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.
- 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
Core members of the group are:
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
Dr Hubbard has interests in:
- Algorithms for multidimensional fluid flow
- Adaptive algorithms
- Multiscale modelling of biomedical applications
- Efficient linear algebra solvers
Dr Iglesias works on inverse problems, particularly for problems in geoscience/geomechanics.
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: