Uncertainty Quantification in Engineering & Applied Sciences

Semester dates

Takes place every other year (last occurence: Spring 2022)
10:00-17:00
Online via Zoom
Timetable

Abstract

Uncertainty quantification & data analysis in applied sciences is a 9 day block course for doctoral students of which our Chair teaches the first 3 days. It presents fundamental concepts and advanced methodologies for handling and interpreting data in relation with models. It elaborates on methods and tools for identifying, quantifying and propagating uncertainty through models of systems with applications in various fields of Engineering and Applied science.

Lecturers

The course is taught jointly by three groups

Objectives

The course is offered as part of the external page Computational Science Zurich (CSZ) graduate program, a joint initiative between ETH Zürich and University of Zürich. This CSZ Block Course aims at providing a graduate level introduction into probabilistic modeling and identification of engineering systems.
Along with fundamentals of probabilistic and dynamic system analysis, advanced methods and tools will be introduced for surrogate and reduced order models, sensitivity and failure analysis, parallel processing, uncertainty quantification and propagation, system identification, nonlinear and non-stationary system analysis.