Professor Geoff Holmes
Pro Vice Chancellor- Health, Engineering, Computing, and Science
Qualifications: BSc(Hons) PhD S'ton
Phone: +64 7 838 4405
I received my degrees in Mathematics from the University of Southampton, England. My PhD involved the development of software packages to assist Mathematicians in solving Einstein's field equations in General Relativity. This was how I got started in Computer Science. After graduating I became a Research Assistant at the Electrical Engineering Department of Cambridge University, England where I was a member of large team working on a speech understanding system. I took up a position as Lecturer in Computer Science in 1987. In 1993 I was appointed Senior Lecturer.
My research interests are fairly broad. I have always held an interest in Computer Speech and have supervised several projects at Waikato on that topic, in particular, speech recognition and speech compression. I currently have two PhD students working on speech compression. I am part of the Department's Machine Learning group where I concentrate my efforts on the application of Machine Learning to agricultural domains. Through my interests in Machine Learning I have recently become very interested in the concept of knowledge discovery in databases.
Sharifi, N., Gong, Z., Holmes, G., & Chen, Y. (2021). A feasibility study of in vivo control and tracking of microrobot using taxicab geometry for direct drug targeting. IEEE Transactions on NanoBioscience, 20(2), 235-245. doi:10.1109/TNB.2021.3062006
Barker, R. D., Barker, S. L. L., Cracknell, M. J., Stock, E. D., & Holmes, G. (2021). Quantitative mineral mapping of drill core surfaces II: long-wave infrared mineral characterization using μXRF and machine learning. Economic Geology, 116(4), 821-836. doi:10.5382/econgeo.4804 Open Access version: https://hdl.handle.net/10289/14118
Mitchell, R., Frank, E., & Holmes, G. (2021). An empirical study of moment estimators for quantile approximation. ACM Transactions on Database Systems, 46(1), 1-21. doi:10.1145/3442337
Read, J., Pfahringer, B., Holmes, G., & Frank, E. (2021). Classifier chains: A review and perspectives. Journal of Artificial Intelligence Research, 70, 683-718. doi:10.1613/jair.1.12376
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