Sebastian Geyer, M.Sc.

Room: N3625

Phone: +49 89 289 23010

E-Mail: s.geyer@tum.de

Office hours: Wednesday 15:00-17:00

Curriculum Vitae

  • since 2017: Ph.D. student at the Engineering Risk Analysis Group, Technische Universität München
  • 2016 - 2017: Research Assistant at the Engineering Risk Analysis Group, Technische Universität München
  • 2014 - 2016: M.Sc. in Civil Engineering, Technische Universität München
  • 2010 - 2013: B.Sc. in Civil Engineering, Technische Universität München

Research

  • Reliability analysis of aged hydraulic structures
  • Advanced sampling methods for reliability analysis
  • User-oriented random field representation methods for spatially varying material properties
  • Correlation models for spatially variable concrete properties using real data
  • Bayesian updating of engineering models with spatially variable properties​

Teaching

  • Since SS18: Teaching assistant for the lecture "Estimation of rare events and failure probabilities", TUM
  • Since WS16/17: Teaching assistant for the lecture “Zuverlässigkeit und Lastannahmen”, TUM
  • SS17: Teaching assistant for the lecture "Advanced Stochastic Finite Element Methods", TUM

Supervised theses/projects

  • Master's thesis: Melina Rohne (2019) - Visualization of random fields and their influence on modeling uncertainties in reliability analysis
  • Bachelor's thesis: Matthias Rosa (2019) - Analysis of different correlation models for spatially variable concrete properties in massive hydraulic structures
  • Master's thesis: Emily Schran (2018) - Sequential importance sampling with a flexible mixture model
  • Bachelor's thesis: Michael Maier (2017) - The effects of stochastic loads on a structural model

Publications

  • Sebastian Geyer, Iason Papaioannou, Claus Kunz, Daniel Straub (2019). Bayesian reliability assessment with spatially variable measurements: The spatial averaging approach. Proceedings of the 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13). Seoul, South Korea
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub (2019). Cross entropy-based importance sampling using Gaussian densities revisited. Structural Safety, 76, 15-27
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub, Claus Kunz (2018). Reliability assessment of large hydraulic structures with spatially distributed measurements. Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE). Ghent, Belgium
  • Arslan Tahir, Claus Kunz, Sebastian Geyer, Daniel Straub (2018). Investigation into structural reliability of reinforced concrete hydraulic structures using different probabilistic methods. Proceedings of the International Federation for Structural Concrete 5th International fib Congress, Melbourne, Australia
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub (2017). On the efficiency of cross entropy-based importance sampling with Gaussian densities. Proceedings of the 15th International Probabilistic Workshop & 10th Dresdner Probabilistik Workshop. Dresden, Germany

Talks

  • Sebastian Geyer, Iason Papaioannou, Claus Kunz, Daniel Straub (2018). Reliability assessment of large hydraulic structures including random fields and measurement data. 3rd International Conference on Vulnerability and Risk Analysis and Management (ICVRAM); 7th International Symposium on Uncertainty Modelling and Analysis (ISUMA); 4th International Symposium on Uncertainty Quantification and Stochastic Modeling (UNCERTAINTIES). Florianopolis, Brazil
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub (2017). Die Cross-Entropy-Methode in der Zuverlässigkeitsanalyse. SOFiSTiK AG, Oberschleißheim, Germany
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub (2017). Modified cross entropy-based importance sampling with a flexible mixture model (Poster). Frontiers of Uncertainty Quantification in Engineering (FRONTUQ). Munich, Germany.
  • Sebastian Geyer, Iason Papaioannou, Daniel Straub (2017). Gaussian densities in the cross entropy method for reliability analysis. International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP). Rhodes, Greece