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

Research Interests

Artificial Intelligence (metaheuristics, machine learning, etc) and it applications in health/medicine.

Teaching Commitments

Recent Publications

  • Mayo, M., & Frank, E. (2020). Improving Naive Bayes for Regression with Optimised Artificial Surrogate Data. Applied Artificial Intelligence, 34(6), 484--514. doi:10.1080/08839514.2020.1726615 Open Access version:

  • Yogarajan, V., Pfahringer, B., & Mayo, M. (2020). A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric?. Applied Artificial Intelligence, 34(3), 251-269. doi:10.1080/08839514.2020.1718343

  • Hébert-Losier, K., Hanzlíková, I., Zheng, C., Streeter, L., & Mayo, M. (2020). The 'DEEP' landing error scoring system. Applied Sciences (Switzerland), 10(3). doi:10.3390/app10030892

  • Mayo, M., & Daoud, M. (2019). Data normalisation using differential evolution and aggregated logistic functions. In Proc 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019) (pp. 920-927). Wellington, NZ. doi:10.1109/CEC.2019.8790251

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