Professor Ajit Narayanan

Professor and Head of Research

Phone: +64 9 921 9999 Extn 9345

Email: ajit.narayanan@aut.ac.nz

Physical Address:
School of Engineering, Computing and Mathematical Sciences (D-75),
Auckland University of Technology,
AUT Tower, 2-14 Wakefield Street,
Auckland, 1010

Qualifications:

BSc (Hons), University of Aston in Birmingham, 1973.
PhD in Philosophy, University of Exeter, 1976.

Memberships and Affiliations:

  • Member of Institute of Electrical and Electronics Engineers (IEEE)
  • Member of Chair of Local (NZ) Chapter of Association for Computing Machinery (ACM)

Teaching Areas:

  • Artificial intelligence, machine learning and nature-inspired computing
  • Bioinformatics, DNA and quantum computing
  • System security and technologies
  • Computational statistics
  • Cognitive science and mind/brain

Research Areas:

  • Application of artificial intelligence and nature-inspired techniques in bioinformatics, systems biology, healthcare informatics and geoinformatics
  • Computational statistics, modelling and simulation
  • Computational linguistics
  • Quantum computing and DNA computing
  • Artificial intelligence and mind/brain

Publications:

A. Refereed journal publications
(Single authored unless otherwise indicated)

  1. Prejudice and educational accountability, A. Narayanan and R. C. Whitfield, Patterns of Prejudice, 11, 1977, 5 pp.

  2. Slip into LISP: How to choose a LISP interpreter, Artificial Intelligence Review, 1 (1), 1986, pp. 53-68.

  3. AI and accountability, AI and Society, 1 (1), 1987, pp. 60-62. (Viewpoint article)
  4. Fodor and Pylyshyn on connectionism, Artificial Intelligence Review, 2 (3), 1988, pp. 195-213.

  5. Object-oriented representations, causal reasoning and expert systems,  A. Narayanan and Y. Jin,  Expert Systems, 8 (1), 1991, pp. 13-17.

  6. On a human-centred approach to database systems, B. Lings, N. Adablah, L. Foster, Y. Jin and  A. Narayanan,  AI and Society, 5 (2), 1991, pp. 128-141.

  7. A computer model for transliterated Arabic,  A. Narayanan and S. Mehdi, Applied Computer Translation, 1 (3), 1991, pp. 5-28.

  8. An object-oriented approach to expert diagnostic systems,  A. Narayanan and Y. Jin,  Journal of Object-Oriented Programming, 4 (6), 1991, pp. 19-29.

  9. Is connectionism compatible with rationalism?,  Connection Science, 4 (3-4), 1992, pp. 271-292.

  10. On abstract automata and their application to finite-state Arabic morphology,  A. Narayanan and L. Hashem,  Artificial Intelligence Review, 7 (6), 1994, pp. 373-399.

  11. Language visualisation: Applications and Theoretical Foundations of a Primitive-Based Approach,  A. Narayanan, D. Manuel, L. Ford, D. Tallis and M. Yazdani,  Artificial Intelligence Review, 9 (2-3), 1995, 215-235. Reprinted in  Integration of Natural Language and Vision Processing, Volume 2: Intelligent Multimedia, P. McKevitt (Ed.), Kluwer Academic Press, 1995.

  12. Revisable knowledge discovery in databases (RKDD), International Journal of Intelligent Systems, 11 (2), 75-96, 1996.

  13. On using animations in Court.  A. Narayanan, G. Penny, S. Hibbin, S. Lochun and W. J. Milne.  Information and Communications Technology Law, 8 (2), 1999, pp. 151-163.

  14. Quantum artificial neural network architectures and components. A. Narayanan and T. Menneer,  Information Sciences, 128 (3-4), 2000, 231-255.

  15. Creating rules from trained neural networks using genetic algorithms. E. Keedwell,  A. Narayanan and D. Savic, International Journal of Computers, Systems and Signals, Volume 1, 2001, pp 30-43.

  16. Can animations be safely used in Court? A. Narayanan and S. Hibbin,  Artificial Intelligence and Law, Volume 9, Number 4, 2002, pp 271-293.

  17. Mining viral protease data to extract cleavage knowledge.  A. Narayanan, X. Wu and Z. R. Yang.  Bioinformatics 18 (1): 5-13, 2002.

  18.  Iconic SQL: Practical issues in the querying of databases through structured iconic expressions.  A. Narayanan and T. Shaman.  Journal of Visual Languages and Computing  13, 2002, 623-647.

  19. Regular Biosequence Pattern Matching with Cellular Automata. K. Laurio, F. Linåker and A. Narayanan.  Information Sciences, 146(1-4), 2002, 89-101.

  20. Machine learning techniques for bioinformatics.  A. Narayanan, E. Keedwell and B. Olsson.  Applied Bioinformatics, 1(4), 2002, 191-222.

  21. Searching for discriminatory rules in protease proteolytic cleavage activity using genetic programming with a min-max scoring function. Z. R. Yang, R. Thomson, T. C. Hodgman, J. Dry, A. K. Doyle,  A. Narayanan and X. Wu.   Biosystems 72, 2003, 159-176.

