Uncertainty in Engineering

Louis Aslett is an Associate Professor in the Department of Mathematical Sciences at Durham University.  His main research interests span applied work in statistical machine learning and computational statistics, as well as methodological work in reliability theory and at the interface between cryptography and statistics. Threaded through this work is an interest in developing these statistical methods so that they are amenable to implementation in modern high performance computing architectures.Frank Coolen is a Professor in the Department of Mathematical Sciences at Durham University. His main research activities are in the theory and methods of statistics and reliability. He has developed methods in nonparametric predictive inference, a frequentist statistics methodology based on few assumptions made possible through the use of imprecise probability for uncertainty quantification. He has presented the survival signature as a powerful tool for system reliability.He has been on the editorial boards of several journals, including the Journal of Statistical Theory and Practice, Communications in Statistics, and the Journal of Risk and Reliability.  Jasper De Bock is an Assistant Professor in the Department of Electronics and Information Systems at Ghent University. He is also the current president of SIPTA  (the Society for Imprecise Probabilities: Theories and Applications). His research is concerned with the foundations of imprecise probabilities and their application to robust inference and decision making, with a particular focus on imprecise stochastic processes and choice functions.

• Introduction to Bayesian statistical inference.- Sampling from complex probability distributions: a Monte Carlo primer for engineers.- Introduction to the theory of imprecise probability.- Imprecise discrete-time Markov chains.- Statistics with imprecise probabilities – a short survey.- Reliability.- Simulation methods for the analysis of complex systems.- Overview of stochastic model updating in aerospace application under uncertainty treatment.- Aerospace flight modeling and experimental testing.