Description
Leader of the group Scientific Computing: Daan Crommelin.
The SC groups develops efficient mathematical methods to simulate and predict real-world phenomena with inherent uncertainties. Such uncertainties arise from e.g. uncertain model parameters, chaotic dynamics or intrinsic randomness, and can have major impact on model outputs and predictions. Our work is targeted in particular at applications in climate, energy, finance and biology. In these vital areas, the ability to assess uncertainties and their impact on model predictions is of paramount importance. Expertise in the SC group includes uncertainty quantification, data assimilation, stochastic multiscale modeling and risk assessment. The availability of data to inform and improve simulations and predictions, for example through learning and data-driven modeling, plays an important role in our research.
News
Quality guarantee for tomographic images developed
CWI researcher Wagner Fortes has developed new methods to determine the quality of tomographic images. Tomography is an imaging technique used in for instance medical CT scanners and electron microscopes that uses penetrating beams to record a series of two-dimensional images from a range of angles.
Kees Oosterlee new editor-in-chief of Journal of Computational Finance
Kees Oosterlee is the new Editor-in-Chief of The Journal of Computational Finance. This international refereed journal focuses on the advances in numerical and computational techniques in pricing, hedging and risk management of financial instruments. Oosterlee will be taking responsibility of selecting papers for the journal from the Fall 2013 issue and onwards.
Scientific Computing group nominated for Huibregtsen Prize
CWI’s research group Scientific Computing, led by mathematician Kees Oosterlee, is nominated for the Huibregtsen Prize 2013. The Huibregtsen Prize is granted for the best scientific research in the Netherlands that is remarkably innovative and has a valuable social impact.
CWI research nominated for Huibregtsen Prize
Research from CWI’s research group Scientific Computing, led by mathematician Kees Oosterlee, is nominated for the Huibregtsen Prize 2013.
Current events
PhD defence Anton van der Stoep (Scientific Computing)
- 2019-03-26T12:30:00+01:00
- 2019-03-26T13:30:00+01:00
PhD defence Anton van der Stoep (Scientific Computing)
Start: 2019-03-26 12:30:00+01:00 End: 2019-03-26 13:30:00+01:00
You are cordially invited to the public defence of Anton van der Stoep on his PhD thesis titled:
Pricing and Calibration with Stochastic Local Volatility Models in a Monte Carlo Setting
Promotor: prof. dr. C.W. Oosterlee (CWI, TU Delft)
Co-promotor: dr. ir. L.A. Grzelak (Rabobank, TU Delft)
- Email: Anton van der Stoep
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iCal
Combined CI/SC Seminar Cristóbal Bertoglio, Bernoulli Institute
- 2019-04-09T11:00:00+02:00
- 2019-04-09T12:00:00+02:00
Combined CI/SC Seminar Cristóbal Bertoglio, Bernoulli Institute
Start: 2019-04-09 11:00:00+02:00 End: 2019-04-09 12:00:00+02:00
Inverse problems in hemodynamics from MRI
We will present recent advances and future challenges in the field of data-based mathematical modeling of blood flows with data coming from Magnetic Resonance Imaging (MRI). Specifically, we will explore different inverse problems when going from more to less measured data: (a) Pressure maps estimation from 3D+time velocity fields, (b) Parameter estimation from 2D velocity fields (c) extension to parameter estimation from highly undersampled raw MRI data.
- Web
- Email: Benjamin Sanderse
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iCal
Members
Associated Members
Publications
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van der Stoep, A.W. (2019, March 26). Pricing and calibration with stochastic local volatility models in a Monte Carlo setting.
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Bisewski, K, Crommelin, D.T, & Mandjes, M.R.H. (2018). Simulation-based assessment of the stationary tail distribution of a stochastic differential equation. In Proceedings of the 2018 Winter Simulation Conference.
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Suárez-Taboada, M, Witteveen, J.A.S, Grzelak, L.A, & Oosterlee, C.W. (2018). Uncertainty quantification and Heston model. Journal of Mathematics in Industry, 8(1). doi:10.1186/s13362-018-0047-2
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Jüling, A, Viebahn, J.P, Drijfhout, S.S, & Dijkstra, H.A. (2018). Energetics of the Southern Ocean Mode. Journal of Geophysical Research: Oceans. doi:10.1029/2018JC014191
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Viebahn, J.P, Crommelin, D.T, & Dijkstra, H.A. (2018). Towards a turbulence closure based on energy modes. Journal of Physical Oceanography. doi:10.1175/JPO-D-18-0117.1
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Rodrigo, C, Hu, X, Ohm, P, Adler, J.H, Gaspar, F.J, & Zikatanov, L.T. (2018). New stabilized discretizations for poroelasticity and the Stokes’ equations. Computer Methods in Applied Mechanics and Engineering, 341, 467–484. doi:10.1016/j.cma.2018.07.003
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Jansson, F, van den Oord, G.J.W.M, Siebesma, A.P, & Crommelin, D.T. (2018). Resolving clouds in a global atmosphere model - a multiscale approach with nested models. In Proceedings - IEEE 14th International Conference on eScience, e-Science 2018. doi:10.1109/eScience.2018.00043
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Kumar, P, Luo, P, Gaspar, F.J, & Oosterlee, C.W. (2018). A multigrid multilevel Monte Carlo method for transport in the Darcy–Stokes system. Journal of Computational Physics, 371, 382–408. doi:10.1016/j.jcp.2018.05.046
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Eggels, A.W, & Crommelin, D.T. (2018). UQ with dependent inputs: Wind and waves. In Proceedings of ECCM 6 and ECFD 7.
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Bisewski, K, Crommelin, D.T, & Mandjes, M.R.H. (2018). Controlling the time discretization bias for the supremum of Brownian Motion. ACM Transactions on Modeling and Computer Simulation, 28(3). doi:10.1145/3177775
Current projects with external funding
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Advies marktconforme waardering NHG garanties ()
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Accurate prediction of slugs in multiphase pipe flow simulation for improved oil and gas production
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Towards cloud-resolving climate simulations
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Valuation Adjustments for Improved Risk Management (ABC-EU-XVA)
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Excellence in Uncertainty Reduction of Offshore Wind Systems (EUROS)
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Rare Event Simulation for Climate Extremes (RESClim)
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Sloshing of Liquefied Natural Gas: subproject Variability (14-10-project2) (SLING)
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Verified Exascale Computing for Multiscale Applications (VECMA)
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WIND Turbine Rotor aeroelasticity UncErtainty quantification (WINDTRUE)
Related partners
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DNV GL Netherlands B.V
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FOM
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Max Planck Institute for Informatics
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Shell, Amsterdam
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Stichting Waarborgfonds Eigen Woningen
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Bull Sas
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CBK Sci Con Ltd
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Bayerische Akademie der Wissenschaften
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Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
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Rijksuniversiteit Groningen
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Suzlon Blades Technology
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TNO
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Technische Universiteit Eindhoven
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Technische Universiteit Delft
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Brunel University London
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University College London
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Universiteit van Amsterdam