  22. Single-layer neural networks for gene expression analysis. A. Narayanan, E. C. Keedwell, S. S. Tatineni and J. Gamalielsson.  Neurocomputing, 61: 217 - 240, 2004.

  23. Discovering gene regulatory networks with a neural-genetic hybrid. E.C. Keedwell and  A. Narayanan.  IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2005, Vol. 2, No. 3: 231-243. 2005.

  24. What distinguishes general practitioners from consultants, according to patients? A. Narayanan and M. Greco, Journal of Healthcare Management and Marketing, 2007, 1(1): 80-87.

  25. AI and accountability. AI and Society, 2007, 21:669-671. Original article from 1987 reprinted in 20th anniversary edition of journal.

  26. Assessing the professional performance of UK doctors: an evaluation of the utility of the General Medical Council patient and colleague questionnaires. J.A. Campbell, M.J.Greco, J. Johnson, S. Richards, A. Dickens and A. Narayanan. Quality and Safety in Health Care, 2008, 17: 187-193.

  27. Resistance gene expression determines the in vitro chemosensitivity of non-small cell lung cancer (NSCLC). Sharon Glaysher, Dennis Yiannakis, Francis G Gabriel, Penny Johnson, Marta E Polak, Louise A Knight, Zoe Goldthorpe, Katharine Peregrin, Mya Gyi, Paul Modi, Joe Rahamim, Mark E Smith2, Khalid Amer, Bruce Addis, Matthew Poole, Ajit Narayanan, Tim J Gulliford, Peter E Andreotti and Ian A Cree. BMC Cancer. 2009. 9:300 http://www.biomedcentral.com/1471-2407/9/300 (IF 3.08)

  28. The molecular basis of the chemosensitivity of metastatic cutaneous melanoma to chemotherapy. Katharine A Parker, Sharon Glaysher, Marta Polak, Francis G Gabriel, Penny Johnson, Louise A Knight, Matthew Poole, Ajit Narayanan, Jeremy Hurren and Ian A Cree. Journal of Clinical Pathology. 2010, doi: 10.1136/jcp.2010.080119, 9pp. (IF 2.324)

  29. Molecular basis of chemosensitivity of platinum pre-treated ovarian cancer to chemotherapy. Glaysher S, Gabriel FG, Johnson P, Polak M, Knight LA, Parker K, Poole M, Narayanan A, Cree IA. British Journal of Cancer 103(5):656-662 2010.

  30. Validation of a multi-source feedback tool for use in General Practice. J. Campbell, A. Narayanan, B. Burford and M. Greco (2010). Education for Primary Care, 21 (3), May 2010, pp. 165-179.

  31. Generalisability in unbalanced, uncrossed and fully nested studies. A. Narayanan, J. Campbell and M. Greco (2010). Medical Education 44 (4): 367-378. (IF 2.6).

  32. Applications in unusual contexts in engineering mathematics: Students’ Attitudes. N Gruenwald, G. Sauerbier, A. Narayanan, S. Klymchuk and T. Zverkova. Mathematics Teaching-Research Journal Online, Vol. 4, No. 1, 2010, pp. 52-67.

  33. RFID enabled smartcards as a context-aware personal health node. D. T. Parry and A. Narayanan. Healthcare Informatics Review online, 14(3), 2010, 10-16. http://www.hinz.org.nz/uploads/file/Journal_Jun10/Parry_P10.pdf

  34. Measuring the quality of hospital doctors through colleague and patient feedback. A. Narayanan, M. Greco, H. Powell and T. Bealing. Journal of Management & Marketing  in Healthcare, Vol. 4, No. 3, 2011, 180-195.

  35. A multi-agent cellular automaton for grapevine growth and crop simulation. A. Narayanan, S. Shanmuganathan and N. Robinson. International Journal of Machine Learning and Computing, 1(3), 2011, pp 291-296.

  36. Outlier detection using humoral mediated clustering. W. Ahmad and A. Narayanan. 2012. International Journal of Computational Intelligence and Applications, Vol. 11, No. 1, 21pp. DOI: 10.1142/S1469026812500034

  37. Humoral artificial immune system for supervised learning. W. Ahmad and A. Narayanan. 2012. International Journal of Computational Intelligence and Applications, Vol. 11, No. 1, 19pp. DOI: 10.1142/S1469026812500046

  38. Gene expression rule discovery with a multi-objective neural-genetic hybrid. E.C. Keedwell and A. Narayanan. 2013. International Journal of Data Mining and Bioinformatics. Vol. 7, No. 4, 376-396.

  39. Society under threat... but not from AI. 2013. Artificial Intelligence & Society.  28 (1): 87-94.

  40. The effects of different representations on static structure analysis of computer malware signatures. A. Narayanan, Y. Chen, S. Pang and B. Tao. 2013. The Scientific World Journal, vol. 2013, Article ID 671096, 8 pages, doi:10.1155/2013/671096.

  41. The reliability of big ‘patient satisfaction’ data. A. Narayanan, M. Greco, H. Powell and L. Coleman. Big Data, 1(3): 41-51. 2013. DOI: 10.1089/big.2013.0021.

