Dr Michael Mayo

Senior Lecturer (Computer Science)

Qualifications: BA(Hons) Otago PhD Cant

Contact Details

Room: G.2.24
Phone: +64 7 838 4403
Extension: 4403
Fax: +64 7 858 5095

Research Interests

Artificial intelligence and health. I have several open projects available for good postgraduate students in this area so let me know if you are interested.

Teaching Commitments

Recent Publications

  • Doaud, M., & Mayo, M. (2017). Using swarm optimization to enhance autoencoder’s images. In V. Torra, Y. Narukawa, A. Honda, & S. Inoue (Eds.), USB Proc 14th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2017) (pp. 118-131). Kitakyushu, Japan.

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

  • 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

  • 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:

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