Jonas Šukys

 

 

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Jonas Šukys
Computational Science & Engineering Lab
Clausiusstrasse 33

ETH-Zentrum, CLT C 11

CH-8092 Zürich
Fax: +41 44 632 99 13
E-Mail: jonas_DOT_sukys_AT_math.ethz.ch
Curriculum Vitae

Research

  • Uncertainty Quantification
  • Multi-level Monte Carlo methods
  • Hyperbolic nonlinear stochastic partial differential equations
  • Multi-phase flows and cavitation dynamics
  • Massively parallel high performance computing
  • Numerical analysis and simulations
  • Finite volume methods

Awards

  • Prize for the Best PhD Work and Presentation - MascotNum, Zürich, Switzerland, 2014

  • BGCE Student Paper Prize, finalist and 2nd place winner - SIAM CSE, Boston, United States, 2013

Software developement

  • PyMLMC
    Highly modular Python Multi-Level Monte Carlo (MLMC) software targeted at launching and managing
    Uncertainty Quantification campaigns of deterministic HPC simulation software on super-computers and post-processing the results.

  • CUBISM-MPCF
    High throughput software for direct numerical simulations of compressible two-phase flows.

  • ALSVID-UQ
    Massively parallel Multi-Level Monte Carlo Finite Volume solver (MLMC-FVM)
    for uncertainty quantification 
    in hyperbolic systems of conservation laws.
    Downloads and description available in project site.

Dissertation 

    J. Šukys

    Multi-level Monte Carlo Finite Volume methods for non-linear systems

    of conservation laws in multi-dimensions with random initial data.

    ETH Zurich, No. 21990. PDF

Publications 

    Download reference list: bib.sukys.lt (BibTeX), tex.sukys.lt (LaTeX).

  • J. Šukys, U. Rasthofer, F. Wermelinger, P. Hadjidoukas, D. Rossinelli, P. Koumoutsakos
    Numerical investigation of cavitation dynamics of O(10^4) bubble clouds:
    cloud geometries, identification of characteristic stages, and classification of cavities
    .
    Manuscript in progress, 2016.

     
  • J. Šukys, U. Rasthofer, F. Wermelinger, P. Hadjidoukas, D. Rossinelli, P. Koumoutsakos
    Uncertainty quantification in multi-phase cloud cavitation collapse flows using optimal control variate multi-level Monte Carlo sampling and petascale direct numerical simulations.
    Manuscript in progress, 2016.

     
  • P. Hadjidoukas, D. Rossinelli, F. Wermelinger, J. Šukys, U. Rasthofer, C. Conti, B. Hejazialhosseini, P. Koumoutsakos
    High throughput simulations of two-phase flows on BlueGene/Q.

    In Proceedings of the ParCo 2015 Conference: Advances in Parallel Computing, IOS Press, Edinburgh, United Kingdom, September 3-4, 2015.
     
  • S. Mishra, Ch. Schwab and J. Šukys
    Multi-Level Monte Carlo Finite Volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium.

    Journal of Computational Physics, 312:192-217, 2016.
    DOI: 10.1016/j.jcp.2016.02.014
     
  • A. Barth, Ch. Schwab and J. Šukys
    Multi-level Monte Carlo approximations of statistical solutions to the Navier-Stokes equation.
    MCQMC 2014, Springer Proceedings in Mathematics & Statistics 163, 2016.
    DOI: 10.1007/978-3-319-33507-0
     
  • C. Sanchez-Linares, M.J. Castro, S. Mishra and J. Šukys
    Multi-level Monte Carlo finite volume method for shallow water equations with uncertain parameters applied to landslide-generated tsunamis.
    Applied Mathematical Modelling 39, 7211-7226, 2015.

    DOI: 10.1016/j.apm.2015.03.011

     
  • L. Grosheintz, S. Mishra, and J. Šukys
    Scalable implementation of massively parallel multi-level Monte Carlo Finite Volume solvers on hybrid CPU/GPU architectures using dynamic load balancing.
    Submitted, 2014.