  42. The Dental Practice Questionnaire: A patient feedback tool for improving the quality of dental practices.  A. Narayanan and M. Greco. Australian Dental Journal, 59(3), 2014, 334-348. DOI: 10.1111/adj.12200.

  43. Community pharmacy performance evaluation: Reliability and validity of the Pharmacy Patient Questionnaire (PPQ). A. Narayanan, M. Greco, P. Reeves, A. Matthews and J. Bergin. International Journal of Healthcare Management, 7(2), 2014, 103-119.

  44. Patient experience of Australian General Practices. A. Narayanan and M. Greco. Big Data. Mar 2016, 4(1): 31-46. DOI: 10.1089/big.2016.0010   


B. Refereed Conference papers, and book chapters
(Single authored unless otherwise indicated; refereed unless otherwise indicated (NR))


  1. What is it like to be a machine?, in S. Torrance (ed.)  The Mind and the Machine, Ellis Horwood, 1984, pp. 79-87.  Second Anglo-French Philosophy Colloquium, Middlesex Polytechnic, April 1983.

  2. Why AI cannot be wrong, in K. S. Gill (ed.),  Artificial Intelligence for Society, Wiley, 1986, pp. 43-53.  Proceedings of the Third Annual Conference on AI for Society, Brighton Polytechnic, 1985.

  3. Memory models of man and machine, in  Artificial Intelligence: Principles and Applications, M. Yazdani (ed.), Chapman-Hall, 1986, pp. 226-258.

  4. Artificial Intelligence Terminology: A Reference Guide, C. Beardon (Ed.), Ellis Horwood, 1989. (Several entries.)

  5. Cognitive architecture and connectionism, in R. Forsyth (ed.), Machine Learning: Principles and Techniques, Chapman and Hall, 1989, pp. 219-237.

  6. Object-oriented expert diagnostic systems: design principles, A. Narayanan and Y. Jin, in T. R. Addis and R. M. Muir (eds.),  Research and Development in Expert Systems VII, Cambridge University Press, 1990, pp. 306-317.

  7. The Chinese Room Argument: An exercise in computational philosophy of mind, in I. Mahalingam and B. Carr (eds.),  Logical  Foundations (Festschrift in honour of D. J. O'Connor), Macmillan, 1991, pp. 106-118.

  8. OBOES: An object-oriented expert system for hardware diagnosis,  A. Narayanan and P. Barbonis,  Colloquium on Intelligent Fault Diagnosis, IEE, Digest 1992/045, London, February 1992.

  9. A three-level finite state model for Arabic morphology,  A. Narayanan and L. Hashem,  Proceedings of the 3rd International Conference on Multilingual Computing, Durham University, 1992, 24pp.

  10. On abstract, finite-state morphology,  A. Narayanan and L. Hashem,  Proceedings of the Sixth Conference of the European Chapter of the Association for Computational Linguistics (EACL-93), 1993, pp. 297-304.

  11. More notes on ‘A clash of intuitions’, R. Al-Asady and  A. Narayanan,  Proceedings of the 13th International Joint Conference on Artificial Intelligence (IJCAI-93), 1993, pp. 682-687.

  12. A representational architecture for nonmonotonic inheritance structures, M. Boden and  A. Narayanan,  Proceedings of the International Conference on Artificial Neural Networks (ICANN-93) (Amsterdam), S. Gielen and B. Kappen (eds.), Springer Verlag, 1993, pp. 343-349.

  13. A connectionist model of nonmonotonic reasoning: Handling exceptions in inheritance hierarchies, M. Boden and  A. Narayanan, in  Connectionism in a Broad Perspective, L. Niklasson and M. Boden (eds.), Ellis Horwood, 1994, pp. 65-78.

  14. On nativist connectionism, in  Connectionism in a Broad Perspective, L. Niklasson and M. Boden (eds.), Ellis Horwood, 1994, pp. 99-108.

  15. Animating language,  A. Narayanan, L. Ford, D. Manuel, D. Tallis, M. Yazdani,  Workshop Notes,  Integrating Natural Language and Vision, 12th (American) National Conference on Artificial Intelligence (AAAI-94), Seattle, USA, 1994, 8 pp.

  16. Handling exceptions in automatically generated knowledge bases,  IEE Knowledge Discovery in Databases Colloquium Digest 1995/021(A), London: IEE Press, 1995, 3pp. (NR)

  17. Visualising quantum computing,  A. Narayanan, M. O'Donovan and M. Moore,  Proceedings of 14th Annual Eurographics Conference (UK Chapter), Volume 1, H. Jones, R. Raby and D. Vicars (Eds.), 1996, pp. 63-82.

  18. Quantum-inspired neural networks and consciousness, T. Menneer and  A. Narayanan,  Consciousness Research Abstracts (Tucson II), University of Arizona, 1996. (NR)

  19. Quantum-inspired genetic algorithms,  A. Narayanan and M. Moore, Proceedings of the IEEE 3rd International Conference on Evolutionary Computation (ICEC96), Nagoya, pp 61-66.

  20. The intentional stance and the imitation game, in  The Legacy of Alan Turing (Volume 1): Machines and Thought, P. Millican and A. Clarke (eds.), Oxford University Press, 1996, pp 63-80. (Refereed paper delivered at the Turing-90 Colloquium to honour the 40th anniversary of the appearance of Turing's paper, Sussex University, April 1990.)

