- Artificial Intelligence, Datamining, Optimisation, Modelling, Simulation
Professor Aickelin has worked for more than twenty years in the fields of Artificial Intelligence, Optimisation and Datamining. He is particularly interested in the 'modelling' stages of problems with a focus on 'robustness'. During this time he has authored over 200 papers in leading international journals and conferences (Google citations 8000, H-index 48) and participated in over 100 international Conference Programme Committees. His YouTube videos on Datamining have been watched by more than 400,000 people. He has been an associate editor of the leading international journal in his field for ten years (IEEE Transactions on Evolutionary Computation). Recently Computerphile has produced a number of clips about his work: Nuggets of Data Gold Illegal Immigration & the Known Unknowns How does GCHQ classify security? What is Machine Learning? Anti-Learning – So bad it’s good Why missing data is the most interesting
- Fattah P, Aickelin U, Wagner C. Measuring behavioural change of players in public goods game. Studies in Computational Intelligence. Springer. 2018, Vol. 751. DOI: 10.1007/978-3-319-69266-1_12
- Dent I, Craig T, Aickelin U, Rodden T. A Method for Evaluating Options for Motif Detection in Electricity Meter Data. Journal of Data Science. 2017.
- Fu X, Ch'ng E, Aickelin U, See S. CRNN: A Joint Neural Network for Redundancy Detection. 2017 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP). IEEE. 2017.
- Jiang X, Bai R, Landa-Silva D, Aickelin U. Fuzzy C-Means-based Scenario Bundling for Stochastic Service Network Design. 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), Honolulu, Hawaii, USA. 2017.
- Fattah P, Aickelin U, Wagner C. Measuring Behavioural Change of Players in Public Goods Game. . Springer. 2017, Vol. tba.
- Kabir S, Wagner C, Havens TC, Anderson DT, Aickelin U. Novel similarity measure for interval-valued data based on overlapping ratio. IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers. 2017. DOI: 10.1109/FUZZ-IEEE.2017.8015623
- Siuly S, Huang Z, Aickelin U, Zhou R, Wang H, Zhang Y, Klimenko SV. Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2017, Vol. 10594 LNCS.
- Aickelin U. Robust Datamining. 4th Asia Pacific Conference on Advanced Research (APCAR- MAR 2017), Melbourne, Australia. 2017.
- Ruan C, Wang Y, Zhang Y, Ma J, Chen H, Aickelin U, Zhu S, Zhang T. THCluster: Herb Supplements Categorization for Precision Traditional Chinese Medicine. 2017 IEEE International Conference on Bioinformatics and Biomedicine, Kansas City, MO, USA. 2017.
- Aickelin U, Reps JM, Siebers P-O, Li P. Using Simulation to Incorporate Dynamic Criteria into Multiple Criteria Decision Making. Journal of the Operational Research Society. 2017, Vol. tba.
- Navarro J, Wagner C, Aickelin U, Green L, Ashford R. Exploring Differences in Interpretation of Words Essential in Medical Expert-Patient Communication. 2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE). IEEE. 2016.
- Navarro J, Wagner C, Aickelin U, Green L, Ashford R. Measuring Agreement on Linguistic Expressions in Medical Treatment Scenarios. IEEE Symposium Series on Computational Intelligence (IEEE SSCI). IEEE. 2016.
- Fattah P, Aickelin U, Wagner C. Measuring Player’s Behaviour Change over Time in Public Goods Game. SAI Intelligent Systems Conference 2016 London. 2016.
- Miller S, Wagner C, Aickelin U, Garibaldi JM. Modelling cyber-security experts' decision making processes using aggregation operators. COMPUTERS & SECURITY. Elsevier Advanced Technology. 2016, Vol. 62. DOI: 10.1016/j.cose.2016.08.001
- Fattah P, Aickelin U, Wagner C. Optimising Rule-Based Classification in Temporal Data. ZANCO Journal of Pure and Applied Sciences. 2016, Vol. 28.
View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile