UNCERTAINTY QUANTIFICATION

Credit Hours: 3 · Graduate

This course introduces a series of computational methods in Uncertainty Quantification (UQ), a field of growing importance across various engineering domains and beyond. Focusing on mathematical theories and numerical methods, the course will cover global sensitivity analysis, multi-fidelity Monte Carlo, and probabilistic machine learning (“surrogate”) models, such as Gaussian process and polynomial chaos expansion, with advanced topics of active learning and dimensionality reduction techniques. Graduate/Undergraduate Equivalency: CEVE 456 . Mutually Exclusive: Cannot register for CEVE 556 if student has credit for CEVE 456 .