diverse team at...
- This National Science Foundation (NSF) Project Grant awarded to Virginia Polytechnic Institute & State University (Virginia Tech), totaling $600,000, supports the development of hardware and software for sustainable and efficient wearable edge intelligence. The project aims to address fundamental accessibility and sustainability challenges of wearable health monitoring devices and artificial intelligence services for underserved communities. Key research focuses include extending the...
- This National Science Foundation award of $247,721 provides funding under the Computer and Information Science and Engineering program (CFDA 47.070) to Arizona State University for a project titled "CAREER: Autonomous Wearable Computing for Personalized Healthcare." The project aims to develop foundations for computational autonomy in wearable-based health monitoring and interventions. Specifically, the university will investigate methods for automatically and autonomously labeling...
- This $318,500 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research to develop an accelerated computation architecture for system modeling techniques and apply them to critical smart environment applications. The key objectives of this 3-year project are to: 1) design efficient computation techniques to accelerate reachability computation in state transition representations,...
- The U.S. National Science Foundation (NSF) awarded a $120,120 CAREER grant under the Computer and Information Science and Engineering (CISE) program to The Johns Hopkins University. The project, titled "DEEPMATTER: A Scalable and Programmable Embedded Deep Neural Network", will develop novel methodologies for optimizing deep neural network (DNN) models to enable their deployment on embedded systems with limited hardware resources and power budgets. The research aims to create new DNN...
This federal Project Grant award of $226,848.00 was made on May 15, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The grant was awarded to Temple University to develop a new ultra-low-power architecture to enable energy-efficient wearable massive-sensor computers. Specifically, the project aims to leverage novel deep learning approaches to minimize power consumption of these sensor-rich wearable devices. This includes learning sensor data characteristics to activate only necessary sensors, and analyzing and compressing sensor data to further reduce power requirements. Real-world experiments will be conducted to evaluate the effectiveness of the proposed ultra-low-power architecture, which is expected to dramatically boost battery life, enhance usability, and improve long-term data capturing capabilities of wearable sensors. This research effort seeks to advance the deployment of wearable massive-sensor computers for big data-driven precision health applications.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $101.9k | 8/18/25 | ||
| Not listed | $124.9k | 7/17/25 |