Breadcrumbs

Dr Michael Mayo

Michael Mayo

Senior Lecturer (Computer Science)

Qualifications: BA(Hons) Otago PhD Cant

Papers Taught

Research Supervised

Ph.D.

  • Gunasinghe, Hansi (main supervisor; in progress) Towards solving the unseen domain problem in machine learning-based glaucoma detection using retinal fundus images
  • 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 

Masters

  • Whitten, Jesse (main supervisor; in progress) Deep learning-based tools and techniques for annotating and clinical analysis of cataract surgery videos
  • 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

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

Recent Publications

  • Breeze, F., Hossain, R., Mayo, M., & McKelvie, J. (2022). Predicting ophthalmic clinic non-attendance using machine learning. Clinical and Experimental Ophthalmology, 49(8), 804. Retrieved from http://gateway.webofknowledge.com/

  • Whitten, J., Mayo, M., & McKelvie, J. (2022). Analysis of phacoemulsification videos using machine learning. Clinical And Experimental Ophthalmology, 49(8), 878. Retrieved from http://gateway.webofknowledge.com/

  • Gunasinghe, H. N., McKelvie, J., Koay, A., & Mayo, M. (2022). Automated detection of glaucoma from retinal fundus images using a variety of fundus cameras. Clinical and Experimental Ophthalmology, 49(8), 911. Retrieved from http://gateway.webofknowledge.com/

  • Rodrigues, M., Mayo, M., & Patros, P. (2022). Evaluation of deep learning techniques on a novel hierarchical surgical tool dataset. In G. Long, X. Yu, & S. Wang (Eds.), Proc 34th Australasian Joint Conference on Advances in Artificial Intelligence (AI 2021) LNCS 13151 (pp. 169-180). Sydney, Australia: Springer. doi:10.1007/978-3-030-97546-3_14

Find more research publications by Michael Mayo

Keywords

Data; Data mining; Health; Imaging; Machine Learning


Contact Details

Email: [email protected]
Room: G.2.24
Phone: +64 7 838 4403