Dr Alexander Gegov
Reader in Computational Intelligence
I am currently Reader in Computational Intelligence in the School of Computing and I have been Associate Dean Research for the Faculty of Technology in the past. I have a PhD in Control Systems and a DSc in Intelligent Systems – both from the Bulgarian Academy of Sciences. I have been a recipient of a national award for best young researcher from the Bulgarian Union of Scientists. I have been Humboldt Guest Researcher at the Universities of Duisburg and Wuppertal in Germany as well as EU Visiting Researcher at the Delft University of Technology in the Netherlands.
My research interests are in the development of computational intelligence methods and their application for modelling and simulation of complex systems and networks. I have edited several books published by Springer. I have authored 4 research monographs and more than 15 book chapters also published by Springer. I have published research papers in a wide range of peer-reviewed journals and conferences including IEEE journals and conferences. I have presented invited lectures and tutorials at more than 20 international research events including IEEE and EPSRC International Conferences and Summer Schools on Fuzzy Systems, Intelligent Systems, Computational Intelligence, Cybernetics and Complexity Science.
I have been actively involved in PhD supervision and examination. I have been Co-investigator on research projects funded by EPSRC, CST and SEEDA. I have been Associate Editor for the IEEE Journal Transactions on Fuzzy Systems, the Elsevier Journal of Fuzzy Sets and Systems, the IOS Journal of Intelligent and Fuzzy Systems, the Atlantis Journal of Computational Intelligence Systems and the IOS Journal of Knowledge Based Intelligent Engineering Systems. I have also been Reviewer for several journals including IEEE journals and Assessor for three national research councils including EPSRC. I have served as Technical Committee Member for the IEEE Society of Systems, Man and Cybernetics.
- Development of computational intelligence methods using rule based systems, fuzzy logic, neural networks and evolutionary algorithms
- Validation of these methods for management, modelling, simulation and control of complex systems characterised by features such as nonlinearity, uncertainty, dimensionality and structure
- Application of these methods in a wide range of areas including transportation, business, finance and environment