     
  • J. Šukys
    Adaptive load balancing for massively parallel multi-level Monte Carlo solvers.
    PPAM 2013, Part I, LNCS 8384, pp. 47--56. Springer Berlin Heidelberg, 2014.
    DOI: 10.1007/978-3-642-55224-3_5

     
  • J. Šukys, Ch. Schwab and S. Mishra
    Multi-Level Monte Carlo Finite Difference and Finite Volume methods for stochastic linear hyperbolic systems.
    MCQMC 2012, Springer Proceedings in Mathematics & Statistics, Volume 65, pp. 649--666, 2013.
    DOI: 10.1007/978-3-642-41095-6_34

     
  • S. Mishra, Ch. Schwab and J. Šukys
    Multi-level Monte Carlo finite volume methods for uncertainty quantification in nonlinear systems of balance laws.
    Lecture Notes in Computational Science and Engineering Volume 92, pp. 225--294, 2013.
    DOI: 10.1007/978-3-319-00885-1_6

     
  • S. Mishra, Ch. Schwab and J. Šukys
    Multi-level Monte Carlo Finite Volume methods for shallow water equations with uncertain topography in multi-dimensions.
    SIAM Journal of Scientific Computing, 34(6), pp. B761--B784, 2012.
    DOI: 10.1137/110857295

     
  • J. Šukys, S. Mishra, and Ch. Schwab
    Static load balancing for multi-level Monte Carlo finite volume solvers.
    PPAM 2011, Part I, LNCS 7203, pp. 245--254. Springer, Heidelberg, 2012.
    DOI: 10.1007/978-3-642-31464-3_25

     
  • S. Mishra, Ch. Schwab and J. Šukys
    Multi-level Monte Carlo finite volume methods for nonlinear systems of conservation laws in multi-dimensions.
    Journal of Computational Physics, 231(8):3365--3388, 2012.
    DOI: 10.1016/j.jcp.2012.01.011

Scientific Visits

  • EDANYA Research Group, Department of Matematical Analysis, University of Malaga.
    November 4-12, 2013, Malaga, Spain.

Invited Talks

  • Uncertainty quantification in cloud cavitation collapse using multi-level Monte Carlo.
    SIAM Conference on Uncertainty Quantification.
    April 5-8, 2016, SwissTech Convention Center, EPFL Campus, Lausanne, Switzerland.

     
  • Cloud Cavitation Collapse.
    Computational Sciene and Engineering (CompSE).
    December 18, 2015, Chair of Fluid Mechanics and Institute of Aerodynamics, RWTH Aachen University, Germany.

     
  • Multi-Level Monte Carlo Finite Volume Solver for Shallow Water Equations with Uncertain Bottom Topography.
    SIAM Conference on Nonlinear waves and Coherent Structures.
    August 11-14, 2014, Churchill College, Cambridge University, Cambridge, United Kingdom.

     
  • Multi-level Monte Carlo Finite Volume methods for stochastic systems of hyperbolic conservation laws.
    MascotNum Workshop on Computer Experiments and Meta-models for Uncertainty Quantification.
    April 23-25, 2014, ETH Zurich, Switzerland.
     
  • Robust massively parallel MLMC-FVM solver for uncertainty quantification in nonlinear conservation laws.
    EDANYA Research Group, Department of Matematical Analysis, University of Malaga.
    November 4-12, 2013, Malaga, Spain.

     
  • MLMC-FVM for systems of stochastic conservation laws in multi-dimensions.
    SIAM Conference on Computational Science and Engineering.
    February 25 - March 1, 2013, Boston, Massachusetts, United States.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    University of Otago, February 8, 2012, Dunedin, New Zealand.

Contributed Talks

  • Uncertainty Quantification in Cloud Cavitation Collapse using Multi-Level Monte Carlo.
    Internation Conference on Monte Carlo and Quasi Monte Carlo Methods 2016, August 16, 2016, San Francisco, United States.

     
  • Uncertainty Quantification in Cloud Cavitation Collapse using Multi-Level Monte Carlo.
    SIAM Conference on Uncertainty Quantification 2016, Lausanne, April 7, 2016, Lausanne, Switzerland.

     
  • Cloud Cavitation Collapse.
    Platform for Advanced Scientific Computing (PASC) Conference, June 3, 2015, Zurich, Switzerland.

     
  • Cloud Cavitation Collapse.
    2nd Frontiers in Computational Physics Conference: Energy Sciences, June 3, 2015, Zurich, Switzerland.

