Project Grant 2213985
- The National Science Foundation (NSF) awarded a $319,556 Project Grant under the Computer and Information Science and Engineering (CISE) program to The Research Foundation for the State University of New York (RF-SUNY) at the University at Albany. The project aims to advance computational modeling of autism spectrum disorder (ASD) through multimodal data collection, fusion, and phenotyping. The research team will integrate behavioral data (e.g. eye tracking, audio/video) with neuroimaging data...
- This Project Grant award of $208,888.00 from the National Institute of Mental Health (CFDA 93.242 - Mental Health Research Grants) supports research to develop computer vision techniques for identifying autism spectrum disorder (ASD) motor deficits in infants. The Washington University project aims to leverage deep learning and computational ethology to automatically extract and analyze kinematic data from video assessments of infant behavior, with the goal of creating objective, scalable...
- The National Science Foundation (NSF) awarded a $1,025,097 Project Grant under the Computer and Information Science and Engineering (CISE) program to The Leland Stanford Junior University (Stanford University) on August 15, 2025. The funding supports the development of deep learning models to analyze video data from a social video game called "GuesswWhat" in order to provide early, accurate, and accessible autism risk assessments for children under 6 years old. The project aims to...
- This National Science Foundation (NSF) Engineering Research Initiation (ERI) project grant, under CFDA 47.041, is awarded for $200,000 to the University of the Pacific to develop a novel wearable sensing and analysis system for early detection of autism spectrum disorder (ASD) in young children and toddlers. The research aims to leverage non-invasive wearable devices to collect physiological and environmental data, and then use machine learning to identify physiological biomarkers and early...
- This Project Grant award, provided under the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070), seeks to co-design an AI-based solution for collecting and analyzing behavior data to support coordinated care for children with autism spectrum disorder (CWA). The University of Texas at San Antonio (UTSA), the prime awardee, will partner with community stakeholders in a pilot study in San Antonio, TX to develop an AI-augmented platform for CWA...
- This $200,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop the mathematical and statistical foundations for a Digital Twin (DT) system to enhance neurophysiological modeling and uncertainty quantification for individuals with Autism Spectrum Disorder (ASD). The key products and services to be delivered include: Computational models based on Conditional Variational Auto-Encoders (CVAE) and longitudinal CVAE to analyze brain...
- The National Science Foundation (NSF) awarded a $149,996 Project Grant under the STEM Education (formerly Education and Human Resources) (CFDA 47.076) program to the University of Alabama Office for Sponsored Programs Division. The purpose of this project is to establish a partnership between the university and the local community organization Arts N' Autism to develop and deliver informal computer science learning opportunities, specifically focused on robotics and coding, for children and...
- This $266,028 Project Grant was awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) to Ball State University in Muncie, Indiana. The grant will fund a collaborative research project to (i) discover evidence linking daylight and behavioral responses in autism educational settings, and (ii) develop and implement guidelines for inclusive indoor environments that harness the benefits of natural light for children with autism spectrum disorder (ASD). The...
- This Project Grant award of $431,750 from the National Institute of Child Health and Human Development (NICHD) under the Child Health and Human Development Extramural Research program (CFDA 93.865) aims to develop algorithms using advanced machine learning models that can predict outbursts in children with autism spectrum disorder (ASD). The key products and services to be delivered under this 2-year award, which runs from July 2025 to June 2027, include: Collecting a novel dataset on the...
- This Cooperative Agreement award from the National Science Foundation's Technology, Innovation, and Partnerships program (CFDA 47.084) provides $1 million to Itherapy, LLC of Martinez, California to develop an evaluative artificial speech intelligence and autism screener system called EASI-AS. The system aims to improve treatment for children with communication impairments by providing specialists and parents with accurate, efficient reports on speech and language evaluations along with...
The University of Louisville received a $249,995 Project Grant from the National Science Foundation to develop an artificial intelligence-enabled software framework for the automatic identification of genetic and neuroimaging markers of Autism Spectrum Disorder. The goal is to reduce the age of diagnosis to approximately six months and provide a detailed profile of where individuals fall on the autism spectrum. The proposed computer-assisted diagnostic system will analyze brain structure and other medical information from children at risk for ASD using deep machine learning models trained on a retrospective cohort imaged prior to age one who were later diagnosed with autism. Validation will utilize an independent dataset. If successful, this system has the potential to significantly reduce the time and $5,000-$7,000 cost of a standard clinical diagnosis while providing pediatricians and other specialists with objective metrics to better communicate findings and tailor treatment plans. The award aligns with the National Science Foundation's Technology, Innovation, and Partnerships program mission to advance breakthrough technologies addressing national challenges through research and innovation.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 7/15/22 |