Computational Modelling Group

statistical analysis

For queries about this topic, contact Jess Jones.

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A novel method for monitoring air pollution from satellites at very high resolution

Joanna Nield, Jason Noble, Edward Milton (Investigators), Robin Wilson

Developing methods to monitor the clarity of the atmosphere from satellites at 100,000 times the resolution of previous methods. This can then be used to monitor air pollution, correct satellite images and provide data for climate studies. Simulation is used to model the effects of atmospheric pollution on light passing through the atmosphere, and to test the method under 'synthetic atmospheres'.

Application of RNA-Seq for gene fusion identification in blood cancers

William Tapper (Investigator), Marcin Knut

Gene fusions are often the cause of different blood cancers. As such, accurate identification of them provides information on the underlying cause of a cancer, ensuring appropriate choice of treatment. However, due to shortcomings of the currently applied methods for gene fusion identification, some of them escape undetected. We are employing RNA-Seq, a cutting-edge method for sequencing RNA, the messenger of genetic information, to investigate gene fusions.

Atlantic ocean meridional heat transport at 26oN: Impact on subtropical ocean heat content variability

Robert Marsh (Investigator), Maike Sonnewald

Local climate is significantly affected by changes in the oceanic heat content on a range of timescales. This variability is driven by heat fluxes from both the atmosphere and the ocean. In the Atlantic the meridional overturning circulation is the main contributor to the oceanic meridional heat transport for latitudes south of about 50◦ N. The RAPID project has been successfully monitoring the Atlantic meridional overturning at 26◦ N since 2004. This study demonstrates how this data can be used to estimate the basin-wide ocean heat content in the upper 800 m between 26◦ N to 36◦ N. Traditionally the atmosphere is seen to dominate the ocean heat content variability. However, previous studies have looked at smaller areas in the Gulf Stream region, finding that the ocean dominates deseasoned fluctuations of ocean heat content, while studies of the whole North Atlantic region suggest that the atmosphere may be dominant. In our study we use a box-model to investigate fluctuations of the ocean heat content in the subtropical North Atlantic between 26◦ N and 36◦ N. The box-model approach is validated using 19 years of high resolution GCM data. We find that in both the GCM and RAPID based data the ocean heat transport dominates the deseasoned heat content variability, while the atmosphere’s impact on the heat content evolution stabilizes after 6 months. We demonstrate that the utility of the RAPID data goes beyond monitoring the overturning circulation at 26◦ N, and that it can be used to better understand the causes of ocean heat content variability in the North Atlantic. We illustrate this for a recent decrease in ocean heat content which was observed in the North Atlantic in 2009 and 2010. Our results suggest that most of this ocean heat content reduction can be explained by a reduction of the meridional ocean heat transport during this period.

Automated Algorithmic Trading with Intelligent Execution

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

In this project, we introduce the first fully automated trading system for real-world stock trading that uses time-adaptive execution algorithm to minimise market impact while increasing profitability com- pared to benchmark strategies.

Automated Trading with Performance Weighted Random Forests and Seasonality

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

This project proposes an expert system that uses novel machine learning techniques to predict the price return over these seasonal events, and then uses these predictions to develop a profitable trading strategy.

Care Life Cycle

Seth Bullock, Sally Brailsford, Jason Noble, Jakub Bijak (Investigators), Elisabeth zu-Erbach-Schoenberg, Jason Hilton, Jonathan Gray

This research programme brings together teams of researchers from social sciences, management science and complexity science to develop a suite of models representing the socio-economic and demographic processes and organisations implicated in the UK’s health and social care provision. Integral to the project is working with our partners in the public sector and communicating the results of these models to policymakers allowing them to effectively plan for the future.

Centre for Doctoral Training in Next Generation Computational Modelling

Hans Fangohr, Ian Hawke, Peter Horak (Investigators), Susanne Ufermann Fangohr, Ryan Pepper, Hossam Ragheb, Emanuele Zappia, Ashley Setter, David Lusher, Alvaro Perez-Diaz, Kieran Selvon, Thorsten Wittemeier, Mihails Milehins, Stephen Gow, Ioannis Begleris, Jonathon Waters, James Harrison, Joshua Greenhalgh, Rory Brown, Robert Entwistle, Paul Chambers, Jan Kamenik, Craig Rafter

The £10million Centre for Doctoral Training was launched in November 2013 and is jointly funded by EPSRC, the University of Southampton, and its partners.

The NGCM brings together world-class simulation modelling research activities from across the University of Southampton and hosts a 4-year doctoral training programme that is the first of its kind in the UK.