  21. On changing one's mind: A connectionist account,  A. Narayanan and M. Boden,  Forms of Representation, D. Peterson (Ed.), Intellect, 1996, pp 101-117.

  22. ‘Quantum-inspired computing’ and ‘Connectionism’, in  Oxford Dictionary of Computing (3rd Edition), I. Pyle (Ed.), Oxford University Press, 1996.

  23. Biomolecular cognitive science, in  Two Sciences of Mind: Readings in Cognitive Science and Consciousness,  S. O Nuallain, P. Mc Kevitt and E. Mac Aogain (Eds.), John Benjamins Publishing, 1997, pp. 21-36.

  24. Structured walkthroughs for a virtual university,  A. Narayanan, G. Penny and S. Hudson,  Proceedings of 15th Annual Eurographics Conference (UK Chapter), 1997, pp. 65-74.

  25. An introductory tutorial on quantum computing.  Quantum Computing: Theory, Applications and Implications, Institution of Electrical Engineers (IEE) Digest No. 97/145, 3pp, 1997. (NR)

  26. DNA algorithms for computing shortest paths.  A. Narayanan and S. Zorbalas. Genetic Programming 1998: Proceedings of the IEEE/ACM/AAAI Third Annual Conference, J. R. Koza  et al. (Eds), 1998, pp. 718-724.

  27. Animating legal testimony.  A. Narayanan, G. Penny, S. Lochun and W. J. Milne.  Proceedings of the 6th National Conference/2nd European Conference on Law, Computers and AI, 1998.

  28. Quantum computing for beginners.  Proceedings of the IEEE/IEE World Congress on Evolutionary Computation (CEC99), Washington, DC, 1999, pp. 2231-2238.

  29. Quantum artificial neural networks vs classical artificial neural networks: Experiments in simulation. T. Menneer and  A. Narayanan,  Proceedings of the IEEE Fourth International Conference on Computational Intelligence and Neuroscience, Atlantic City, NJ, February 2000, pp. 757-759.

  30. A quantum algorithm for route finding.  A. Narayanan and J. Wallace,  Cybernetics and Systems 2000: Proceedings of the Fifteenth European Meeting on Cybernetics and Systems Research (EMCSR 2000), R. Trappl (Ed.), Volume 1,  Vienna, April 2000, pp 140-143.

  31. On synaptic plasticity: Modelling molecular kinases involved in transmitter release. D. Lundh and  A. Narayanan,  Artificial Neural Networks in Medicine and Biology, H. Malmgren, M. Borga and L. Niklasson (Eds.), Springer Verlag, 2000, pp 277-282.

  32. Evolving rules from neural networks trained on continuous data. E. C. Keedwell,  A. Narayanan and D. Savic,  Proceedings of IEEE 2000 World Congress on Evolutionary Computation (CEC2000), Volume 1, 2000, 639-645.

  33. From data mining to rule refining - A new tool for post data mining rule optimisation. E. Keedwell, F. Bessler,  A. Narayanan and D. Savic.  12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI2000), Vancouver, 2000, pp 82-85.

  34. Quantum sorting and route finding. J. Wallace and A. Narayanan.  Fifth International Conference on Computing Anticipatory Systems CASYS 2001, D. M. Dubois (Ed.), Liege, 2001, 2pp.

  35. Cloning consciousness: The future for Artificial Intelligence and Cognitive Science?  Towards a Science of Consciousness, Skovde, Sweden, 2001, Abstract 172.

  36. Modelling gene regulatory networks using artificial neural networks. E.C. Keedwell,  A. Narayanan and D. Savic,  Proceedings of the 2002 IEEE/INNS/ENNS International Joint Conference on Neural Networks (IJCNN'02), 2002, pp183-189.

  37. Recognising Prosite patterns with cellular automata. K. Laurio, F. Linaker and  A. Narayanan,  Proceedings of the Sixth Joint Conference on Information Sciences, Caulfield, Chen, Cheng, Duro, Honavar, Kerre, Lu, Romay, Shih, Ventura, Wang, Yang (eds.), 2002, 1174-1179.

  38. All there is to the mind is to have the right genes, or, consciousness as a form of genetic engineering.  Artificial Intelligence and Cognitive Science: Proceedings of the 13th Irish Conference AICS 2002, M. O'Neill, R. F. E. Sutcliffe, C. Ryan, M. Eaton and N. J. Griffiths (Eds), Springer Verlag Lecture Notes in Artificial Intelligence (LNAI 2464), 2002, pp 78-86.

  39. Genetic algorithms for gene expression analysis. E. C. Keedwell and  A. Narayanan.  Applications of Evolutionary Computation: Proceedings of the 1st European Workshop on Evolutionary Bioinformatics, G. Raidl  et al., Springer Verlag LNCS 2611, 2003, 76-86.

  40. Artificial intelligence and machine learning techniques for Bioinformatics: Tutorial.  A. Narayanan, E. Keedwell and B. Olsson. ISMB 2003 Tutorial Notes, Tutorial presented at ISMB03, Brisbane, July 2003.

