Michael Odetayo is a Principal Lecturer and the Programme Manager for IT and Joint courses in the Computer Science subject group of the School of Mathematical and Information Sciences, Coventry University, UK. Before joining Coventry University, he obtained his MSc degree from the Department of Computer Science, Imperial College, London, UK. Later he became a Chief Analyst/Programmer at the Computer Centre of Ahmadu Bello University, Zaria, Nigeria, where he led many project teams that designed and developed computer based systems for the University and other organisations outside it. He was also the course co-ordinator of the Computer Centre. After completing his PhD at the Department of Computer Science, University of Strathclyde, Glasgow, UK, he joined De Montfort University, Leicester, UK, where he was a Senior Lecturer in the Department of Computer Science for many years. He has published many papers in Genetic Algorithms and Classifier Systems. His other research areas include Expert Systems, Neural Networks, Fuzzy Logic, Data Mining and Machine Learning. He is a member of the International Programme Committee of the International Mendel Conference on Soft Computing.

Research Interests

Evolutionary systems - His current primary research area is in the field of evolutionary computation and learning systems. At the moment the
systems that he is concentrating on include:

1. Hybrid/Adaptive Genetic based systems

He is interested in exploring ways of combining Genetic Algorithms with other heuristics or weak methods. Although Genetic Algorithms are general-purpose methods, they do fail sometimes to reach optimal solutions at acceptable times. However, they have some advantages over other methods (such as the ability to produce many optimal or near optimal solutions at a time) which he believes should be exploited. A hybrid system seems to be an excellent method of achieving that goal. The objective is to develop a set of problem solving heuristics that intelligently and dynamically integrate Genetic Algorithms with other similar heuristics so as to exploit and maximise their strengths.

2. Learning systems in medical applications

He is interested in employing Evolutionary Systems, Neural Networks, Fuzzy Logic systems and similar Artificial Intelligent based systems in the knowledge discovery and data mining of medical data.

PUBLICATIONS

1990

ODETAYO, M.O. (1990) On genetic algorithms in machine learning and optimisation, PhD Thesis. Glasgow: University of Strathclyde.

CONFERENCE PROCEEDINGS

2002

ODUSANYA, A.A., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., LAKSHMI, M.S. and SHERBET, G.V. (2002) Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI2002), A genetic algorithm-based model for breast cancer prognosis, Orlando, USA, 14-18 July pp. 394-397

SEKER, H., ODETAYO, M.O., PETROVIC, D. and NAGUIB, R.N.G. (2002) Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI2002), Prognostic prediction in prostate cancers: statistical, neural networks and fuzzy approaches, Orlando, USA, 14-18 July pp. 402-405 ISBN: 980-07-8150-1

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G. and HAMDY, F.C. (2002) Proceedings of the IEEE EMBS UK & ROI Postgraduate Conference on Biomedical Engineering and Medical Physics, A hybrid system for prognosis in prostate cancer, Aston University, Birmingham, 2-3 July pp. 18 ISBN: 0-9543157-0-7

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L. and LAKSHMI, M.S. (2002) Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE02), An artificial neural network based feature evaluation index for the assessment of clinical factors in breast cancer survival analysis, Winnipeg, Canada, pp. 1211-1215 ISBN: 0-7803-7514-9

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L., LAKSHMI, M.S. and SHERBET, G.V. (2002) Proceedings of the American Association for Cancer Research, Assessment of nodal involvement in breast cancer patients using histological and image cytometric prognostic factors, San Francisco, USA, pp. 40

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L., LAKSHMI, M.S. and SHERBET, G.V. (2002) Proceedings of the IEEE International Conference on Fuzzy Systems, Soft feature evaluation indices for the identification of significant image cytometric factors in assessment of nodal involvement in breast cancer patients, Hawaii, USA, pp. 1592-1595 ISBN: 0-7803-7281-6

2001

SEKER, H., ODETAYO, M.O., PETROVIC, D. and NAGUIB, R.N.G. (2001) Proceedings of the Symposium on Research in Computers Science, Prognostic prediction in prostate and breast cancer: comparison of statistical, neural networks and fuzzy approaches, In: MO Odetayo (Ed), Coventry University, TechnoCentre, pp. 31-35 ISBN: 1-90818-05-2

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G. and HAMDY, F.C. (2001) Proceedings of the European Symposium on Fuzzy Logic and Technology, Statistical and soft feature evaluation indices for prostate cancer prognostic factor asessments, De Montfort University, Leicester, pp. 26-29

2000

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G. and HAMDY, F.C. (2000) In P Sincak, J Vascak, V Kvasnicka, R Mesiar (eds): The State of the Art in Computational Intelligence, A soft measurement technique for searching significant subsets of prostate cancer prognostic markers, Heidelberg, New York, pp. 325-328 ISBN: 1615-3871