CRISIS – Complexity Research Initiative for Systemic InstabilitieS

Frank McGroarty (Investigator), Bob De Caux

A new approach to modelling and understanding financial system and macroeconomic risk and instability

Deep Optimisation

Jamie Caldwell

The project will develop the implementation and application of a new optimisation technique. 'Deep optimisation' combines deep learning techniques in neural networks with distributed optimisation methods to create a dynamically re-scalable optimisation process. This project will develop this technique to better-understand its capabilities and limitations and develop GPU implementations. The protein structure prediction problem will be used as the main test application.

DIPLOS - Dispersion of Localised Releases in a Street Network

Trevor Thomas, Ian Castro (Investigators)

The security threat level from international terrorism, introduced by the UK Security Service, has been classified as either "severe" or "critical" for much of its six-year history, and currently remains as "substantial" (source: MI5 website). Part of the risk posed by terrorist threats involves potential releases of air-borne chemical, biological, radiological or nuclear (CBRN) material into highly populated urbanised areas. Smoke from industrial accidents within or in the vicinity of urban areas also pose risks to health and can cause widespread disruption to businesses, public services and residents. The Buncefield depot fire of 2005 resulted in the evacuation of hundreds of homes and closure of more than 200 schools and public buildings for two days; consequences would have been much more severe if prevailing meteorological conditions had promoted mixing or entrainment of the smoke plume into the urban canopy. In both these scenarios it is crucial to be able to model, quickly and reliably, dispersion from localised sources through an urban street network in the short range, where the threat to human health is greatest. However, this is precisely where current operational models are least reliable because our understanding and ability to model short-range dispersion processes is limited. The contribution that DIPLOS will make is:

1. to fill in the gaps in fundamental knowledge and understanding of key dispersion processes,
2. to enable these processes to be parametrized for use in operational models,
3. to implement them into an operational model, evaluate the improvement and apply the model to a case study in central London

Most of the existing research on urban dispersion has focused on air quality aspects, with sources being extensive and distributed in space. Scientifically, this research is novel in focusing on localized releases within urban areas, and on dispersion processes at short range. Through a combination of fundamental studies using wind tunnel experiments and high resolution supercomputer simulations, extensive data analysis and development of theoretical and numerical models, DIPLOS will contribute to addressing this difficult and important problem from both a scientific research and a practical, operational perspective.

Early warning signals in climate data

Kevin Oliver, James Dyke (Investigators), Maike Sonnewald

Paleoclimatic records reveal that the Earth’s climate system has undergone sharp transitions between
states. Much work has recently been devoted to assessing how likely the current climate is to undergo such a sharp transition. This is motivated by the severe socioeconomic consequences such dramatic changes would entail. Thus, predicting iminent transitions would be very valuable. This review provides an overview of two promising techniques which could potentially be used to assess the stability of components of the climate system. These techniques are degenerate fingerprinting and detrended fluctuation analysis (DFA). It is found that degenerate fingerprinting is more widely used, but that DFA could be more suitable. DFA allows for memory in the time-series, and can give better results with less data. However, the DFA technique is best suited for systems close to the transitions, and relies on calibration with the degenerate fingerprinting technique further from the transition. Applying these techniques to forecast transitions is unfortunately impeded by lack of suitable data. Using data from several sources could overcome this. Thus, the techniques could be very valuable if the use of unevenly spaced data from several sources does
not lead to serious loss off accuracy. However, the techniques are still very useful when assessing underlying dynamics in model output and paleooceanographic time-series.

How sensitive is ocean model utility to resolution?

Kevin Oliver (Investigator), Maike Sonnewald

One of the most intriguing problems in recent ocean modeling research is the impact of varying model resolution on model accuracy. Increasing model resolution one includes more of the important processes. However, the increase in accuracy with resolution is unlikely to be linear. Thus, as computational cost increases with resolution, a critical assessment of achieved benefits is prudent. Here we analyse a suite of realistic and compatible global ocean model runs from coarse (1o, ORCA1), eddy-permitting (1/4o, ORCA025) and eddy resolving (1/12o, ORCA12) resolutions. Comparisons of steric height variability (varSH) highlight changes in ocean density structure, revealing impacts on mechanisms such as downwelling and eddy energy dissipation. We assess vertical variability using the covariace of the deep and shallow varSH. Together with assessing isopycnal movements, we demonstrate the influence of deep baroclinic modes and regions where the barotropic flow sheds eddies. Significant changes in the deepwater formation and dispersion both in the Arctic and Antarctic are found between resolutions. The varSH increased from ORCA1 to ORCA025 and ORCA12, particularily in the Southern Ocean and Western Boundary Currents. However, there is no significant covariance between the surface and deep in ORCA1, while ORCA025 and ORCA12 show significant covariance, implying an important missing energy pathway in ORCA1. Comparing ORCA025 and ORCA12 we see significant differences in eddy energy dissipation. We assess the impact of varying model resolution on the mean flow, discussing implications to dissipation pathways on model accuracy, with reference to stochastic parameterisation schemes.

