Posted on: 24 September 2019
We are pleased to announce that the TU Delft Institute for Computational Science and Engineering (DCSE) will host a Fall School featuring introductory and advanced courses on reduced-order modeling and uncertainty quantification with applications of engineering interest. The topics covered during the lectures will range from Bayesian inference, sampling methods, adjoint approaches, adaptive methods, and use of reduced-order methods to enable efficient UQ analyses. Special emphasis will be given to the intuitive understanding of the material, with possibly some hands-on exercises and tutorials, to help students appreciate the widespread use of the presented techniques.
A certificate will be provided to all participants after completion of the Fall School.
Olivier Le Maître (CMAP, CNRS, Ecole Polytechnique, France)
Zoltan Perko (TU Delft, The Netherlands)
Serge Prudhomme (Polytechnique Montréal, Canada)
Rob Remis (TU Delft, The Netherlands)
Raúl Tempone (TU Aachen, Germany)
The lectures will be organized into two sessions per day, from 9:00 am to 12:00 noon and from 2:00 pm to 5:00 pm, each day of the week and will cover the following topics:
Olivier Le Maître: “Bayesian inference (1h), Reduced-order modeling for Bayesian inference (2h), Markov Chain Monte Carlo sampler (2h), advanced topic (1h)”.
Zoltan Perko: “Adjoint techniques (3h) and spectral methods (3h)”.
Serge Prudhomme: “Reduced-order modeling (3h) and adaptive methods (3h)”.
Rob Remis: “Model-order reduction techniques for waves and fields in complex media (6h)”.
Raúl Tempone: “Multi-level and multi-index Monte Carlo methods (6h)”.
Ph.D. students, post-docs, early-career researchers, etc.
November 4-8, 2019
Delft University of Technology
X TU Delft
Room: Dance Studio A
2628 CD Delft
For registration please visit:
Fees for TU Delft students/participants and non-TU Delft participants are € 100 and € 300, respectively. Registration for DCSE students is free subject to available seating.
For additional information and registration, please contact Berna Torun (B.Torun@tudelft.nl) or Deborah Dongor (D.M.Dongor@tudelft.nl).