Grant Awarded for Machine Learning Approaches for Safe Geothermal Exploration

Jing Yang and Chris Marone, professors of electrical engineering and geosciences respectively, were awarded a 2019 Penn State Multidisciplinary Seed Grant for collaborative research on "Machine learning approaches for safe geothermal exploration".  Machine learning (ML) the study of algorithms and statistical models used by computers to perform tasks based on patterns and inference rather than with explicit instructions, will be paired with real energy-related applications, learning to better predict seismic activity during geothermal exploration.

The complete article can be found at Penn State News.