Professor Emma Hart

Director of CEC

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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.


  • 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


Prof. Hart gained a 1st Class Honours Degree in Chemistry from the University of Oxford, followed by an MSc in Artificial Intelligence from the University of Edinburgh. Her PhD, also from the University of Edinburgh, explored the use of immunology as an inspiration for computing, examining a range of techniques applied to optimisation and data classification problems. 

She moved to Edinburgh Napier University in 2000 as a lecturer, and was promoted to a Chair in 2008 in Natural Computation. She continues to research in the area of developing novel bio-inspired techniques for solving a range of real-world optimisation and classification problems, as well as exploring  the fundamental properties of immune-inspired computing through modelling and simulation.

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Areas of Expertise link icon

  • Bio-inspired Computing
    In our increasingly global economy, companies are under pressure to optimise their activities in order to gain a competitive edge or to even remain sustainable. our optimisation research specialises in developing state-of-the-art algorithms that are capable of obtaining solutions to complex...
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+44 (0)131 455 2783

Room C54
Merchiston Campus
10 Colinton Road
EH10 5DT

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    PhD Project Involvement

    Lyndsey Jenkins (PhD 2015-)
    Enhancing the capacity for workplace learning and innovation in Scotland.
    Christopher Stone (PhD 2015-)
    Software healing inspired by the immune system.
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    Andreas Steyven (PhD 2013-)
    Exploiting cooperative behaviour to guide open-ended evolution in multi-robot applications. This research is concerned with the evolution and adaptation of robots in evolutionary robotics (ER) in an open-ended evolutionary (OEE) environment. OEE processes are objective free evolutionary...
    Emilia Sobolewska (PhD 2009-)
    Learning to cope with non discretionary use of digital techologies. Technology surrounds people; it functions as their best friend and the worst enemy. From a trip to the local supermarket, to almost every aspect of people’s professional and social lives technology...
    Dana Khartabil (PhD 2015-)
    Visualisation of arguments.
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    Aurelien Ammeloot (PhD 2013-)
    Understanding and designing interactive collaborative spaces. I am currently working on a PhD programme in the Centre for Interaction Design, supervised by Prof. David Benyon and Dr. Oli Mival. I am investigating the state of the art in interactive and...
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    Samuel Chinenyeze (PhD 2012-)
    Energy-efficient (green) software architecture for smart pervasive systems. With the growing need of the industry and due to high business demands, there have consequently been high demands of IT products to address these needs (majorly seen in the automation of...
    Ewan Gunn (PhD 2008-)
    Exploiting learning across hierarchies within multi-agent systems in complex environments. One of the challenges of artificial intelligence in computer games is the effective use of learning to either automate the creation of intelligent agents for the release of a game, or to allow agents...
    See all PhD projects

    Recent Publications

    Capodieci, N., Hart, E., Cabri, G. (2016). An Artificial Immunology Inspired Approach to Achieving Self-Expression in Collective Adaptive Systems. IEEE Transactions on Autonomous and Adaptive Systems, to appear, (), .

    Hart, E., Sim, K. (2016). A Hyper-Heuristic Ensemble Method for Static Job-shop Scheduling. Evolutionary Computation, (pre-print, accepted for publication May 2016), (), .

    Salah, A., Hart, E. (2016). Validating the Grid Diversity Operator: an Infusion Technique for Diversity Maintenance in Population-based Optimisation Algorithms. In: (Ed.) Applications of Evolutionary Computation, 9598, () ( ed.). (pp. 11-26). : . .

    Segredo, E., Paechter, B., Hart, E., Gonzalez-Vila, C. (2016). Hybrid Parameter Control Approach Applied to a Diversity-based Multi-objective Memetic Algorithm for Frequency Assignment Problems. In: (Ed.) 2016 IEEE Congress on Evolutionary Computation (CEC), , () ( ed.). (pp. In Press). : . .

    See all publications

    Supervised dissertations

    Kahembwe, E. (2014). A Flexible Framework for Analysing Genetic Algorithms In Go (BSc (Hons) Games Development Dissertation). Edinburgh Napier University (Kerridge, J., Hart, E.).

    Maroulis, G. (2014). Comparison between Maximum Entropy and Naïve Bayes classifiers: Case study; Appliance of Machine Learning Algorithms to an Odesk’s Corporation Dataset (MSc Information Systems Development Dissertation). Edinburgh Napier University (Hart, E., Urquhart, N.).

    McMillan, C. (2014). Comparison of Pathfinding Algorithms Using the GPGPU (BEng (Hons) Games Development Dissertation). Edinburgh Napier University (Hart, E., Urquhart, N.).

    Sim, K. (2010). Development of a Problem Generator for Bin Packing Problems: An Analysis of Benchmark Problems and Current Stochastic Deterministic Problem Solving Techniques (MSc Advanced Software Engineering Dissertation). Edinburgh Napier University.

    See all supervised dissertations