The National Science Foundation (NSF) awarded a $597,292 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the Research Foundation of the City University of New York (RFCUNY) - Hunter College to improve the long-term reliability and evolvability of machine learning (ML) systems. This 3-year project will develop methodologies and automated refactoring techniques to address technical debt in ML systems, which can negatively impact the...
The National Science Foundation awarded a $666,000 Project Grant to The Trustees of Columbia University in the City of New York (Columbia University) through the Computer and Information Science and Engineering Program (CFDA #47.070). The objective is to improve the performance, robustness, generalizability, and efficiency of deep learning models for software assurance tasks such as bug detection, debugging, test input generation, and test suite prioritization. The research focuses on encoding...
The National Science Foundation (NSF) has awarded a $533,995 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Iowa State University of Science and Technology (Iowa State University). The 4-year grant, spanning from October 1, 2023 to September 30, 2027, aims to improve the performance, robustness, generalizability, and efficiency of deep learning models for critical software assurance tasks such as bug detection, debugging, test input...
The National Science Foundation (NSF) awarded a $299,993 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Chicago. The grant supports a collaborative research project on the "Foundations of Few-Round Active Learning" in supervised machine learning. The key objectives are to advance active learning algorithms and improve understanding of their capabilities in scenarios with limited interaction rounds. The research aims...
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 $100,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop a holistic benchmarking infrastructure for evaluating large language models used in software engineering. The key activities include: Conducting surveys and interviews with the software engineering and machine learning research communities to gather requirements and understand barriers in evaluating large language models for code....
The National Science Foundation (NSF) awarded a $800,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Illinois Urbana-Champaign. The 3-year grant, effective September 1, 2024, focuses on enhancing the safety of large language models (LLMs) used in high-stakes applications. The project aims to develop quantifiable safety measures and algorithms to detect and mitigate unsafe behaviors in LLMs, such as providing false or...
This $242,024 Project Grant awarded by the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) to Carnegie Mellon University (CMU) focuses on improving the reliability and efficiency of machine learning (ML) models for detecting malicious software (malware). The project aims to develop new techniques to make ML-based malware detectors more resistant to being fooled by attackers, as well as more time- and space-efficient. Key innovations include novel...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...
This $799,368 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) will support the University of Illinois in developing AI systems that can learn from and exceed the capabilities of human demonstrations. The key products and services to be delivered through this 3-year award include: Reformulating imitation learning methods for AI systems that are more capable...