  41. Analyzing gene expression data for childhood medulloblastoma survival with artificial neural networks.  A. Narayanan, E. Nana and E.C. Keedwell,  Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, October 2004, 9-16.

  42. Artificial neural networks for reducing the dimensionality of gene expression data.  A. Narayanan, Alan Cheung, Jonas Gamalielsson, Ed Keedwell and Christophe Vercellone. In Bioinformatics Using Computational Intelligence Paradigms, U. Seiffert, L.C. Jain and P. Schweizer (Eds.), Studies in Fuzziness and Soft Computing Vol. 176, Springer Verlag, 2005, 191-216.

  43. Neural networks and temporal gene expression data. A. Krishna, A. Narayanan and E.C. Keeedwell. Applications of Evolutionary Computing (EvoBio05), Special Session on Bioinformatics, F. Lothlauf et al. (Eds), Springer Verlag LNCS 3449, 2005, 64-73.

  44. Reverse engineering gene networks with artificial neural networks. A. Krishna,  A. Narayanan and E. C. Keedwell. Proceedings of the 7th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA05), Special Session on Bioinformatics, B. Ribeiro, R. Albrecht, A. Dobnikar, D. W. Pearson and N.C. Steele (Eds.).  325-328, Springer Computer Science, March 2005.

  45. Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets. Juliusdottir, T., Keedwell, E. Corne, D. and Narayanan, A. Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB '05), 1-8. 2005. ISBN: 0-7803-9387-2

  46. Gene expression classification using multi-objective ensembles. E. C. Keedwell and A. Narayanan. Adaptive and Emergent Behaviour and Complex Systems - Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB, 2009, pp. 15-20.

  47. Unsupervised artificial neural nets for modelling the effects of climate change on New Zealand grape wines. Shanmuganathan, S.,Sallis, P., and Narayanan, A. In B. Anderssen et al. (eds) 18th IMACS World Congress - MODSIM09 International Congress on Modelling and Simulation, 13-17 July 2009, Cairns, Australia. ISBN: 978-0-9758400-7-8. pp. 803-809.

  48. Statistical data analysis incorporating web text mining to establish correlations between grape wine taster comments and wine ratings. S. Shanmuganathan, P. Sallis and A. Narayanan. Proceeding of the IEEE 6th International Conference on Information Technology in Asia (CITA09), 6 - 9th July 2009, Sarawak, Malaysia. ISBN 983-92576-6-8, IEEE computer society, 258-262.

  49. Teaching Non-Traditional Applications to Engineering Students. Sauerbier, G., Narayanan, A., Gruenwald, N., Klymchuk, S. and Zverkova, T. In Araujo, A., Fernandes, A., Azevedo, A., Rodrigues, J.F. (Eds) Proceedings of the International Conference on Educational Interface between Mathematics and Industry (ICMI-20 Study), Lisbon, Portugal, pp. 437-447, 2010. ISBN-13: 978-1-933223-64-2

  50. Teaching Unusual Applications in Engineering Mathematics: Students’ Attitudes. Gruenwald, N., Sauerbier, G., Narayanan, A., Klymchuk, S. and Zverkova, T. In Schott, D. (Ed) Proceedings of the 15th conference of the Mathematics Working Group (MWG) of the European Society for Engineering Education (SEFI), Wismar, Germany, 2010. E-format, ISBN: 978-3-939159-97-1

  51. Doctors using patient feedback to establish professional learning goals:  Results from a communication skill development program. L Baker, M. Greco and A. Narayanan. In Wayne Pease, Malcolm Cooper and Raj Garurajan (Eds.) Biomedical Knowledge Management: Infrastructures and Processes for eHealth Systems, IGI Global, 2010. Chapter 22. 303-314.

  52. Micro-climate variations related to vineyard crop quality. P. Sallis, S. Shanmuganathan and A. Narayanan. (2010)  Proceedings of WAC2010 (World Automation Congress) on Soft Computing for Industry ISSCI 2010, Kobe, Japan, September 19-22, 7pp. Also in  AutoSoft: The Journal of Intelligent Automation and Soft Computing, 1-7, 2010. IEEE Press.

  53. Data mining techniques for modelling seasonal climate effects on grapevine yield and wine quality.  S. Shanmuganathan, P. Sallis and A. Narayanan (2010). Proceedings of the IEEE Second International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), Liverpool, UK, 28 – 30 July 2010, 84-89.

  54. Data mining techniques for modelling the influence of daily extreme weather conditions on grapevine, wine quality and perennial crop yield. S. Shanmuganathan, P. Sallis and A. Narayanan (2010). Proceedings of the IEEE Second International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), Liverpool, UK, 28 – 30 July 2010, 90-95.

  55. Modelling the seasonal climate effects on grapevine yield at different spatial and unconventional temporal scales. S. Shanmuganathan, P. Sallis and A. Narayanan.  Proceedings of International Congress on Environmental Modelling and Software (iEMSs), David A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.), 5-8 July, Ottawa, Canada, 2010, 10pp. http://www.iemss.org/iemss2010/index.php, Session 15.

