EPSCoR Research Fellows: NSF: Integrating GeoAI and Spatiotemporal Analytics to Model Demand, Supply, and Predictive Trends in the Engineering Workforce

This Research Infrastructure Improvement (RII) EPSCoR Research Fellows project provides a fellowship to an Associate Professor and training for a graduate student at the University of Arkansas. This work is conducted in collaboration with Emory University. Through the fellowship, the PI will study how employers’ needs for artificial intelligence skills in engineering differ across regions and change over time. The project will compare three kinds of information: engineering job openings, the number of engineering graduates, and business investments that may lead to future hiring. It will identify places where the supply of skilled engineers may not meet employer demand. The project will produce maps and an open-access career toolkit for engineering students, advisors, and educators. These resources will help users recognize emerging career opportunities and needed skills. The fellowship will strengthen research and training capacity in Arkansas and help colleges respond to changes in the engineering workforce. This project will develop a spatial workforce science framework to identify and forecast regional engineering skill gaps. Natural language processing and locally deployed open-source language models will extract and classify artificial intelligence-related technical, methodological, professional, and social competencies from longitudinal engineering job advertisements. The project will integrate three location-based data layers: employer demand from job postings, engineering graduate supply from the Integrated Postsecondary Education Data System, and industry investment as an indicator of future hiring. Data will be aligned at county and state levels and analyzed using spatial clustering, workforce-gap measures, and time-lagged forecasting. The resulting competency taxonomy, workforce-gap maps, and open-source computational workflows will advance research on technological change, education, and regional labor markets. The PI will continue and expand this research at the University of Arkansas. The fellowship will train a graduate research assistant, integrate methods into graduate courses, produce career-development resources for engineering programs, and sustain collaboration through publications and future grant proposals. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows (ERF). The ERF program supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.