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Frist Center earns two large NSF grants to promote neurodiverse employment

Posted by on Tuesday, September 15, 2020 in News.

Frist Center grant recipients interacting with guests at the Center’s grand opening in July, 2019.

The National Science Foundation has awarded two highly competitive grants to Vanderbilt’s team working at the Frist Center for Autism and Innovation.

The first is a $5 million award that greatly expands a School of Engineering-led project for creating novel AI technology and tools and platforms that train and support individuals with Autism Spectrum Disorder in the workplace. The second is an NSF2026 EAGER project grant which enriches the NSF2026 Idea Machine winning entry, “Harnessing the Human Diversity of Mind.” It seeks to develop and evaluate integrated, AI-enabled technologies for measuring a person’s visuospatial cognitive skills in new ways and then using these measurements to predict performance on workplace-relevant tasks.

An autism self-advocate being “geared up” for Dr. Kunda’s visual perception study.

The first significant federal investment follows a successful $1 million, nine-month pilot grant to the same team that forged partnerships with employers and other stakeholders and produced viable prototypes through immersive, human-centric design. The multi-university team includes Yale University, Cornell University, Georgia Institute of Technology and Vanderbilt University Medical Center as academic partners. This grant, made through NSF’s Convergence Accelerator program, advances the School of Engineering’s focus on Inclusion Engineering,® which uses the disciplines within engineering to broaden meaningful participation for people who have been marginalized.

VR tech in use by an autistic adult at the Frist Center grand opening in July, 2019.

The second grant will include conducting a large pilot study with individuals on the autism spectrum and neurotypical individuals, in which participants will be given several visuospatial tests, and detailed data about their actions will be recorded using sensors such as eye trackers and cameras. Then, data mining and machine learning techniques will be used to extract meaningful patterns from these rich streams of behavioral data, and analyses will be conducted to examine how these patterns in foundational behaviors map onto individual skills and interests in realistic, workplace-relevant activities. This research will also gather and analyze detailed feedback from industry partners to identify specific job types and sectors that would benefit from recruiting employees who are strong in visuospatial cognitive skills. This project will involve neurodiverse students and staff in many of its activities, in particular by involving graduate trainees supported by the NSF Research Traineeship in Neurodiversity Inspired Science & Engineering (NISE) and by leveraging the skills of neurodivergent interns at the Frist Center.

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