  56. Modelling the effects of daily extreme weather on grapevine and wine quality. S. Shanmuganathan, P. Sallis and A. Narayanan (2010). Proceedings of International Congress on Environmental Modelling and Software (iEMSs), David A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.), 5-8 July, Ottawa, Canada, 2010, pp 2327-2335. Session 28.  http://www.iemss.org/iemss2010/index.php, Session 28.

  57. Humoral mediated clustering. W. Ahmad and A. Narayanan. Proceedings of the IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2010), Liverpool, UK, September, 2010, pp 1471-1481.

  58. Feature weighting for efficient clustering. W. Ahmad and A. Narayanan. 2010. Proceedings of the IEEE 6th International Conference on Advanced Information Management and Service (IMS), 236-242. ISBN: 978-1-4244-8599-4. INSPEC Accession Number: 11824130.

  59. Towards an automated digital data forensic model with specific reference to investigation processes. J. Scholtz and A. Narayanan. Proceedings of the 8th Australian Digital Forensics Conference, Perth, Australia, pp 142-155.  Edith Cowan University, Perth, Australia, December 2010.

  60. Gene expression rule discovery with a multi-objective neural-genetic hybrid. E.C. Keedwell and A. Narayanan. 2010. Proceedings of BIBM (IEEE International Conference on Bioinformatics and Biomedicine), Hong Kong, December 2010, 649-657.

  61. Outlier detection using humoral-mediated clustering (HAIS). W. Ahmad and A. Narayanan. 2010. Proceedings of NaBIC2010 (IEEE World Congress on Nature and Biologically Inspired Computing). Kitakyushu, December 2010, pp 45-52.

  62. Humoral artificial immune system (HAIS) for supervised learning. W. Ahmad and A. Narayanan. 2010. Proceedings of NaBIC2010 (IEEE World Congress on Nature and Biologically Inspired Computing). Kitakyushu, December 2010, 37-44.

  63. Mathematical modelling of infectious disease with biomathematics: Implications for teaching and research. Gruenwald, N., Sauerbier, G., Narayanan, A., Klymchuk, S. and Zverkova, T.  In Kaiser, G. (Ed) Proceedings of the 14th International Conference on the Teaching of Mathematical Modelling and Applications (ICTMA-14), Hamburg, Germany, 2011. (In print)

  64. A multi-agent (MA) cellular automata (CA) framework for grapevine growth and crop simulation. Shanmuganathan, S., Narayanan, A., Robinson, N., IEEE Proceedings of the 3rd International Conference on Machine Learning and Computing (ICMLC 2011), Singapore, February 26-28, 2011. http://www.icmlc.org/  IEEE Catalog Number: CFP1127J-PRT ISBN: 978-1-4244-9252-7. Also appeared in International Journal of Machine Learning and Computing.

  65. Data mining and χ2 test based hybrid approach to modelling climate effects on grape crop in varieties of Kumeu, New Zealand.  Shanmuganathan, S., Sallis, P., Narayanan, A. IEEE Proceedings of the 3rd International Conference on Machine Learning and Computing (ICMLC 2011), Singapore, February 26-28, 2011, pp 355-359. http://www.icmlc.org/   IEEE Catalog Number: CFP1127J-PRT ISBN: 978-1-4244-9252-7.

  66. Quantum jump clustering. W. Ahmad and A. Narayanan. 2011. Editors: Ding Y, Wang H, Xiong N, Hao K, Wang L. Proceedings of IEEE 7th International Conference on Natural Computation (ICNC 2011). 3: 1352-1357. Jul 2011.

  67. Population-based artificial immune system clustering algorithm. W. Ahmad and A. Narayanan. 2011. In Pietro Liò, Giuseppe Nicosia, Thomas Stibor (Eds.): Artificial Immune Systems, 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings. Lecture Notes in Computer Science 6825 Springer 2011, pp. 348-360.

  68. Principles and methods of artificial immune system vaccination of learning systems.  W. Ahmad and A. Narayanan. 2011. In Pietro Liò, Giuseppe Nicosia, Thomas Stibor (Eds.): Artificial Immune Systems, 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings. Lecture Notes in Computer Science 6825 Springer 2011, pp. 268-281.

  69. Modelling the seasonal climate variability and its effects on vintage wines from Marlborough, NZ. Shanmuganathan, S., Sallis, P., Narayanan, A. Proceedings of the 8th International Conference on Fuzzy Systems and Knowledge Discovery, Shanghai, China, 26-28 Jul 2011. Vol 4, pp 2128-2133. Proceedings Editors: Ding Y, Li Y, Fan Z, Li S, Wang L. IEEE Conference Record Number for FSKD’11: 18083. ISBN 978-1-61284-178-6, IEEE catalog no. CFPIIFSK-PRT.

  70. A cellular automaton framework for within-field vineyard variance and grape production simulation. S. Shanmuganathan, A. Narayanan and N. Robinson. The 7th International Conference on Natural Computation, Shanghai, China, 26 Jul 2011 - 28 Jul 2011. Vol 3, pp 1430-1435.  Proceedings Editors: Ding Y, Wang H, Xiong N, Hao K, Wang L. IEEE Conference Record Number for ICNC’11.ISBN 978-1-4244-9951-9, catalog no. CFP11CNC-PRT p1456-1461.

