معرفی
Parisa Shokouhi is an Associate Professor in the Department of Engineering Science and Mechanics at the College of Engineering, Penn State. Her research focuses on leveraging artificial intelligence and machine learning techniques to analyze acoustic data, with applications in geophysics and energy engineering.
Current projects include developing a wave physics-informed deep learning framework for acoustic data analysis, exploring machine learning approaches to predict induced seismicity and image geothermal reservoir properties, rapid forecasting of CO2 flow using machine learning, and evaluating technology pathways for imaging rock properties. These projects are supported by the College of Engineering at Penn State and the U.S. Department of Energy's National Energy Technology Laboratory (NETL) through Leidos, Inc.
Her work integrates data fusion and physics-informed deep learning to address complex engineering challenges in energy systems and geophysical imaging.
