The Group has enjoyed considerable support for its research primarily from EPSRC and the EU. The NCRG has also attracted significant competitive funding from theBBSRC, the Royal Society, the Leverhulme Trust and theBritish Council and a large amount of industrial funding (last 5 years awards totalling in excess of £2M).
We welcome enquiries from PhD-qualified researchers from all countries outside the UK wishing to apply for a European Commission-funded Marie Sklodowska-Curie Individual Fellowship to come to work with us at Aston.
Subject areas might include Biomedical Information Engineering and Signal Processing; Health Informatics; Statistical Physics of Networks, Communication, Learning and Advance Inference Methods; Complex Systems and Networks; Non-linear Differential and Stochastic Equations, Chaos and turbulence; Theory and Simulation of Biomolecules. Please contact the relevant member of staff or David Saad for further details.
NCRG has a strong research record in the area of pattern analysis and machine learning. Prior activity has included major theoretical and algorithmic advances and inventions. For example, the GTM (Generative Topographic Mapping), MDN (Mixture Density Network), NeuroScale, and hierarchical GTM - all highly exploited models around the world - were all invented and developed by the NCRG members. Novel approaches to algorithm design and implementation have been invented in the group, facilitating new ways to extract information for complex data sources. Part of this work has been embodied in software, known as NetLab, which is widely used. These methods have also been used in a broad range of applications, particularly in the biomedical area. Among the researchers working on the development of pattern analysis techniques and their application are Dr Dan Cornford, Dr Randa Herzallah, Prof. David Lowe and Prof. Ian Nabney. In Dr Max Little group novel nonlinear signal processing and machine learning approaches for biomedical, biological, environmental and other scientific time series analysis applications are developed.
Max Little: A test for Parkinson's with a phone call
Hidden Connections: an Inaugural Lecture by Prof Ian Nabney
The NCRG work in the application of statistical mechanics techniques to complex interacting systems resulted in several significant contributions, in areas linked to the theory of learning, information theory, cryptography and hard computational problems. Activities linking statistical physics and information theory improved existing bounds in coding theory and provided insight that led to the development of new state-of-the-art error-correcting codes. Similar techniques have been employed to investigate multi-user communication, failures in electricity grids and distributed storage of data. Statistical mechanics has a very broad application regime under the general auspice of many body physics, for example, soft condensed matter systems like polymers, liquid crystals and fluids, and particularly in biological (immunology, population biology and atherosclerosis) and bioinformatic (protein and gene sequencing) mechanisms (see Dr Amit Chattopadhyay). Another direction of the research is the theory of strongly correlated systems in condensed matter and quantum optics. The collective behaviour of social and biological systems and their interdependency, in addition to traditional physics models are studied using statistical physics. Among the researchers working in this area are Dr Jort van Mourik, Dr Juan P Neirotti, Dr Igor Yurkevich, Dr Roberto Alamino, and Prof. David Saad.
NCRG has developed a generic expertise in the area of complex systems. This activity encompasses both the modelling and understanding of complex dynamical systems, and the development of novel statistical and physical inference methods. The former looks at, for instance, the emergence of collaboration and hierarchy in evolving learning agents and arrays of micromechanical systems (MEMS), the dynamics of econo-systems (the field known as econophysics), environmental modelling, modelling of biological and chemical systems, and environmental modelling; while the latter focuses on new ways to extract information from complex systems, combining mathematical understanding and novel algorithmic development. A unique expertise developed in the NCRG is the ability to link and exploit methods that have been developed in the statistical physics community to model and analyse complex systems. Among the researchers working in this area are Dr Sudhir Jain, Prof. David Lowe, Dr Jort van Mourik, Dr Juan P Neirotti, Dr Michael Stich, Dr Randa Herzallah, Dr Roberto Alamino, Dr Amit Chattopadhyay, and Prof. David Saad. Otti D'Huys studies the dynamics of complex time-delay systems.
NCRG is active in fluid dynamics research. Understanding the complex interactions between coherent structures and turbulent fluctuations in fluid flows found in geophysical fluid dynamics and quantum fluids such as Bose-Einstein condensates and superfluid helium is the work done in Dr Jason Laurie group. Research is undertaken in Dr Tomas Johansson group in inverse ill-posed problems, where methods are proposed and investigated for the stable reconstruction of physical quantities in heat, fluid and wave models (partial partial differential equations) sensitive to measurement noise. Dr Sotos Generalis works in the field of fluid dynamics and turbulence.
Turbulence by Prof Friedrich Busse: Leverhulme Lecture 2013
Another area of the NCRG research is related to the field of nonlinear stochastic systems that are described by stochastic ordinary, partial, or delay differential equations. One example of such system is the Nonlinear Schrodinger Equation driven by spatio-temporal Gaussian noise. Such systems describe e.g. propagation of optical solitons in fibre transmission link with noise emitting optical amplifiers. Another example is the Complex Ginzburg-Landau equation under the influence of time-delay and noise. Such systems describe e.g. waves and oscillations in chemical and biochemical systems. In the study the traditional perturbational approach was applied to render the stochastic PDE to the system of stochastic ODEs (Langevin equations) with multiplicative noise for the parameters of an optical soliton. Then assuming that noise is white in both spatial and time coordinates a series of approaches were used to determine the distribution of the solution (including the Fokker-Planck equation, functional integration, direct Monte Carlo simulations). While population biology has long been accepted in the main stream of biological research and is seen as a key application area of physics and mathematics in biology, the implication of randomness through uncertainties in the dynamical evolution of such phenomena have only recently started creating waves due to their tremendous importance in medical research. Combining tools from stochastically forced PDEs and statistical multivariate analysis, frontline research in fluid mechanical turbulence, alongside modelling crack propagation in nanomaterials is conducted in the group ( Dr Amit Chattopadhyay). Among the researchers working in this area are Dr Michael Stich and Dr Jason Laurie. Mathematics of Signal Representation is the subject of Dr Laura Rebollo-Neira group.
Systems of biological and (bio-)chemical nature are paradigmatic examples for complex and nonlinear systems. With the ultimate aim of not only to understand natural systems, but also to control and engineer them, they are studied within the NCRG using a wide range of analytical and numerical methods like differential equations, networks and graph theory, and agent-based modelling. Hybrid methods of simulating molecular systems, that model them at different scales in space and time simultaneously in a unified 'multiphysics' framework, is underway at NCRG. One of the applications includes all-atom simulations of whole viruses in water. For details see web page of Dr Amit Chattopadhyay, Dr Michael Stich, Dr Roberto Alamino, and Dr Dmitry Nerukh.
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