Project Title	Geotechnical Data Fusion for Improving AI Subsurface Predictions
University	Pennsylvania State University
Principal Investigator(s)	Kaleigh Yost
Funding Source(s) and Amounts Provided (by each agency or organization)	Federal Funds, $62,026 Match, $62,027
Total Project Cost	$124,053
Start and End Dates	08/01/2024 - 07/31/2025
Brief Description of Research Project	Subsurface profile prediction using AI tools is perhaps most widely used for offshore applications6 and has yet to be widely adopted in mainstream geotechnical practice. Further, we are unaware of any research efforts to validate AI predictions of subsurface conditions using geophysical field data in geotechnical engineering. Thus, this project is novel, and the methodologies we will develop to assess the efficacy of, and ultimately improve, predicted subsurface conditions will be broadly applicable for other regions of the US (and world) and for other predictive algorithms. Geosetta is already partnered with over 16 DOTs throughout the US. Improvements made to their algorithms by inclusion of more data will automatically benefit DOTs nationwide. Further, as part of our technology transfer plan we will develop a project for an undergraduate class that incorporates the use of Geosetta, effectively training the future geotechnical workforce to responsibly use AI tools that will be available to them in practice. This will broadly benefit geotechnical practice, especially within the transportation industry where these tools are already being adopted.