This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $1,550,000.00 to President and Fellows of Harvard College (Harvard University) aims to develop a bio-symbiotic system for advanced computation by integrating artificial intelligence (AI) agents with brain organoids through neuron-soft, high-density, three-dimensional (3D) bioelectronics. The project will implement the following key technical thrusts: (A) developing neuron-soft bioelectronics with over...
This Project Grant award of $200,000 from the National Science Foundation's STEM Education (47.076) program aims to promote AI readiness and democratize AI technologies for a broad spectrum of advanced cyberinfrastructure users and researchers. The key products and services provided under this 4-year award, which began on September 1, 2023, include: Developing a comprehensive suite of experiential learning modules, including flexible micro-modules and immersive extended reality experiences, to...
This $494,313 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program aims to create a multidisciplinary network of researchers to explore the potential and challenges of new technologies in fostering collective learning. The project will develop a theoretical framework to guide the design of technology-enhanced learning environments, create tools to study collective learning, and design technological platforms that...
This $299,738 federal Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program is focused on using machine learning (ML) to analyze the socioeconomic impacts of place-based innovations, with a specific emphasis on understanding the effects on socially vulnerable populations. The project aims to develop scalable ML models that can quantify the impacts of NSF's Regional Innovation Engines (NSF Engines) investments in New York...
This $452,604 Project Grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) supports the development of a large foundational artificial intelligence (AI) model for advanced seismic data analysis to revolutionize the field of earthquake science. The project, led by the President and Fellows of Harvard College, aims to train the AI model on a vast archive of seismic data to identify and characterize earthquake signals, utilizing cutting-edge techniques like...
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 $247,811 Project Grant award from the National Science Foundation (NSF) Engineering Directorate (CFDA 47.041) supports research at Oberlin College to develop and test AI programming tools to assist scientists in writing computer programs for scientific research. The goal is to create AI models and tools that can help scientists, who are not expert programmers, be more productive and improve the reproducibility of scientific work. Key products and services include developing large language...
This $127,000 federal Project Grant award from the National Science Foundation (NSF) STEM Education program (CFDA 47.076) will fund the development of comprehensive educational modules and software-based labs to prepare students and future engineers to address security vulnerabilities in artificial intelligence (AI) and machine learning (ML) systems. The key products to be delivered under this 3-year award include: Practice-in-the-loop learning experiences for students to understand security...
The National Science Foundation (NSF) awarded a $299,635 Project Grant under the Technology, Innovation, and Partnerships (CFDA 47.084) program to the University of Texas at Arlington (UTA) for a project titled "POSE: PHASE I: SCOPING AND PLANNING FOR AN OPEN-SOURCE ECOSYSTEM OF MACHINE LEARNING MODELS THAT SELECT TEXTS FOR RESEARCH PURPOSES". This grant supports scoping and planning activities to transition an academic research artifact - machine learning software that identifies...
This $100,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to create an infrastructure for benchmarking and holistically evaluating large language models (LLMs) for software engineering applications. The key objectives are to: Conduct a survey, interviews, and a workshop to gather requirements and gauge interest from the software engineering and machine learning communities for such...
This $738,226 federal Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program aims to establish an open-source ecosystem (OSE) that will revolutionize machine learning (ML) for scientific discovery. The project, led by the President and Fellows of Harvard College, will leverage the existing MLCommons community to develop and apply foundation models for science. Key objectives include creating benchmarks, datasets, and models for ML research, as well as offering courseware, training, and documentation to democratize artificial intelligence (AI) technologies. A sub-award to the University of Virginia will oversee curation and integration of the OSE artifacts, ensuring open-source accessibility through a curated MLCommons Research GitHub repository. This initiative seeks to expand the community of scientific contributors, address the shortage of AI talent, and enable diverse users to construct custom AI systems to drive scientific breakthroughs, improve public health, and enhance national competitiveness.