People

Michelle Dunbar

Michelle Dunbar

Background

Michelle recently completed her PhD in Applied Mathematics at the University of New South Wales. Michelle has experience in applying mathematical optimisation techniques to real-world airline networks; to assist in the integration of key operational decisions and in providing robust solutions under operational uncertainty. She also has experience in applying non-linear optimisation tools to a variety of medical datasets to allow for improved disease detection and diagnosis; one of these tools has subsequently been taken up by a health care company.

Research areas and expertise

Operations Research and Discrete Optimisation: Linear and Integer Programming

  • Airline scheduling, rail scheduling and logistics.
  • Optimisation under uncertainty and minimisation of delay propagation between connecting resources.
  • Integrated infrastructure planning.

Non-linear Optimisation: Quadratic Programming

  • Non-linear optimisation models for Support Vector Machine (SVM) classification and feature selection.
  • Application of SVMs to medical datasets to allow for improved disease detection and diagnosis.

Academic Qualifications

  • Ph.D.; (Applied Mathematics), 2012, University of New South Wales, Australia.
  • Bachelor of Advanced Science (Applied Mathematics), Hons. (Class I), 2008, University of New South Wales, Australia.

Publications

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Professional Associations

  • Australian Mathematical Society (AustMS). Australian and New Zealand Industrial and Applied Mathematics (ANZIAM).
  • INFROMS, The OR Society
Last reviewed: 8 March, 2016