The interdisciplinary work in the Analysis group includes development of new mathematical and computational tools as well as wide-ranging applications.
Theme: Applied Analysis
Innovative work in smart and nano-materials technologies involves computational models that lead to fundamental mathematical questions (existence and well-posedness, stability, qualitative properties of solutions) that fall within the remit of Applied Analysis. The group members’ expertise in spectral analysis, coagulation-fragmentation equations and homogenisation theory has enabled them to supplement and guide numerical and experimental work in the AFRC and a KTN industrial internship with Procter & Gamble on the mathematical modelling of spray-drying, while their expertise in network modelling and analysis underpins work in Mathematical Ecology.
Theme: Numerical Analysis
Numerical Analysis group is one of the largest and most highly regarded groups of its kind in the UK. Their research is focused on the construction and analysis of computational methods for algebraic and differential equations arising in a wide variety of application areas, equipping them to make important contributions across all the University’s strategic research themes. Current examples include Measurement Science & Enabling Technologies (regarding sensor networks with NPL), Advanced Manufacturing & Materials (regarding electric heating in collaboration with the AFRC), Inverse problems, advanced image processing and deep learning, and Ocean, Air & Space (regarding unsteady vortex-dominated flows).
Theme: Stochastic Analysis
Research by the Stochastic Analysis group on stochastic differential equation (SDE) models for option values in energy markets, stochastic numerical solutions for nonlinear energy models, and time-series models for financial data contributes across many of the University’s strategic research themes, notably Energy and Health & Wellbeing. The group has an internationally acknowledged research capability in the mathematical modelling of stochastic systems. In particular, several very popular numerical methods for nonlinear SDEs, including the tamed Euler-Maruyama (EM), the stopped EM, and the tamed Milstein methods, and adaptive EM methods have recently been developed based on ground-breaking work by the group.
Theme: Combinatorics
The group's research interests are in enumerative, bijective, algebraic and topological combinatorics, with connections to theoretical computer science, physics and graph theory. Much of our work has been connected to permutation patterns, a relatively young but very active research area, with several hundred papers published in the last ten years and several distinct lines of research emerging lately.
If you're interested in collaborating with us or wish to enquire about postgraduate or postdoctoral research positions then please contact one of the group members listed below.
Our researchers
- Prof Xuerong Mao (Head of Group)
- Dr Francesca Arrigo
- Dr Gabriel Barrenechea
- Dr David Bevan
- Professor Ke Chen
- Dr Penny Davies
- Prof Victorita Dolean Maini
- Dr Mohammud Foondun
- Dr Michael Grinfeld
- Professor Sergey Kitaev
- Dr Philip Knight
- Dr Matthias Langer
- Prof John Mackenzie
- Dr Jiazhu Pan
- Dr Jennifer Pestana
- Dr Alison Ramage
- Dr Michele Ruggeri
- Prof Einar Steingrimsson
- Dr Yue Wu
- Dr Yoshihito Kazashi
