High dimensional computation is a new frontier in scientific computing, with applications
ranging from financial mathematics such as option pricing or risk management, to parameter
estimation, to groundwater flow, heat transport, and wave propagation. Often the difficulties
come from uncertainty or randomness in the data, and they present major challenges in the
areas of Data Science and Uncertainty Quantification. This workshop provides a forum for
interaction between international experts, with the aim to establish new collaborations.
Albert Cohen (Université Pierre et Marie Curie, Paris)
Ivan Graham (University of Bath)
Michael Griebel (University of Bonn)
Christoph Schwab (ETH Zürich)
Ian H. Sloan (University of New South Wales, Sydney)
Aretha Teckentrup (University of Edinburgh)
Raul Tempone (King Abdullah University of Science and Technology)
Stefan Vandewalle (KU Leuven)
In addition to the invited speakers, we will also have a small number of contributed talks.
On the Friday before the workshop, December 14, we will have 3 tutorials as an introduction on
computational methods for PDEs with random coefficients. These tutorials will be given by Anthony
Nouy (Ecole Centrale Nantes), Dirk Nuyens (KU Leuven) and Rob Scheichl (University of Bath).
Everybody is welcome to attend.
"Uncertainty Quantification - Efficient Methods for PDEs with Random Coefficients"
We have travel and accommodation support available for 8 PhD students at EUR600 each. Please encourage
suitable candidates to apply. They need to send a 1 page resume + 3 paragraphs of motivation + a support
letter from the supervisor to firstname.lastname@example.org
September 15. PhD students receiving travel and accommodation support must participate in the Friday