  71. Analysing the climate variability in the wine regions of New Zealand and Chile: A GIS perspective. S. Shanmuganathan, A. Narayanan and A. Perez Kurokia. International Conference on Modelling and Simulation (MODSIM 2011), Perth, Australia, 12 Dec 2011 – 16 Dec 2011, pp 1146-1152.

  72. Establishing the correlation between soil and crop production to optimize wine quality. A Perez-Kuroki, S. Shanmuganathan, F. Scannavino Jr, P. Sallis and A. Narayanan. International Conference on Modelling and Simulation (MODSIM 2011), Perth, Australia, 12 Dec 2011 – 16 Dec 2011, pp 1132-1138.

  73. Real Time Replanning based on A* for Collision Avoidance in Multi-Robot Systems. F. Liu and A.  Narayanan. Proceeding of URAI 2011 (8th International Conference on Ubiquitous Robots and Ambient Intelligence), Korea, November 2011, pp 473-479. (IEEE Conference Record 18962)

  74. Organisational preparedness for hosted virtual desktops in the context of digital forensics. N. Jawale and A. Narayanan. 2011. Proceedings of the 9th Australian Digital Forensics Conference, Edith Cowan University, Perth Western Australia, 5th -7th December, pp 66-75.

  75. Malicious software detection using multiple sequence alignment and data mining. Chen, Y., Narayanan, A., Pang, S. and Tao, B. Proceedings of the 26th IEEE International Conference on Advanced Information Networking and Applications (AINA 2012). Fukuoka, Japan, March 2012,  pp 8-14.

  76. Multiple sequence alignment and artificial neural networks for malicious software detection. Chen, Y., Narayanan, A., Pang, S. and Tao, B. Proceedings of 8th IEEE Conference on Natural Computation (ICNC’12), Chonqing, China, May, 2012, pp. 261-265. DOI: 10.1109/ICNC.2012.6234576

  77. The Use of Cellular Automata for Modelling (SIR)N Diseases with Migratory Reinfection. O. Apenteng, A. Narayanan and S. Klymchuk. In F.Yama (Ed.), International Conference on Computer Research and Development, ICCRD 2013 (pp. 59-63). New York, USA: ASME Press. 2013. doi:10.1115/1.860182_ch10

  78. The effects of different representations on malware motif identification. A. Narayanan, Y. Chen, S. Pang and B. Tao. Proceedings of 2012 International Conference on Computational Intelligence and Security (ICIS 2012). Guangzhou, China, November 2012, pp. 86-90. DOI: 10.1109/CIS.2012.27.

  79. Modelling the climate change effects on Malaysia's oil palm yield. S. Shanmuganathan and A. Narayanan. 2012. IEEE Symposium on E-Learning, E-Management and E-Services (IS3e), pp. 1-6. DOI: 10.1109/IS3e.2012.6414948

  80. Climate change and grape wine quality: A GIS approach to analysing New Zealand wine regions. S Shanmuganathan, A. Narayanan and P. Sallis. 2012. In N. Chhetri (ed.), Human and Social Dimensions of Climate Change, Chapter 11, InTech. ISBN 978-953-51-0847-4. Available from: http://www.intechopen.com/books/human-and-social-dimensions-of-climate-change/climate-change-and-grape-wine-quality-a-gis-approach-to-analysing-new-zealand-wine-regions.

  81. A human-inspired collision avoidance method for multi-robot and mobile autonomous robots. R. Liu and A. Narayanan. 16th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2013), Dunedin, New Zealand, 01 Dec 2013 - 06 Dec 2013. Proceedings Editors: Boella G, Elkind E, Savarimuthu BTR, Dignum F, Purvis MK. PRIMA 2013: Principles and Practice of Multi-Agent Systems. Springer-Verlag, Berlin Heidelberg. 8291: 181-196. 2013. http://link.springer.com/content/pdf/10.1007%2F978-3-642-44927-7_13.pdf

  82. A Hybrid Approach to Modelling the Climate Change Effects on Malaysia’s Oil Palm Yield at the Regional Scale. S. Shanmuganathan, A. Narayanan, M. Mohamed, R. Ibrahim and H. Khalid. In Herawan, T., Ghazali, R. and Dereis, M.M. (Eds), Recent Advances on Soft Computing and Data Mining. Proceedings of the First International Conference on Soft Computing and Data Mining (SCDM-2014). Universiti Tun Hussein Onn Malaysia, Johor, Malaysia (June 16-18 2014). Springer International, 2014, pp 335-345. DOI10.1007/978-3-319-07692-8_32.

  83. An evolutionary computational approach to phase and synchronization in biological circuits. A. Narayanan and E. Keedwell. Proceedings of the IEEE 2014 10th International Conference on Natural Computation (ICNC 2014), Xiamen, China, August 2014, pp. 421-426. 978-1-4799-5151-2/14.

  84. Solving capacitated vehicle routing problem using Intelligent Water Drops algorithm. A. Wedyan and A. Narayanan. Proceedings of the IEEE 2014 10th International Conference on Natural Computation (ICNC 2014), Xiamen, China, August 2014, pp. 471-476. 978-1-4799-5151-2/14.

