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Personal profile

Biography

Simon completed his PhD in 2019, focusing on generating test cases that effectively stress-test optimisation algorithms and determine their relative strengths and weaknesses. He has a particular interest in optimisation algorithm development, empirical performance analysis, and automated algorithm configuration using machine learning methods.

Simon also has extensive experience applying optimisation and data analysis techniques to real-world problems, including optimisation for road and rail logistics, development of automated tools to analyse operational data from wind farms; and short-term energy production forecasting.

Education/Academic qualification

Mathematics, Doctorate of Philosophy - Science, University of Melbourne

9 Mar 201512 Dec 2019

Award Date: 17 Jan 2020

Network

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