Erik von Schwerin
Given a mathematical model of a system with uncertainties, a computational method of approximation of that model, and a specific Quantity of Interest (QoI) of the system, how can we, with as small computational effort as possible, approximate the QoI within a user-specified accuracy? Most of Erik von Schwerin's research relates in some way or another to this question.
Research Interests
Erik von Schwerin's research interests include Deterministic and stochastic differential equations, Computations with uncertainty, Error control and adaptivity, Systematic coarse graining, Hybrid modeling, and Multiscale methods.
About
Erik von Schwerin is a Research Scientist at Professor Raúl F. Tempone's Stochastic Numerics Research Group (STOCHNUM) at King Abdullah University of Science and Technology (KAUST).
Research Interests
Erik von Schwerin's research interests include Deterministic and stochastic differential equations, Computations with uncertainty, Error control and adaptivity, Systematic coarse graining, Hybrid modeling and Multiscale methods.
Selected Publications
Abdul-Lateef Haji-Ali, Fabio Nobile, Erik von Schwerin, and Raúl Tempone, Optimization of mesh hierarchies in Multilevel Monte Carlo samplers, Stochastic Partial Differential Equations: Analysis and Computations, Vol. 4, Issue 1, Pages 76–112, 2016.
Nathan Collier, Abdul-Lateef Haji-Ali, Fabio Nobile, Erik von Schwerin, and Raúl Tempone, A Continuation Multilevel Monte Carlo algorithm, BIT Numerical Mathematics, June 2015, Volume 55, Issue 2, pp 399-432
- Joakim Beck, Yang Liu, Erik von Schwerin, and Raúl Tempone, Goal-Oriented Adaptive Finite Element Multilevel Monte Carlo with Convergence Rates, Computer Methods in Applied Mechanics and Engineering, 2022, Vol. 402,: p. 115582
Christian Bayer, Håkon Hoel, Erik von Schwerin, and Raúl Tempone, On non-asymptotic optimal stopping criteria in Monte Carlo Simulations, SIAM Journal on Scientific Computing, 2014, Vol. 36, No. 2 : pp. A869-A885
Giovanni Migliorati, Fabio Nobile, Erik von Schwerin, and Raúl Tempone, Analysis of Discrete L² Projection on Polynomial Spaces with Random Evaluations, Foundations of Computational Mathematics, 2014, Vol. 14, No. 3 : pp. 419-456
Håkon Hoel, Erik von Schwerin, Anders Szepessy, and Raúl Tempone, Implementation and analysis of an adaptive multilevel Monte Carlo algorithm, Monte Carlo Methods and Applications, 2014, Vol. 20, No. 1 : pp. 1-41.
Erik von Schwerin and Anders Szepessy, A Stochastic Phase-Field Model Determined from Molecular Dynamics, ESAIM: M2AN 44, 627—646, 2010.
Education Profile
- Ph.D. Numerical Analysis, Royal Institute of Technology (KTH), Stockholm, Sweden, 2007.
- M.S. Engineering Physics, Royal Institute of Technology (KTH), Stockholm, Sweden, 2001.
Qualifications
Education
- PhD (Dr. rer. nat.)
- Numerical Analysis, Royal Institute of Technology (KTH), Sweden, 2007
- Swedish
- Native or bilingual proficiency
- English
- Full professional proficiency
