Laura Scarabosio

scarabosio@science.ru.nl

I am a tenure track assistant professor at the Radboud University working in numerical analysis and uncertainty quantification.

Research interests

  • Shape uncertainty
  • Random multiscale materials
  • Multilevel methods
  • Deep neural networks
  • Bayesian inversion
  • Applications to medicine and biology

    • Publications

    Preprints

  • L. Scarabosio, Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification
  • M. Fritz, C. Kuttler, M.L. Rajendran, L. Scarabosio, B. Wohlmuth, On a subdiffusive tumour growth model with fractional time derivative

    • Articles in journals

  • L. Scarabosio, B. Wohlmuth, J.T. Oden, D. Faghihi, Goal-oriented adaptive modeling of random heterogeneous media and model-based multilevel Monte Carlo methods, Computers & Mathematics with Applications 78.8 (2019): 2700-2718. Preprint
  • U. Khristenko, L. Scarabosio, P. Swierczynski, E. Ullmann, B. Wohlmuth, Analysis of Boundary Effects on PDE-Based Sampling of Whittle--Matérn Random Fields, SIAM/ASA Journal on Uncertainty Quantification 7 (3), 948-974. Preprint
  • L. Scarabosio, Multilevel Monte Carlo on a high-dimensional parameter space for transmission problems with geometric uncertainties, International Journal for Uncertainty Quantification 9.6 (2019). Preprint
  • R. Hiptmair, L. Scarabosio, C. Schillings, C. Schwab, Large deformation shape uncertainty quantification in acoustic scattering, Advances in Computational Mathematics, 1-44. Preprint
  • E.A.B.F. Lima, J.T. Oden, B. Wohlmuth, A. Shahmoradi, D.A. Hormuth II, T.E. Yankeelov, L. Scarabosio, T. Horger, Selection and validation of predictive models of radiation effects on tumor growth based on noninvasive imaging data, Computer methods in applied mechanics and engineering 327, 277-305. Preprint
  • A. Paganini, L. Scarabosio, R. Hiptmair, I. Tsukerman, Trefftz approximations: a new framework for nonreflecting boundary conditions, IEEE Transactions on Magnetics 52 (3), 1-4.

    • Theses

  • L. Scarabosio, Shape uncertainty quantification for scattering transmission problems, Diss. ETH Zurich, 2016.

    • Curriculum vitae

    Professional experience

  • Aug 2020 - present: tenure track assistant professor, IMAPP, Radboud University (Netherlands).
  • Sep 2016 - Jul 2020: postdoc, Chair of Numerical Analysis, TU Munich (Germany).
  • May 2016 - Aug 2016: scientific assistant, Seminar for Applied Mathematics, ETH Zürich (Switzerland).

    • Education

  • Feb 2012 - May 2016: PhD in Mathematics, Seminar for Applied Mathematics, ETH Zürich (Switzerland).
  • Oct 2009 - Dic 2011: Master in Mathematical Modelling in Engineering, Polytechnic of Turin (Italy).
  • Sep 2006 - Oct 2009: Bachelor in Mathematics in Engineering, Polytechnic of Turin (Italy).

    • Teaching

    Courses

  • Spring 2021: Monte Carlo Methods, Radboud University.
  • Fall 2020: Bachelor seminar (with P. Hochs), Radboud University.
  • Fall 2019: Einführung in die Programmierung, TU Munich.
  • Fall 2017: Einführung in die Programmierung, TU Munich.
  • 2016 - 2020: teaching assistant for various courses in numerical analyis at TU Munich.
  • 2012 - 2016: teaching assistant for various courses in numerical analysis at ETH Zürich.

    • Supervision

  • Jan 2020 - Jul 2020: co-supervision of Master thesis of Alexandra Starostina, "Robin boundary conditions for PDE-based sampling of Gaussian Random Fields", TU Munich.