     
  • Adaptively balanced parallel MLMC solver for acoustic wave propagation with log-normal coefficients.
    MCQMC 2014 Conference, April 6-11, 2014, Leuven, Belgium.

     
  • Robust massively parallel MLMC-FVM solver for uncertainty quantification in nonlinear conservation laws.
    Computational Science and Engineering Laboratory, December 6, 2013, ETH Zurich, Switzerland.
     
  • Adaptive load balancing for massively parallel multi-level Monte Carlo solvers.
    Parallel Processing and Applied Mathematics 10th International Conference, September 8-11, 2013, Warsaw, Poland.

     
  • Robust massively parallel MLMC-FVM solver for uncertainty quantification in nonlinear conservation laws.
    Pro*Doc Workshop, August 14-16, 2013, Disentis/Muster, Switzerland.
     
  • Robust massively parallel MLMC-FVM solver for uncertainty quantification in nonlinear conservation laws.
    Swiss Numerics Colloquium, April 5, 2013, Lausanne, Switzerland.
     
  • Daugialygiai Monte Carlo metodai stochastinėms dalinėms diferencialinėms lygtims.
    LJMS, January 2, 2013, VU MIF, Vilnius, Lithuania.
     
  • MLMC-FVM for systems of stochastic conservation laws in multi-dimensions.
    HYP2012, June 26, 2012, Padua, Italy.
     
  • MLMC-FVM for shallow water equations with uncertain bottom topography.
    Swiss Numerics Colloquium, April 13, 2012, Bern, Switzerland.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    MCQMC 2012 Conference, February 13-17, 2012, Sydney, Australia.

     
  • Static load balancing for multi-level Monte Carlo finite volume solvers.
    Parallel Processing and Applied Mathematics 9th International Conference, September 11-14, 2011, Torun, Poland.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    Pro*Doc Workshop, August 18-19, 2011, Disentis/Muster, Switzerland.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    Workshop on High-Dimensional Aspects of Stochastic PDEs, August 8-12, 2011, HIM, Bonn, Germany.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    Swiss Numerics Day, May 6, 2011, USI Lugano, Switzerland.

     
  • MLMC for systems of stochastic conservation laws in multi-dimensions.
    Hyperbolic Group Seminar, Seminar for Applied Mathematics, March 22, 2011, ETH Zurich, Switzerland.

     
  • FEM-ABC coupling for discretization of Helmholtz equation in unbounded domains using FEniCS.
    Colloquium in Applied Mathematics, May 26, 2010, ETH Zurich, Switzerland.

Exposure

  • Contribution to featured projects on the Gauss Centre for Supercomputing

Posters

  • MLMC for systems of hyperbolic conservation laws with random input data.
    Analysis and numerical approximation of PDEs, September 8-10, 2014, ETH Zurich, Switzerland.
  • MLMC for systems of hyperbolic conservation laws with random input data.
    Swiss Numerics Day, April 25, 2014, University of Zurich, Switzerland.
  • MLMC for systems of hyperbolic conservation laws with random initial data.
    SAMHYP, February 18-19, 2011, ETH Zurich, Switzerland.

Teaching

  • Spring Term 2016: Computational Methods for Engineering and Applications I
  • Spring Term 2015: Computational Science and Engineering Seminar
  • Spring Term 2015: Computational Methods for Engineering and Applications I
  • Fall Term 2015: High Performance Computing I
  • Spring Term 2014: Numerical Methods for Partial Differential Equations
  • Fall Term 2013: Numerische Methoden für CSE
  • Fall Term 2012: Lineare Algebra und Numerische Mathematik D-BAUG
  • Fall Term 2012: Numerische Methoden für CSE
  • Fall Term 2011: Numerische Methoden für CSE
  • Spring Term 2011: Numerische Methoden für PHYS
  • Fall Term 2010: Numerische Methoden für CSE

Previous Affliations

  • Seminar for Applied Mathematics, ETH Zurich, Switzerland
  • Fraunhofer MEVIS, Bremen, Germany
  • Algorithmica Technologies GmbH, Bremen, Germany
  • Jacobs University Bremen, Bremen, Germany
  • Finasta Investment Management, Vilnius, Lithuania
  • Nacionalinė Moksleivių Akademija, Lithuania. KTUG, Kaunas, Lithuania.