## About this book

### Introduction

The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.

### Keywords

Polynomial Chaos Risk Analysis Risk Models Sensitivity Analysis Uncertainty Quantification

### Editors and affiliations

- Roger Ghanem
- David Higdon
- Houman Owhadi

- 1.Viterbi School of EngineeringUniversity of Southern CaliforniaLos AngelesUSA
- 2.Los Alamos National LaboratoryLos AlamosUSA
- 3.California Institute of Technology PasadenaUSA

#### About the editors

Roger Ghanem is the Gordon S. Marshall Professor of Engineering at the University of Southern California where he holds joint appointments in the Departments of Civil & Environmental Engineering and Mechanical & Aerospace Engineering.

David Higdon is Scientists and Group Leader in Statistical Sciences at Los Alamos National Laboratories. He has developed statistical concepts and methodologies that are uniquely adapted to modeling and simulation and computationally intensive numerical models

Houman Owhadi is a Professor of Applied & Computational Mathematics and Control & Dynamical Systems at the California Institute of Technology.

### Bibliographic information