Core
Numerical Analysis
Floating-point arithmetic, nonlinear equations, linear systems, eigenvalue problems, interpolation and quadrature.
Teaching & didactics
Teaching spans introductory numerical analysis, approximation theory, differential equations, visual computation and doctoral topics, supported by a long-running archive of notes, code and examinations.
Teaching areas
Courses are organised around a common progression: mathematical foundations, stable algorithms, computational implementation and applications.
Core
Floating-point arithmetic, nonlinear equations, linear systems, eigenvalue problems, interpolation and quadrature.
Approximation
Polynomial and rational approximation, splines, radial basis functions, stability and multivariate methods.
Scientific computing
Time-stepping, finite differences, multistep methods and computational models for applied problems.
Advanced
Kernel methods, numerical linear algebra, approximation, medical applications and focused research topics.
Books & resources
The archive combines explanatory notes, exercises, code, examination texts and longer-form publications.
Concepts, algorithms and executable examples for a first course in numerical computation.
View book ArchiveHistorical teaching material developed across Mathematics, Computer Science, Statistics and related programmes.
Open archive CodeSelected Matlab / Octave resources connected to numerical methods and approximation.
Browse softwareTeaching history
A concise map of the teaching archive; the legacy page preserves the detailed year-by-year material.
Numerical analysis, approximation theory, differential equations, doctoral topics and applications in medicine.
Numerical calculus, analysis, approximation methods, computer graphics and computational laboratories.
Early teaching in numerical analysis and computational mathematics.
Teaching experience in Belgium, Germany, Poland, New Zealand and Cameroon.
For students
Please use the contact page and include the course or topic in the subject line.