AI-Enabled Model Integration

Scientists are frequently asked to provide models and simulations about complex systems from weather and climate to disease transmission but they may not accurately reflect on-the-ground circumstances. Research scientists at UT's Texas Advanced Computing Center are developing new technologies that can combine and analyze data in new ways and make more accurate predictions. The project will include a first-of-its-kind model that interlaces hurricane projections with storm surge and flooding models in a dynamic, interactive. These can be applied at a large, region-wide scale, allowing faster, better-informed decisions for people to deal with both sudden disasters like flash floods and storms as well as more gradual change such as drought conditions and increasing temperatures. Long term, this project seeks to design an artificial intelligence-enabled modeling framework that becomes the de facto example of how data and community feedback can be integrated to inform decisions in real-time.

 

 

Team Members


Suzanne Pierce
Texas Advanced Computing Center
Clint Dawson
Oden Institute
Katy Brown
Oden Institute and Molecular Biosciences
Michael Shensky
UT Libraries
Lissa Pearson
Texas Advanced Computing Center
Kelly Pierce
Texas Advanced Computing Center
Anna Dabrowski
Texas Advanced Computing Center
Je'aime Powell
Texas Advanced Computing Center
Eirik Valseth
Oden Institute
Dev Niyogi
Geological Sciences and Civil, Architectural, and Environmental Engineering