  85. Further experiments in biocomputational structural analysis of malware. V. Naidu and A. Narayanan.  Proceedings of the IEEE 2014 10th International Conference on Natural Computation (ICNC 2014), Xiamen, China, August 2014, pp. 610-615. 978-1-4799-5151-2/14.

  86. Intelligent Collision Avoidance between Autonomous Agents using Adaptive Local Views. R. Liu and A. Narayanan. Principles and Practice of Multi-Agent Systems: 17th international Conference (PRIMA 2014). H.K.Dam, J. Pitt, Y.Xu, G. Governatori, T. Ito (Eds.), Gold Coast, Queensland, December 2014, Lecture Notes in Computer Science (LCNS) 8861, Springer, 2014. 190-205. ISSN 0302-9743. e-ISSN 1611-3349. ISBN 978-3-319-13190-0. e-ISBN 978-3-319-13191-7. DOI 10.1007/978-3-319-13191-7.

  87. The role of hypermutation and affinity maturation in AIS approaches to clustering. W. Ahmad and A. Narayanan, in Muhammad Usman (Ed.), Improving Knowledge Discovery through the Integration of Data Mining Techniques, Chapter 7, IGI Global (Advances in Data Mining and Database Management), 2015. DOI: 10.4018/978-1-4666-8513-0.ch007

  88. Artificial immune system: An effective way to reduce model overfitting. W. Ahmad and A. Narayanan. 2015. Proceedings of the 7th International Conference on Computational Collective Intelligence Technologies and Applications, September 21-23 2015, Madrid. Computational Collective Intelligence, Núñez, M., Nguyen, N.T., Camacho, D., Trawiński, B. (Eds.). Springer Lecture Notes in Artificial Intelligence (LNAI 9329), pp. 316-327. 2015. DOI: 10.1007/978-3-319-24069-5_30

  89. Hierarchical data classification using deep neural networks. S. S. Tirumala and A. Narayanan. Proceedings of the 22nd International Conference on Neural Information Processing (ICONIP 2015), Arik, S., Huang, T., Lai, W.K., Liu, Q. (Eds.), Spriner. 9489: 492-500. 2015. DOI 10.1007/978-3-319-26555-1.

  90. Temporal data analysis and mining methods for modelling the climate change effects on Malaysia’s oil palm yield at different regional scales. Shanmuganathan S, Narayanan A, Medagoda N. In Handbook of Research on Climate Change Impact on Health and Environmental Sustainability. Editor: Dinda S. 2015.

  91. Exploring the Role of Structural Similarity in Securing Smart Metering Infrastructure. A.B.Aminu, W. Liu, Q. Bai and A. Narayanan. 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS 2015), Sydney Australia: IEEE DSDIS Proceedings, pp.343-349. DOI: 10.1109/DSDIS.2015.95

  92. Revealing the Role of Topological Transitivity in Efficient Trust and Reputation System in Smart Metering Infrastructure . A.B.Aminu, W. Liu, Q. Bai and A. Narayanan.  In 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS 2015), Sydney Australia: IEEE DSDIS Proceedings, pp.337-342.

  93. Classification and diagnostic Prediction of Prostate Cancer using Gene Expression and Artificial Neural Networks. S. S. Tirumala and A. Narayanan. To appear in Proceedings of IEEE World Congress on Computational Intelligence (WCCI), Vancouver, Canada, July 2016.

  94. A String-Based Approach for Detecting Viral Polymorphic Malware Variants. V. Naidu and A. Narayanan. To appear in Proceedings of IEEE World Congress on Computational Intelligence (WCCI), Vancouver, Canada, July 2016.

C. Books authored and edited

  1. Artificial Intelligence: Human Effects, M. Yazdani and  A. Narayanan (eds.), Ellis Horwood, 1984, 318pp.

  2. Introduction to LISP, A. Narayanan and N. E. Sharkey, Ellis Horwood, 1985, 260pp.

  3. On Being a Machine (Volume 1): Formal Aspects of Artificial Intelligence, A. Narayanan, Ellis Horwood, 1988, 200pp.

  4. On Being a Machine (Volume 2): Philosophy of Artificial Intelligence, A. Narayanan, Ellis Horwood, 1990, 247pp.

  5. Law, Computer Science, and Artificial Intelligence, A. Narayanan and M. Bennun (Eds.), Ablex, 1991, 266pp.  Reprinted as paperback in 1998.

  6. Proceedings of the Fifth National Conference/First European Conference on Law, Computers and Artificial Intelligence, I. M. Carr and A. Narayanan (Eds.), Exeter University Centre for Legal Interdisciplinary Development, 1996, 225pp.

  7. Biocomputing and Emergent Computation, D. Lundh, B. Olsson and A. Narayanan (Eds.), World Scientific, 1997. 299pp.

  8. Intelligent Bioinformatics, E.C. Keedwell and A. Narayanan, Wiley, 2005, 280pp.  (2nd print)


Last updated: 24-Nov-2016 8.25am

The information on this page was correct at time of publication. For a comprehensive overview of AUT qualifications, please refer to the Academic Calendar.