Overview of Research Interests

My interests lie the area of Biologically Inspired Computing, in particular Artificial Immune Systems (AIS). I undertake research in  three main areas: optimisation, self-organising and self-adaptive systems, and understanding biological systems.

Optimisation 

• Hyper-heuristics as a practical method of solving optimisation problems encountered in the real world, e.g packing, scheduling and routing
  
• Use of optimisation techniques to minimise carbon emissions and in low-carbon technologies and renewable energy sector
• Optimisation systems that learn from experience and self-improve over time

Understanding biological systems

• How can ideas from complex biological systems  effectively be transferred to algorithms for use in engineered systems, through a process of modelling and abstraction ?

• Understanding the role of complex networks in biological systems - in particular, understanding through modelling and simulation how the topology of a biological network ultimately influences the functionality of that network.  
• Fundamentals of Collective, Adaptive Systems
  

Self-adaptive and Self-organising Systems

• Applying immunological and other biological inspiration to building self-maintaining, adaptive, autonomous, distributed systems which have to continuously operate inside some kind of viability zone
• Learning in autonomous systems e.g evolutionary robotics
  
• Adaptation and learning in distributed systems such as wireless sensor networks