Bayesian Inverse Problems : Fundamentals and Engineering Applications

Juan Chiachio-Ruano

ISBN 10: 1138035858 / ISBN 13: 9781138035850

Published by CRC Press, 2021

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This book is devoted to a special class of engineering problems called Bayesian inverse problems. These problems comprise not only the probabilistic Bayesian formulation of engineering problems, but also the associated stochastic simulation methods needed to solve them.

Seller Inventory # 9781138035850

Bibliographic Details

• Title: Bayesian Inverse Problems : Fundamentals and Engineering Applications
• Publisher: CRC Press
• Publication Date: 2021
• Language: English
• ISBN 10: 1138035858
• ISBN 13: 9781138035850
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 18D millimeters 260 millimeters width by 183 millimeters height by 18 millimeters depth
• Weight: 672 grams

About this title

Synopsis

This book is devoted to a special class of engineering problems called Bayesian inverse problems. These problems comprise not only the probabilistic Bayesian formulation of engineering problems, but also the associated stochastic simulation methods needed to solve them. Through this book, the reader will learn how this class of methods can be useful to rigorously address a range of engineering problems where empirical data and fundamental knowledge come into play. The book is written for a non-expert audience and it is contributed to by many of the most renowned academic experts in this field.

About the Author

Juan Chiachío-Ruano is an Associate Professor of Structural Engineering at University of Granada (Spain), and a researcher at the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI). He has devoted his research career to the study and development of Bayesian methods in application to a wide range of Mechanical and Structural Engineering problems. Prior to joining University of Granada, he has developed a significant international research career working at top academic institutions in the UK and the USA.

Manuel Chiachío-Ruano holds a PhD in Structural Engineering (2014) by the University of Granada (Spain). Currently, he is Associate Professor and Head of the Intelligent Prognostics and Cyber-physical Structural Systems Laboratory (iPHMLab) at the University of Granada. He has developed a significant part of his research in collaboration with the California Institute of Technology (USA), the University of Nottingham (UK) and NASA Ames Research Center (USA), during his stays at these institutions.

Shankar Sankararaman received his PhD in Civil Engineering from Vanderbilt University, Nashville, TN, USA, in 2012. Soon after, he joined NASA Ames Research Center, where he developed Machine Learning algorithms and Bayesian methods for system health monitoring, prognostics, decision-making, and uncertainty management. Dr Sankararaman has co-authored a book on prognostics and published over 100 technical articles in international journals and conferences. Presently, Shankar is a scientist at Intuit AI, where he focuses on implementing cutting edge research in products and solutions for Intuit’s customers.