New Research Aims to Fix Machine Learning’s Struggle with Uncertainty

  • UT Austin PI: Tan Bui-Thanh
  • Funding Source: National Science Foundation's Office of Advanced Cyber Infrastructure, the Office of Fusion Energy Sciences' Machine Learning (ML) and Artificial Intelligence (AI) for Fusion Energy Sciences program with Los Alamos National Lab, and the Oakridge National Lab
  • Award: Three grants total more than $1M
  • Award Date: 2023 (various dates)

These grants will support the development of scientific machine learning models that take into account uncertainty and use underlying governing mathematical models to fill in data gaps, the same way our brains do. The result is the ability to use limited information and physics laws to create machine learning models that are able to do as much or even faster than real-time processing and predicting than models that rely on only the governing physics or that are purely data-driven. Learn more.