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, deep/machine learning, heuristic search algorithms, and ways to apply and implement them in various other disciplines such health/medicine and edge computing

Research Supervised


  • Gunasinghe, Hansi (main supervisor; in progress) TBA
  • Rodrigues, Mark (main supervisor; in progress) Neuro-symbolic artificial intelligence for surgical tool management
  • Lu, Lisa (main supervisor; in progress) TBA
  • Zhang, Zijang (cosupervisor; in progress) TBA
  • Zheng, Chen (cosupervisor; in progress) Detecting non-obvious neuroimaging abnormalities using deep learning-based generative models
  • Hirsz, Malgorzata (cosupervisor; in progress) Epidemiological evidence that can help to improve timely diagnosis of colorectal cancer in New Zealand
  • Madurapperumage, Anuradha (cosupervisor; in progress) Chronological risk estimation and prediction in health informatics through a knowledge-based system: an application to complications of diabetes mellitus
  • Wang, Hongyu (cosupervisor; in progress) User friendly deep learning
  • Daoud, Maisa (main supervisor; 2020) Autoencoder-based techniques for improved classification in settings with high dimensional and small sized data
  • Zhang, Edmond Yiwen (main supervisor; 2012) Improving bags-of-words model for object categorization 


  • Whitten, Jesse (main supervisor; in progress) TBA
  • Gong, Hao (main supervisor; in progress) Surgical instruments classification using bag of visual words model
  • Bradley, Neil (main supervisor; 2020) Hokohoko: a comprehensive framework for evaluating artificial intelligence-based and statistical techniques for foreign exchange speculation
  • Wang, Hongyu (main supervisor; 2019) Metaheuristic optimisation of insulin infusion protocols using historical data with validation using a patient simulator
  • Zheng, Chen (main supervisor; 2016) Surrogate assisted evolutionary algorithms for wind farm layout optimisation problem

Teaching Commitments

Recent Publications

  • Gunasinghe, H., McKelvie, J., Koay, A., & Mayo, M. (2021). Comparison of pretrained feature extractors for glaucoma detection. In Proc 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) (pp. 390-394). Nice, France: IEEE. doi:10.1109/isbi48211.2021.9434082

  • Wakes, S. J., Bauer, B. O., & Mayo, M. (2021). A preliminary assessment of machine learning algorithms for predicting CFD-simulated wind flow patterns over idealised foredunes. Journal of the Royal Society of New Zealand, 51(2), 290-306. doi:10.1080/03036758.2020.1868541

  • Wang, H., Chepulis, L., Paul, R. G., & Mayo, M. (2021). Metaheuristic optimization of insulin infusion protocols using historical data with validation using a patient simulator. Vietnam Journal of Computer Science, 8(2), 263-290. doi:10.1142/s2196888821500111 Open Access version:

  • Mayo, M., & Koutny, T. (2020). Neural multi-class classification approach to blood glucose level forecasting with prediction uncertainty visualisation. In K. Bach, R. Bunescu, C. Marling, & N. Wiratunga (Eds.), Proc 5th International Workshop on Knowledge Discovery in Healthcare Data (KDH 2020) Vol. 2675 (pp. 80-84). Santiago de Compostela, Spain & Virtually: CEUR Workshop Proceedings. Retrieved from

Find more research publications by Michael Mayo