Research

              Alex Bespalov

Current research project

  • Numerical analysis of adaptive UQ algorithms for PDEs with random inputs (funded by EPSRC)
    This joint project with collaborators at The University of Manchester focuses on the development of robust, accurate, and practical numerical methods for solving parameter-dependent PDEs stemming from uncertainty quantification models.

Current PhD students

  • Leonardo Rocchi (since October 2015).
    Project title: "Adaptive algorithms for numerical solution of PDEs with random inputs".
  • Rawin Youngnoi (since September 2016),
    jointly supervised with Dr Daniel Loghin.
    Project title: "Domain decomposition methods for PDE problems with random inputs".

Supervised Master student

  • Matthew Williams (MSci project, 2014 2015).
    Project title: "Stochastic sampling methods for PDEs with random input data".