Breadcrumbs

Dr Michael Mayo

Senior Lecturer (Computer Science)

Qualifications: BA(Hons) Otago PhD Cant

Contact Details

Email: mmayo@waikato.ac.nz
Room: G.2.24
Phone: +64 7 838 4403
Extension: 4403
Fax: +64 7 858 5095

Research Interests

artificial intelligence (mainly evolutionary algorithms and machine learning), and applications in health and energy optimisation

Teaching Commitments

Recent Publications

  • Goltz, N., & Mayo, M. (2017). Enhancing regulatory compliance by using artificial intelligence text mining to identify penalty clauses in legislation. In MIREL 2017 - Workshop on 'Mining and REasoning with Legal texts', held in conjunction with the 16th International Conference on Artificial Intelligence and Law. Conference held at King’s College, London, UK. Open Access version: https://hdl.handle.net/10289/11940

  • Mayo, M., & Goltz, N. (2017). Constructing document vectors using kernel density estimates. In V. Torra, Y. Narukawa, A. Honda, & S. Inoue (Eds.), Modeling Decisions for Artificial Intelligence. MDAI 2017 (pp. 183-194). Cham: Springer. doi:10.1007/978-3-319-67422-3_16

  • Wilson, B., Wakes, S., & Mayo, M. (2017). Surrogate modeling a computational fluid dynamics-based wind turbine wake simulation using machine learning. In Proc 2017 IEEE Symposium Series on Computational Intelligence (SSCI 2017) (pp. 1-8). Honolulu, Hawaii: IEEE. doi:10.1109/SSCI.2017.8280844 Open Access version: https://hdl.handle.net/10289/11785

  • Mayo, M., & Daoud, M. (2017). Aesthetic local search of wind farm layouts. Information, 8(2), 39. doi:10.3390/info8020039 Open Access version: https://hdl.handle.net/10289/11017

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