Hunting for Walking Technicolor at the LHC

Alexander Belyaev (Investigator), Azaria Coupe

Now that the LHC experiment at CERN has observed the Higgs boson, the final piece of the particle physics theory called the Standard Model, the focus of theoretical and experimental physicists shifts to what could possibly be discovered next. Phenomenologists, such as myself, straddle this line between theory and experiment, comparing the many theories of physics Beyond the Standard Model to whatever the LHC discovers, even drawing conclusions from what it doesn’t discover. I focus on a theory called Walking Technicolor (WTC), what the LHC would see if it were correct, and what the lack of discovery so far means for the fate of WTC.

Investigation into the Interfacial Physics of Field Effect Biosensors

Nicolas Green, Chris-Kriton Skylaris (Investigators), Benjamin Lowe

This interdisciplinary research aims to improve understanding of Field Effect Transistor Biosensors (Bio-FETs) and to work towards a multiscale model which can be used to better understand and predict device response.

Measuring organisation with statistical complexity

Seth Bullock (Investigator), David Arden

What is a organisation and how can we measure it? In particular, can we automate the process of picking out the emergence of pattern and structure in a noisy system over time?

On the applicability of nonlinear timeseries methods for partial discharge analysis

Paul Lewin (Investigator), Lyuboslav Petrov

The governing processes of Partial Discharge (PD)
phenomena trigger aperiodic chains of events resulting in ’ap-
parently’ stochastic data, for which the widely adopted analysis
methodology is of statistical nature. However, it can be shown,
that nonlinear analysis methods can prove more adequate in
detecting certain trends and patterns in complex PD timeseries.
In this work, the application of nonlinear invariants and phase
space methods for PD analysis are discussed and potential pitfalls
are identified. Unsupervised statistical inference techniques based
on the use of surrogate data sets are proposed and employed for
the purpose of testing the applicability of nonlinear algorithms
and methods. The Generalized Hurst Exponent and Lempel Ziv
Complexity are used for finding the location of the system under
test on the spectrum between determinism and stochasticity. The
algorithms are found to have strong classification abilities at
discerning between surrogates and original point series, giving
motivation for further investigations.

Origins of Evolvability

Richard Watson, Markus Brede (Investigators), William Hurndall

This project examined the putative evolvability of a Lipid World model of fissioning micelles. It was demonstrated that the model lacked evlovability due to poor heritability. Explicit structure for micelles was introduced along with a spatially localised form of catalysis which increased the strength of selection as coupling between potential chemical units of heredity were reduced.

Simulation of biological systems at long length and distance scales

Jonathan Essex (Investigator), Kieran Selvon

This project aims to shed light on cell membrane mechanisms which are difficult to probe experimentally, in particular drug permiation across the cell membrane. If one had a full understanding of the mechanism, drugs could be designed to target particular embedded proteins to improve their efficacy, the viability of nano based medicines and materials could also be assessed, testing for toxicity etc.

Supernova Rates in the Local Universe

Mark Sullivan (Investigator), Christopher Frohmaier

This project will calculate the frequency of exploding stars -- or supernovae -- in the nearby universe. We simulate a 'toy universe' by exploding billions of stars in a computer, and then artificially 'observing' these explosions by replicating a real astronomical sky survey, the Palomar Transient Factory (PTF). The results of this simulation allows us to discover the rate at which supernovae occur in the local universe each year.

The application and critical assessment of protein-ligand binding affinities

Jonathan Essex (Investigator), Ioannis Haldoupis

A method that can accurately predict the binding affinity of small molecules to a protein target would be imperative to pharmaceutical development due to the time and resources that could be saved. A head-to-head comparison of such methodology, ranging from approximate methods to more rigorous methods, is performed in order to assess their accuracy and utility across a range of targets.

Uncertainty quantification and propagation through complex chains of computational models

Dave Woods (Investigator), Stephen Gow

This project will explore how predictions can be made and assessed through complex chains of computer models.

Variability in high pressure blade trailing edge geometry and its impact on stage capacity and blade temperature

Andy Keane (Investigator), Jan Kamenik

My project involves the trailing edge (TE) geometry of gas turbine high pressure turbine blades, which is subject to inevitable variability due to the manufacturing processes involved.


