Data Science and Dynamics Research Group

We focus on the analysis of real-world dynamical systems that generate large data sets. A broad range of mathematical techniques are applied to identify system characteristics, and to make predictions using data and mathematical models.

Overview

Our group covers a wide range of research topics that are concerned with dynamical systems — deterministic or stochastic — that typically involve substantial data. These include, in particular, certain areas of mathematical biology including sleep and circadian rhythms, molecular dynamics, analysis in meteorology and climate sciences, mathematical criminology, machine learning, and more generally analysis of information-driven systems such as financial markets, electoral competitions, or internet communities.

A range of mathematical techniques from ordinary differential equations, partial differential equations, stochastic differential equations, information theory, probability, and statistics are applied to investigate behaviours of real-world dynamical systems.

    Our people

    Academic staff

    Professor Philip Aston

    Professor of Mathematics

    Werner Bauer profile image

    Dr Werner Bauer

    Lecturer in Mathematics

    Dorje C Brody profile image

    Professor Dorje Brody

    Professor in Mathematics

    Dr Audrey Kueh

    Teaching Fellow

    David Lloyd profile image

    Professor David Lloyd

    Professor in Mathematics, Deputy Head of School of Mathematics & Physics, Director of Learning and Teaching School of Mathematics & Physics

    Ian Roulstone profile image

    Professor Ian Roulstone

    Emeritus Professor

    Naratip Santitissadeekorn profile image

    Dr Naratip Santitissadeekorn

    Senior Lecturer in Data Assimilation

    Anne Skeldon profile image

    Professor Anne Skeldon

    Professor of Mathematics

    Postgraduate research students

    Steve Falconer

    Postgraduate Research Student