2026–2027 IAIER Seed Grant Funding Awardees

Principal Investigator: Asha Ralph

This qualitative study uses focus groups to examine how HBCU students perceive the benefits, concerns and barriers associated with responsible AI use in higher education. Findings may inform institutional policies, faculty practices and future approaches to supporting students' effective and ethical use of AI.

Principal Investigator: Grace Hao
Co-Principal Investigator: Siobhan Day Grady

This pilot project examines how family functioning relates to identity development and mental health among gender-diverse and neurodiverse youth. It will also evaluate a digital platform that provides participants with real-time summaries, tailored resources and data-informed feedback.

Principal Investigator: Jonathan Schultz

This project develops interpretable machine-learning methods to analyze volatile organic compounds in exhaled breath for lung disease screening. The team will build a curated training database, separate molecular signals from noise and release open-source tools that support more accurate, affordable diagnostics.

Principal Investigator: Kevin P. Williams
Co-Principal Investigator: Weifan Zheng,  Xiaojia Ji and Michael Tarpley

This project combines artificial neural networks and retrieval-augmented generation to accelerate drug discovery for inflammatory breast cancer. The system will screen compounds, connect predicted results with disease and clinical evidence, and produce ranked candidates for future study.

Principal Investigator: Lance Hulme

Cave of Dreams is an immersive, AI-enabled installation that transforms cultural data into responsive sound environments shaped by each visitor. The project explores audio-led, real-time storytelling and will develop a transferable approach for education, public engagement and community-based cultural initiatives.

Principal Investigator: Manoj Prasad

This project will develop an AI-driven platform to identify small molecules that may regulate mitochondrial oxidative stress pathways linked to Alzheimer's disease. By combining machine learning with biochemical and pharmacological data, the research will prioritize promising candidates for future therapeutic study.

Principal Investigator: TaVshea Smith

This project establishes a pilot AI literacy professional development program for preservice early childhood educators. Through structured learning experiences and classroom partnerships, participants will develop the pedagogical knowledge and ethical frameworks needed to integrate AI meaningfully into early childhood learning.

Principal Investigator: Zhiming Yang

This project uses machine learning, satellite-derived aerosol data and weather information to estimate seasonal PM2.5 concentrations in North Carolina counties without ground monitoring stations. The models will be validated against measurements from PurpleAir monitors and support expanded air-quality monitoring.