Dr Alexander Gegov
Biography
I am Associate Professor in Computational Intelligence in the School of Computing at the University of Portsmouth. I am also Visiting Professor in Control Theory in the English Faculty of Engineering at the Technical University of Sofia. I have been Associate Dean Research for the Faculty of Technology at the University of Portsmouth. I have a PhD in Cybernetics and a DSc in Artificial Intelligence – 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. I have also been EU Visiting Researcher at the Delft University of Technology in the Netherlands.
My research interests are in the development of artificial intelligence and machine learning methods as well as their application for modelling and simulation of complex systems and networks. I have guest edited several special issues of journals and books with conference proceeding published by IEEE and Springer. I have authored 5 research monographs and more than 20 book chapters published by Springer. I have also authored more than 150 articles and papers in a wide range of peer-reviewed specialised journals and international conferences including IEEE journals and conferences. I have presented more than 20 invited lectures and tutorials at international scientific events including IEEE, EPSRC and NATO Conferences and Summer Schools on Artificial Intelligence, Fuzzy Systems, Neural Networks, Intelligent Systems, Computational Intelligence, Cybernetics and Complexity Science. I have been actively involved as PhD Supervisor and PhD Examiner. I have also been Principal Investigator and Co-Investigator on research projects funded by NATO, EU, EPSRC and Innovate UK.
I am Editorial Board Member for the IEEE Transactions on Artificial Intelligence, the IEEE Transactions on Fuzzy Systems, the Elsevier Journal of Fuzzy Sets and Systems and the Springer International Journal of Computational Intelligence Systems. I am also Reviewer for several journals including IEEE Transactions on Neural Networks and Learning Systems as well as Assessor for several research councils including the Australian Research Council. I am currently Member of the Soft Computing Technical Committee of the IEEE Society of Systems, Man and Cybernetics as well as Member of the Emergent Technologies Technical Commitee and the Outstanding Paper Award Committee of the IEEE Computational Intelligence Society. I am also Member of the IEEE Working Group on Explainable Artificial Intelligence and the IEEE Task Force on Explainable Fuzzy Systems as well as Member of the NATO Research Task Group on Reinforcement Learning and the NATO Exploratory Team on Explainable Artificial Intelligence.
New mailCopyResearch interests
- Development of artificial intelligence and machine learning methods using fuzzy systems, neural networks and evolutionary algorithms
- Validation of these methods for management, modelling, simulation and control of complex systems and networks characterised by nonlinearity, uncertainty, dimensionality and connectivity
- Application of these methods in areas such as public security (in collaboration with NATO), financial forecasting, medical diagnosis and environmental modelling and their evalution in terms of feasibility, accuracy, efficiency and transparency
Research outputs
2024
Energy efficiency evaluation of Artificial Intelligence algorithms
Gegov, A., Isiaq, O., Jafari, R., Penev, K.
1 Oct 2024, In: Electronics. 13, 19, 11p., 3836
Unveiling vulnerabilities in deep learning-based malware detection: Differential privacy driven adversarial attacks
Arabikhan, F., Gegov, A., Shojafar, M., Taheri, R.
8 Aug 2024, In: Computers and Security
Medical image classification using a many to many relation, multilayered fuzzy systems and AI
Akula, K. K., Akula, M., Arabikhan, F., Gegov, A., Jafari, R., Jouffroy, R., Marcucci, M.
3 Jul 2024, In: WSEAS Transactions on Computers. 23
Integrating structural causal model ontologies with LIME for fair machine learning explanations in educational admissions
Bednar, P., Gegov, A., Igoche, B. i., Matthew, O.
25 Jun 2024, In: Journal of Computing Theories and Applications. 2, 1, p. 65-85, 21p.
Medical image classification using a quantified hazard ratio and a multilayer fuzzy approach
Akula, K. K., Akula, M., Gegov, A.
18 Feb 2024, In: Computing and Artificial Intelligence. 2, 1, 15p., 450
Integrated generative adversarial networks and deep convolutional neural networks for image data classification: a case study for COVID-19
Abidah Shahrul, N., Chaw Seng, W., Gegov, A., Muhammad Naim Ku Khalif, K., Syafadhli Abu Bakar, A.
18 Jan 2024, In: Information. 15, 58, 17p., 58
2023
Large-scale group decision-making method using hesitant fuzzy rule-based network for asset allocation
Abdul Rahman, S. F., Gegov, A., Ku Khalif, K. M. N., Shafie, S., Yaakob, A.
26 Oct 2023, In: Information. 14, 11, 18p., 588
Artificial intelligence-based medical image classification using a multilayer fuzzy approach
Akula, K. K., Arabikhan, F., Gegov, A.
25 Oct 2023, In: WSEAS Transactions on Computers. 22
TOPSIS based Renewable-Energy-Source-Selection using Moderator Intuitionistic Fuzzy Set
Gegov, A., Joshi, B. P., Joshi, N.
1 Oct 2023, In: International Journal of Mathematical, Engineering and Management Sciences. 8, 5, p. 979-990, 12p.
Modelling and simulation of traffic light control
Boneva, Y., Gegov, A., Vatchova, B.
28 Sep 2023, In: Cybernetics and Information Technologies. 23, 3, p. 179-191, 13p.