This image shows Ilja Kröker

Dr.

Ilja Kröker

Postdoc
Institute for Modelling Hydraulic and Environmental Systems (LS3/SimTech)

Contact

+49 711 685 60745

Business card (VCF)

Pfaffenwaldring 5a
D-70569 Stuttgart
Room: 1.15

  1. 2020

    1. Oladyshkin S, Mohammadi F, Kröker I, Nowak W. Bayesian3 active learning for Gaussian process emulator using information theory. Entropy. 2020;22(0890):1–27.
    2. Oladyshkin S, Beckers F, Kroeker I, Mohammadi F, Heredia A, Noack M, et al. Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. In: Computational Methods in Water Resources (CMWR). 2020. (Computational Methods in Water Resources (CMWR)).
  2. 2019

    1. Bürger R, Kröker I. Computational uncertainty quantification for some strongly degenerate parabolic convection–diffusion equations. Journal of Computational and Applied Mathematics [Internet]. 2019;348:490–508. Available from: http://www.sciencedirect.com/science/article/pii/S037704271830551X
    2. Köppel M, Franzelin F, Kröker I, Oladyshkin S, Santin G, Wittwar D, et al. Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. Computational Geosciences. 2019;23(2):339–54.
  3. 2018

    1. Barth A, Kröker I. Finite Volume Methods for Hyperbolic Partial Differential Equations with Spatial Noise. In: Klingenberg C, Westdickenberg M, editors. Theory, Numerics and Applications of Hyperbolic Problems I. Cham: Springer International Publishing; 2018. p. 125--135. (Klingenberg C, Westdickenberg M, editors. Theory, Numerics and Applications of Hyperbolic Problems I).
  4. 2017

    1. Bürger R, Kröker I. Hybrid Stochastic Galerkin Finite Volumes for the Diffusively Corrected Lighthill-Whitham-Richards Traffic Model. In: Cancès C, Omnes P, editors. Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic and Parabolic Problems: FVCA 8, Lille, France, June 2017 [Internet]. Cham: Springer International Publishing; 2017. p. 189--197. (Cancès C, Omnes P, editors. Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic and Parabolic Problems: FVCA 8, Lille, France, June 2017). Available from: http://dx.doi.org/10.1007/978-3-319-57394-6_21
    2. Köppel M, Kröker I, Rohde C. Intrusive uncertainty quantification for hyperbolic-elliptic systems governing two-phase flow in heterogeneous porous media. Comput Geosci. 2017;21(4):807--832.
  5. 2016

    1. Barth A, Bürger R, Kröker I, Rohde C. Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach. Computers & Chemical Engineering [Internet]. 2016;89:11-- 26. Available from: http://www.sciencedirect.com/science/article/pii/S0098135416300503
  6. 2014

    1. Bürger R, Kröker I, Rohde C. A hybrid stochastic Galerkin method for uncertainty quantification  applied to a conservation law modelling a clarifier-thickener unit. ZAMM Z Angew Math Mech [Internet]. 2014;94(10):793–817. Available from: http://dx.doi.org/10.1002/zamm.201200174
    2. Kröker I, Nowak W, Rohde C. A stochastically and spatially adaptive parallel scheme for uncertain and non-linear two-phase flow problems. Computational Geosciences. 2014;19:269–84.
    3. Köppel M, Kröker I, Rohde C. Stochastic Modeling for Heterogeneous Two-Phase Flow. In: Fuhrmann J, Ohlberger M, Rohde C, editors. Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects [Internet]. Springer International Publishing; 2014. p. 353--361. (Fuhrmann J, Ohlberger M, Rohde C, editors. Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects; vol. 77). Available from: http://dx.doi.org/10.1007/978-3-319-05684-5\_34
  7. 2013

    1. Kröker I. Stochastic models for nonlinear convection-dominated flows [Doctoral dissertation]. Universität Stuttgart; 2013.
  8. 2012

    1. Kröker I, Rohde C. Finite volume schemes for hyperbolic balance laws with multiplicative  noise. Appl Numer Math [Internet]. 2012;62(4):441--456. Available from: http://dx.doi.org/10.1016/j.apnum.2011.01.011
  9. 2011

    1. Bürger R, Kröker I, Rohde C. Uncertainty quantification for a clarifier-thickener model with random feed. In: Finite volumes for complex applications VI Problems & perspectives Volume 1, 2 [Internet]. Springer; 2011. p. 195--203. (Finite volumes for complex applications. VI. Problems & perspectives. Volume 1, 2; vol. 4). Available from: http://dx.doi.org/10.1007/978-3-642-20671-9\_21
  10. 2008

    1. Kröker I. Finite volume methods for conservation laws with noise. In: Finite volumes for complex applications V. ISTE, London; 2008. p. 527--534. (Finite volumes for complex applications V).

10/2007 Diploma in Mathematics, Bielefeld University
10/2013 PhD, Fakulty of Mathematics and Physics, Excellence Cluster Simulation Technology (SimTech), University of Stuttgart
10/2013-09/2017 Postdoc Researcher, Department of Computational Methods for Uncertainty Quantification, Institute of Applied Analysis and Numerical Simulation, University of Stuttgart
10/2017-03/2018 Professor substitute for Applied Mathematics, Friedrich-Alexander-University Erlangen-Nürnberg
04/2018-03/2019 Postdoc Researcher, Department of Computational Methods for Uncertainty Quantification, Institute of Applied Analysis and Numerical Simulation, University of Stuttgart
Seit 09/2019 Scientific Researcher, Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart

Surrogate-based active learning for parameter inference in geosciences via Bayesian sparse 2 multi-adaptivity enhanced by information theory

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