Project Grant 2122220
- 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 $599,573 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports the University of Notre Dame's research to develop a new machine learning paradigm for effective yet efficient foundation graph learning models (FGLMs). The project aims to create techniques, methods, and models for FGLMs that can be widely applied in areas like scientific research, social network analysis, anomaly detection, drug...
- The National Science Foundation awarded a $515,999 Project Grant to the University of Notre Dame under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to develop comprehensive methods for learning to augment graph data through machine learning algorithms. Over a three-year period from March 2022 to February 2025, the University will deliver novel techniques to augment graph data by counterfactual inference on edges as treatment variables, forecasting...
- 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...
- The National Science Foundation (NSF) awarded a $175,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of North Carolina at Charlotte. The project, titled "CRII: CSR: ENABLING ON-DEVICE CONTINUAL LEARNING THROUGH ENHANCING EFFICIENCY OF COMPUTING, MEMORY, AND DATA", aims to develop an efficient on-device continual learning framework that can incrementally learn new knowledge without forgetting prior learnt knowledge, while...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award, with a total funding of $174,770, supports the development of an adaptive, federated, continuous learning system that uses a novel federated, semi-supervised learning framework. This framework aims to retrain deep neural network models on distributed, unlabeled, heterogeneous data from edge devices, while leveraging explainable AI techniques to expedite local training. The...
- This $499,861 National Science Foundation project grant under the Computer and Information Science and Engineering program (CFDA 47.070) supports the development of real-time, scalable and secure collaborative intelligence capabilities at the edge. Wayne State University is the primary awardee and will work with sub-awardee University of Delaware to implement collaborative learning algorithms enabling distributed, privacy-preserving training across edge devices for multi-target tracking...
- This Project Grant from the National Science Foundation Division of Information and Intelligent Systems provides $190,070 to the University of Notre Dame du Lac from September 2021 through August 2024. The grant supports research to advance online STEM learning through augmenting accessibility with explanatory captions and artificial intelligence. Specifically, the University of Notre Dame du Lac will conduct collaborative research under the Computer and Information Science and Engineering...
- This five-year, $199,995 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop a co-designed framework of hardware, software, and algorithms enabling extreme-scale machine learning systems for emerging artificial intelligence of things and internet of senses technologies. Specifically, the Saint Louis University team will pursue five research thrusts: developing hardware and compiler approaches for large-scale split learning...
- This National Science Foundation project grant of $600,000 supports research through June 2025 at the University of Notre Dame under the Office of International Science and Engineering program (CFDA 47.079). The grant funds a partnership between researchers at Notre Dame and Ecole Centrale de Lyon in France to study the impact of emerging information processing technologies on computer architectures and applications. Specifically, the researchers will examine how new architectures enabled by...
This three-year Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $299,999 to the University of Notre Dame for research titled "TOWARDS UNSUPERVISED LEARNING ON RESOURCE CONSTRAINED EDGE DEVICES WITH NOVEL STATISTICAL CONTRASTIVE LEARNING SCHEME." The funding period is from October 1, 2021 through September 30, 2024. The grant supports the development of unsupervised learning techniques that can operate on resource-constrained edge devices with limited processing and memory capabilities. Specifically, the University of Notre Dame researchers will investigate novel statistical contrastive learning schemes to enable unsupervised learning directly on edge devices without transferring data to cloud servers. The goal is to advance privacy-preserving artificial intelligence that keeps user data localized to edge devices.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $50.0k | 3/8/23 | ||
| Not listed | $250.0k | 7/21/21 |