Michelle Dunbar

Michelle Dunbar


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.


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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