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Scientific Computing and Data Science Seminar

October 8, 2019 - 10:00am

Speaker: Cosmin Safta (Sandia National Laboratories)

Title: Uncertainty Quantification and Machine Learning Algorithms for Physical Models - Tackling Computational Expense and High-Dimensionality

Description: This presentation will focus on analysis workflows for quantifying uncertainty in physical systems. In this context I will describe challenges posed by the computational cost and high-dimensionality associated with applications of interest to DOE (Earth System Model, Atmospheric Transport Models) and DoD (Scramjet Engine). I will outline algorithmic developments adapted to each application including both supervised and unsupervised sparse learning techniques.


ACS 362B