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.









Instable blood supply may help healthy cells compete with tumor cells

Instable blood supply may help healthy cells compete with tumor cells

Researchers of CWI’s Scientific Computing group have found that instabilities in the blood supply in cancerous tissue can, surprisingly, lead to a less favorable environment for tumor cells. Their findings shed light on the potential negative side effects of current treatments that aim to actually normalize the blood supply in cancerous tissues.

Instable blood supply may help healthy cells compete with tumor cells - Read More…

CWI researcher simulates complex financial developments, from interest rates to the possibility of bankruptcy

CWI researcher simulates complex financial developments, from interest rates to the possibility of bankruptcy

PhD student Alvaro Leitao Rodriguez proposes new methods to tackle complex problems in the financial sector. With these methods, Leitao Rodriguez successfully simulates the movements of the interest rates in the Foreign eXchange (FX) markets and evaluates corresponding risks.

CWI researcher simulates complex financial developments, from interest rates to the possibility of bankruptcy - Read More…

Better estimation of financial risks possible with maths

Better estimation of financial risks possible with maths

Due to the recent financial crisis, the requirements imposed on banks have been made stricter. Banks must model the credit risk of the counterparties now in their portfolios, for instance. A measure for this is the credit value adjustment (CVA): the difference between the value of a portfolio without credit risk and the value if a possible bankruptcy of the counterparty is included. Qian Feng modelled CVAs and designed a new algorithm that can help banks estimate the risks precisely, so they can take appropriate measures if necessary.

Better estimation of financial risks possible with maths - Read More…

Current events

Uncertainty Quantification Seminar Ivan Yaroslavtsev (TU Delft)

  • 2019-02-21T15:00:00+01:00
  • 2019-02-21T16:00:00+01:00
February 21 Thursday

Start: 2019-02-21 15:00:00+01:00 End: 2019-02-21 16:00:00+01:00

Korteweg-de Vries Institute, room F1.15

Title: Burkholder-Davis-Gundy inequalities and stochastic integration in UMD Banach spaces

Abstract: In this talk we will present Burkholder--Davis--Gundy inequalities for general UMD Banach space-valued martingales. Namely, we will show that for any UMD Banach space X, for any X-valued martingale M with M_0=0, and for any 1 \leq p < infty:
E sup_{0 \leq s \leq t} ||M_s||^p \eqsim_{p, X} E gamma([M]_t)^p,   t \geq 0,

where [M]_t is the covariation bilinear form of M defined on X* x X* by

[M]_t(x*, y*) = [<M,x*>,<M, y*>]_t,   for x*, y* in X*,

and gamma([M]_t) is the L2-norm of a Gaussian measure on X having [M]_t as its covariance bilinear form.

As a consequence we will extend the theory of vector-valued stochastic integration with respect to a cylindrical Brownian motion by van Neerven, Veraar, and Weis, to the full generality.

PhD defence Anton van der Stoep (Scientific Computing)

  • 2019-03-26T12:30:00+01:00
  • 2019-03-26T13:30:00+01:00
March 26 Tuesday

Start: 2019-03-26 12:30:00+01:00 End: 2019-03-26 13:30:00+01:00

TU Delft

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)

CI/SC Seminar Cristóbal Bertoglio, Bernoulli Institute

  • 2019-04-09T11:00:00+02:00
  • 2019-04-09T12:00:00+02:00
April 9 Tuesday

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.


Associated Members


Current projects with external funding

  • Valuation Adjustments for Improved Risk Management ( ABC-EU-XVA)
  • Accurate prediction of slugs in multiphase pipe flow simulation for improved oil and gas production
  • Geometric Structure and Data Assimilation
  • Towards cloud-resolving climate simulations
  • Excellence in Uncertainty Reduction of Offshore Wind Systems (EUROS)
  • Rare Event Simulation for Climate Extremes (RESClim)
  • Sloshing of Liquefied Natural Gas: subproject Variability (14-10-project2) (SLING)
  • Verified Exascale Computing for Multiscale Applications (VECMA)
  • WIND Turbine Rotor aeroelasticity UncErtainty quantification (WINDTRUE)

Related partners

  • DNV GL Netherlands B.V
  • FOM
  • Max Planck Institute for Informatics
  • SE Blades Technology B.V.
  • Shell, Amsterdam
  • Bull Sas
  • CBK Sci Con Ltd
  • Bayerische Akademie der Wissenschaften
  • Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
  • Rijksuniversiteit Groningen
  • TNO
  • Technische Universiteit Eindhoven
  • Technische Universiteit Delft
  • Brunel University London
  • University College London
  • Universiteit van Amsterdam