Quantifying and reducing uncertainties in earth fluid models

Quantifying and reducing uncertainties in earth fluid models

Internship Description

Earth fluid models are subject to different sources of uncertainties. We will work on developing and implementing Bayesian inference approaches to quantify and reduce uncertainties in these models with focus on applications related to the coastal ocean, e.g. storm surges, tsunamis, oil spill, waves, etc. We envision using statistical and polynomial chaos-based techniques to build surrogate models that can be used to reduce the computational burden of the sampling step in the Bayesian inference. 

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Faculty Name

Ibrahim Hoteit, Omar Knio

Field of Study

Applied Mathematics, Earth Sciences and Engineering, or any related field