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G. and HAMDY, F.C. (2000) Proc of the World Congress on Medical Physics and Biomedical Engineering, Ranking prostate cancer prognostic markers using a fuzzy k-nearest neighbour algorithm, Chicago, USA. 23-28 July, CD-ROM pp. 4008-33988

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L., LAKSHMI, M.S. and SHERBET, G.V. (2000) Proceedings, IEEE International Conference on Information Technology Applications in Biomedicine, A fuzzy measurement-based assessment of breast cancer prognostic markers, Arlington, VA, USA, pp. 174-178 ISBN: 0-7803-6449-X

1998

ODETAYO, M.O. (1998) Proceedings, International Conference on Genetic Algorithms, Optimization Problems, Fuzzy Logic, Neural Networks and Rough Sets, Generating rules using a Holland based classifier learning system, Brno, Czech Republic, pp. 80-85 ISBN: 80-214-1199-6

1997

ODETAYO, M.O. (1997) Proceedings, IEEE International Euromicro Conference, Empirical study of the interdependencies of genetic algorithms parameters, Budapest, Hungary, pp. 639-643 ISBN: 1089-6503

ODETAYO, M.O. and FOLKER, M. (1997) Proceedings of Computer Measurement Groups International Conference, Conjecture upon the analysis of computer performance by means of evolutionary computing, USA. pp. 425-435

1996

ODETAYO, M.O. (1996) Proceedings of Mendel'96, 2nd International Mendel Conference on Genetic Algorithms, Relationship between replacement strategy and population size, Brno, Czech. June

1995

ODETAYO, M.O. (1995) Proceedings of Mendel'95, Replacing one or two individuals at a time during reproduction: an investigation, Brno, Czech Republic.

ODETAYO, M.O. (1995) Proceedings of AISB Workshop on Evolutionary Computation, Rule induction using classifier based learning method: an investigation, AISB.

ODETAYO, M.O. (1995) Proceedings of ADT Conference, Structured genetic algorithm (SGA): a new genetic model for overcoming low viability and low variation, ADT.

1993

ODETAYO, M.O. (1993) IEE Colloquium on Genetic Algorithms for the Control Systems Engineering, Optimal population size for genetic algorithms: an investigation, London, Savoy Place. May

1992

MCGREGOR, D.R., ODETAYO, M.O. and DASGUPTA, D. (1992) Proceedings of the IEE International Symposium on Intelligent Control, Adaptive control of a dynamic system using genetic-based methods, Glasgow, Institute of Electrical Engineers, London. August

1989

MCGREGOR, D.R., FREDERIKSEN, A. and ODETAYO, M.O. (1989) presented at IEE Colloquium on Knowledge Based Systems, Design configuration using genetic algorithms, Edinburgh, UK, Heriot-Watt University.

ODETAYO, M.O. and MCGREGOR, D.R. (1989) Proceedings of the Third International Conference on Genetic Algorithms, Genetic algorithm for inducing control rules for a dynamic system, USA, George Mason University.

CHAPTERS IN BOOKS

2000

ODUSANYA, A.A., ODETAYO, M.O., PETROVIC, D. and NAGUIB, R.N.G. (2000) A review of soft computing and gynaecological cancer In: Quo Vadis Computational Intelligence? - New Trends and Approaches in Computational Intelligence (Eds: P Sincak & J Vascak). Springer-Verlag. pp. 485-490. ISBN: 3-7908-1324

1995

ODETAYO, M.O. and DASGUPTA, D. (1995) Controlling a dynamic physical system using genetic based learning methods In: Practical Handbook of Genetic Algorithms New Frontier Volume II, (edited). Lance Chambers.

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L., LAKSHMI, M.S. and SHERBET, G.V. (2002) Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches Anticancer Research 22 pp. 433-438.


PAPERS IN JOURNALS

2002

SEKER, H., ODETAYO, M.O., PETROVIC, D., NAGUIB, R.N.G., BARTOLI, C., ALASIO, L., LAKSHMI, M.S. and SHERBET, G.V. (2002) Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches Anticancer Research 22 pp. 433-438.

1995

ODETAYO, M.O. (1995) Knowledge acquisition and adaptation: a genetic approach Expert Systems 12 (1) .

OTHER EXHIBITION OR CONFERENCE ROLES

2002

ODETAYO, M.O. (2002) Computational intelligence methods in medicine, Organiser. 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI2002). 14-18 July Orlando, USA.

ODETAYO, M.O. (2002) Programme Committee Member , Programme Committee Member. 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI2002). 14-18 July Orlando, USA.

1998

ODETAYO, M.O. (1998) Rule induction using a Holland learning classifier system, Research Seminar. 28 January Coventry University.