Sally Brailsford
Professor, Management (FBL)
Seth Bullock
Professor, Electronics and Computer Science (FPAS)
Jonathan Essex
Professor, Chemistry (FNES)
Hans Fangohr
Professor, Engineering Sciences (FEE)
Andy Keane
Professor, Engineering Sciences (FEE)
Paul Lewin
Professor, Electronics and Computer Science (FPAS)
Frank McGroarty
Professor, Management (FBL)
Edward Milton
Professor, Geography (FSHS)
Dave Woods
Professor, Southampton Statistical Sciences Research Institute (FSHS)
Nicolas Green
Reader, Electronics and Computer Science (FPAS)
Peter Horak
Reader, Optoelectronics Research Centre
Robert Marsh
Reader, National Oceanography Centre (FNES)
Jakub Bijak
Senior Lecturer, Social Sciences (FSHS)
Markus Brede
Senior Lecturer, Electronics and Computer Science (FPAS)
Joanna Nield
Senior Lecturer, Geography (FSHS)
Nicholas Sheron
Senior Lecturer, Medicine (FM)
Richard Watson
Senior Lecturer, Electronics and Computer Science (FPAS)
Alexander Belyaev
Lecturer, Physics & Astronomy (FPAS)
James Dyke
Lecturer, Electronics and Computer Science (FPAS)
Ian Hawke
Lecturer, Mathematics (FSHS)
Kevin Oliver
Lecturer, National Oceanography Centre (FNES)
Chris-Kriton Skylaris
Lecturer, Chemistry (FNES)
Trevor Thomas
Lecturer, Engineering Sciences (FEE)
Mark Sullivan
Principal Research Fellow, Physics & Astronomy (FPAS)
Taihai Chen
Research Fellow, Electronics and Computer Science (FPAS)
Jason Noble
Research Fellow, Electronics and Computer Science (FPAS)
Robin Wilson
Research Fellow, Geography (FSHS)
Grant Aitken
Postgraduate Research Student, Geography (FSHS)
David Arden
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Patrick Bechlars
Postgraduate Research Student, Engineering Sciences (FEE)
Ioannis Begleris
Postgraduate Research Student, Engineering Sciences (FEE)
Ash Booth
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Lewys Brace
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Rory Brown
Postgraduate Research Student, Civil Engineering & the Environment (FEE)
Jamie Caldwell
Postgraduate Research Student, Engineering Sciences (FEE)
Paul Chambers
Postgraduate Research Student, Engineering Sciences (FEE)
Azaria Coupe
Postgraduate Research Student, Physics & Astronomy (FPAS)
Paul Cross
Postgraduate Research Student, Engineering Sciences (FEE)
Bob De Caux
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Samuel Diserens
Postgraduate Research Student, Engineering Sciences (FEE)
Graham Elliott
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Robert Entwistle
Postgraduate Research Student, Engineering Sciences (FEE)
Christopher Frohmaier
Postgraduate Research Student, Physics & Astronomy (FPAS)
Stephen Gow
Postgraduate Research Student, Engineering Sciences (FEE)
Jonathan Gray
Postgraduate Research Student, Social Sciences (FSHS)
Joshua Greenhalgh
Postgraduate Research Student, Engineering Sciences (FEE)
Ioannis Haldoupis
Postgraduate Research Student, Chemistry (FNES)
James Harrison
Postgraduate Research Student, Engineering Sciences (FEE)
Jason Hilton
Postgraduate Research Student, Social Sciences (FSHS)
William Hurndall
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Jan Kamenik
Postgraduate Research Student, Engineering Sciences (FEE)
Marcin Knut
Postgraduate Research Student, Medicine (FM)
Konstantinos Kouvaris
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Benjamin Lowe
Postgraduate Research Student, Electronics and Computer Science (FPAS)
David Lusher
Postgraduate Research Student, Engineering Sciences (FEE)
Alvaro Perez-Diaz
Postgraduate Research Student, Engineering Sciences (FEE)
Lyuboslav Petrov
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Richard Pichler
Postgraduate Research Student, Civil Engineering & the Environment (FEE)
Craig Rafter
Postgraduate Research Student, Engineering Sciences (FEE)
Hossam Ragheb
Postgraduate Research Student, Engineering Sciences (FEE)
Sonya Ridden
Postgraduate Research Student, Mathematics (FSHS)
Kieran Selvon
Postgraduate Research Student, Engineering Sciences (FEE)
Ashley Setter
Postgraduate Research Student, Engineering Sciences (FEE)
Maike Sonnewald
Postgraduate Research Student, National Oceanography Centre (FNES)
Massimo Stella
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Jonathon Waters
Postgraduate Research Student, Engineering Sciences (FEE)
Thorsten Wittemeier
Postgraduate Research Student, Engineering Sciences (FEE)
Emanuele Zappia
Postgraduate Research Student, Engineering Sciences (FEE)
Elisabeth zu-Erbach-Schoenberg
Postgraduate Research Student, Management (FBL)
Jess Jones
Technical Staff, iSolutions
Susanne Ufermann Fangohr
Administrative Staff, Civil Engineering & the Environment (FEE)
Mihails Milehins
Alumnus, University of Southampton
Mohamed Bakoush
None, None
Brian Bonney
None, None
Ian Castro
None, None
Enrico Gerding
None, None
William Tapper
None, None
Sheng Yang
None, None