Complexity, Emergence & Upscaling

Specific research:

• general methodologies for variable reduction on networks

• the identification of continuum limits in particle systems

• coherent phenomena in turbulent systems.

Applications:

• complex systems theory
  
• weather & climate
• controlling stability of fusion plasmas.

Complex Fluids and Complex flows

Specific research:

• Granular and foam systems - explicit particle based simulations of the flow properties
• Soft (Brownian) systems - wavelet-based techniques to incorporate long range hydrodynamic coupling.
• Simulating flow through particular geometries using up-scaled pseudo particles (versions of Dissipative Particle Dynamics) to capture viscoelastic and intertial effects.

Applications:

• flow of people, cars
• granular materials
• diagnosis of cancer, hypertension, heart disease

Clustering, Condensation and Jamming

Specific research:

• how fast do clusters grow, how large, and even effectively infinite?
• localised condensate (e.g. traffic jam) vs background (e.g. flowing traffic) at critical density:
• connecting biology (molecular transport, ant trails), social sciences (traffic and transport modeling) and physics (granular media, Bose Einstein condensation).

Applications:

• weather & climate
• flow of people, cars
• granular materials

Complex Networks & their dynamics

Specific research:

• neuroscience - how neuronal details such as spatial extension and the propagation of calcium waves influence overall neural computation.
• markets - how local bartering rules can lead to the emergence of market prices with realistic stochastic dynamics.
• epidemiological research - how contact networks propagating infection interact with the social networks propagating adoption of preventative measures.
• biodiversity- how the pattern of clone boundaries conforms to classical growth interface models
• early genetic evolution and speciation - role of fitness and horizontal gene transfer.

Applications:

• infectious diseases
• neural computing
• data storage
• dynamics of opinions & markets

Network Statistical Inference

Specific research:

• multiple fields, from molecular biology to health and economics.
• novel methods for network learning, including Bayesian approaches, MCMC and penalized likelihood methods.
• in cancer protein signalling networks - breaking new ground in the field and have implications for other diseases as well as signalling biology more generally.
• plant pathology - specifically the response of the model organism
• public health - relationships, as captured in a social network, can influence health status (over and above the contribution of other factors):
• we are developing statistical network models to analyse a suitable database on adolescent health.
• social economics - advanced inference approaches to probe the relationship between subjective well-being and risk-taking.

Applications:

• diagnosis of cancer, hypertension, heart disease
• data storage

New applications of statistical mechanics

Specific research:

• well developed set of tools for fresh applications in molecular biology, traffic theory, opinion dynamics

Applications:

• granular materials
• dynamics of opinions and markets
• molecular biology