This Project Grant award, valued at $348,227.00, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The award aims to improve the scalability and effectiveness of healthcare-focused large language models (LLMs) by developing methods to evaluate and mitigate issues with incomplete data. The key products and services to be delivered include: An evaluation framework to address factual and faithfulness...
This $400,000 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 a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models. The key objectives are to: 1) create new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2) explore model...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $518,693 to the University of Rhode Island to develop an integrated framework for recording and decoding multimodal neural associations of visual hallucinations and motor functions in Parkinson's disease. The project aims to leverage electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and virtual reality to investigate the interaction between electrocortical and...
This $1,309,500 Project Grant awarded by the National Institutes of Health (NIH) under the Trans-NIH Research Support (CFDA 93.310) program supports the development of a novel digital psychiatry diagnostic framework that utilizes crowdsourcing algorithms to improve the specificity of machine learning models in distinguishing between autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) in adolescents. The key products and services to be delivered under this 3-year...
This Project Grant award of $425,875.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at The Leland Stanford Junior University (Stanford University) to develop novel computational and statistical methods for analyzing high-dimensional neural and behavioral data. The key objectives of this 5-year project are to: 1) develop state space models (SSMs) to better understand how brain activity changes...
This Project Grant award for $370,687 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a multiscale modeling framework to analyze brain structure and function, with a focus on understanding atypical neural activity in autism. The project aims to: 1) implement a multiscale forward model integrating cellular mechanisms and whole-brain dynamics using spiking neural networks and neural masses, 2)...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to understand the effects of large language models (LLMs) on the work of online information professionals. The $370,692 award, which runs from June 2025 to May 2030, will develop models and tools to help these professionals assess and manage the risks posed by LLM-generated content, which can sometimes contain false or misleading information....
This $400,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The project aims to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models, in order to increase the accountable and safe use of these advanced AI systems and mitigate potential harms. The key research thrusts involve: 1) new...
This $317,591 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance personalized healthcare through the use of large language models (LLMs) and novel memory semiconductor devices. The project aims to develop efficient retrieval-augmented generation (RAG) techniques for LLM personalization, focusing on reducing latency and hardware overhead through algorithm-hardware...
This $300,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research to develop brain-machine interfaces for speech decoding. The project aims to restore the ability to communicate through speech for individuals who have lost it due to conditions like ALS, stroke, or traumatic brain injury. The key objectives are to collect large amounts of intracranial electroencephalography...