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101-0190-08L 3 Credits DR D-MAVT , D-BAUG
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Uncertainty Quantification and Data Analysis in Applied Sciences

Lecturers: Prof. Dr. Eleni Chatzi
Examiners: Prof. Dr. Eleni Chatzi, Prof. Dr. Konstantinos Papadimitriou, Dr. Stefano Marelli, Dr. Vasileios Ntertimanis, Dr. Maliki Moustapha, Dr. Antonios Kamariotis
Does not take place this semester. Open to doctoral students from within ETH and UZH who work in the field of Computational Science. External graduate students and other auditors will be allowed by permission of the instructors.
VVZ CR n/a

Last Updated: 2026-06-01 11:33:17

Abstract

The course 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.

Objective

This 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.

Content

The topics to be covered are organized in three broad categories: Track 1: Uncertainty Quantification and Rare Event Estimation in Engineering, offered by the Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich (18 hours) Lecturers: Dr. Stefano Marelli, Dr. Maliki Moustapha Track 2: Bayesian Inference and Uncertainty Propagation, offered the by the System Dynamics Laboratory, University of Thessaly, and the Chair of Structural Mechanics and Monitoring, ETH Zurich (18 hours) Lecturers: Prof. Dr. Costas Papadimitriou, Dr. Antonios Kamariotis, Dr. Konstantinos Tatsis, Giacomo Arcieri Track 3: Data-driven Identification and Simulation of Dynamic Systems, offered the by the Chair of Structural Mechanics and Monitoring, ETH Zurich (18 hours) Lecturers: Dr. Vasilis Dertimanis, Prof. Dr. Eleni Chatzi The lectures will be complemented via a comprehensive series of interactive Tutorials.

Resources

Lecture Notes

The course script is composed by the lecture slides, which will be continuously updated throughout the duration of the course on the CSZ website.

Literature

Suggested Reading: Track 2 : E.T. Jaynes: Probability Theory: The logic of Science Track 3: T. Söderström and P. Stoica: System Identification, Prentice Hall International, Link see Learning Materials. Xiu, D. (2010) Numerical methods for stochastic computations - A spectral method approach, Princeton University press. Smith, R. (2014) Uncertainty Quantification: Theory, Implementation and Applications SIAM Computational Science and Engineering, Lemaire, M. (2009) Structural reliability, Wiley. Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M. & Tarantola, S. (2008) Global Sensitivity Analysis - The Primer, Wiley.

Learning Materials (Links)

General Information

Language
English
Levels
DR
Frequency
Every two years

Examination

Type
ungraded semester performance

Course Components

Type Title Time & Place Hours
lecture with exercise Uncertainty Quantification and Data Analysis in Applied Sciences
Does not take place this semester. Block course
No time listed 54 h semesterly

Offered In