School of Mathematical Sciences

Scientific Computation

Scientific computation and numerical analysis are concerned with the design and analysis of computational algorithms. Research areas include: computational PDEs; high-order finite element/discontinuous Galerkin methods; a posteriori error analysis and adaptivity; numerical integration of stochastic ordinary and partial differential equations; Bayesian inverse problems; Uncertainty Quantification;  multiscale modelling and computation; computational electromagnetics; computational fluid mechanics; numerical simulation of bifurcation problems; computational cell biology; stochastic dynamics and modelling; computational finance.



Research Areas

  • A posteriori error analysis and adaptivity
  • Bayesian inverse problems
  • Computational cell biology
  • Computational electromagnetics
  • Computational fluid mechanics
  • Computational PDEs
  • High-order finite element/discontinuous Galerkin methods
  • Multiscale modelling and computation
  • Numerical simulation of bifurcation problems
  • Numerical integration of stochastic ordinary and partial differential equations
  • Stochastic dynamics and modelling

Group Members


Core members of the group are: 

Paul Houston

Professor Houston has interests in:

  • Numerical methods for partial differential equations
  • Finite element and discontinuous Galerkin methods
  • A posteriori error estimation
  • Adaptive mesh generation
  • Computational fluid mechanics and computational electromagnetics
Matthew Hubbard

Dr Hubbard has interests in:

  • Algorithms for multidimensional fluid flow
  • Adaptive algorithms
  • Multiscale modelling of biomedical applications
  • Efficient linear algebra solvers


Marco Iglesias

Dr Iglesias works on inverse problems, particularly for problems in geoscience/geomechanics.


Michael Tretyakov

Professor Tretyakov has current interests in numerical integration of stochastic differential equations, probabilistic approaches to numerical solution of non-linear partial differential equations, financial mathematics, stochastic dynamics and modelling in genetics.


Kris van der Zee

Dr van der Zee has interests in:

  • Foundations of error estimation and adaptivity, multiscale and adaptive modelling
  • Computational mechanics and computational PDEs
  • Uncertainty quantification, validation and Bayesian experimental design
  • Evolving interface phenomena, free-boundary problems and diffuse-interface models
  • Applications to engineering mechanics, biomechanics and mechanobiology.




Many other members of the School undertake scientific computation work as part of their research, including:




Thinking of joining us?

We are keen to create an environment which supports all staff members by providing:






Professor Michael Tretyakov

School of Mathematical Sciences

University of Nottingham
University Park

t: +44 (0) 115 95 14954


School of Mathematical Sciences

The University of Nottingham
University Park
Nottingham, NG7 2RD

For all enquiries please visit: