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Peter Whigham imageBSc(Hons)(ANU), PhD(NSW)

Room 3.43, Otago Business School
Tel +64 3 479 7391

Background and interests

Professor Peter A Whigham is Director of the Spatial Information Research Centre (SIRC) and actively pursues research interests in spatial modelling, theoretical population genetics and evolutionary computation models.

Professor Whigham's interests include many aspects of spatial research including the use of machine learning techniques for modelling spatio-temporal patterns and the use of spatial systems for modelling ecological behaviour, aspects of public health and theoretical population genetics.

He also performs basic research in the field of evolutionary computation, especially genetic programming. His teaching interests include spatial modelling and analysis, intelligent information systems and applied ecology.

Current PhD students are performing research in financial and economic modelling of business processes, remote sensing technologies for methane emissions and landuse, general ecology and the interdisciplinarity of research teams at universities.

Professor Whigham is also a member of the research group:
Data Science

Professor Whigham is also the recipient of Teaching Awards and Supervisor Awards.



Currently supervising

  • Valentin Kiselev
  • Harry Peyhani
  • Mahsa Toorchi
  • Adriaan Lotter

Currently co-supervising

  • Saeed Rahimi
  • Caitlin Owen
  • Maryam Nakhoda


Rahimi, S., Moore, A. B., Whigham, P. A., & Dillingham, P. (2023). Counterfactual reasoning in space and time: Integrating graphical causal models in computational movement analysis. Transactions in GIS. Advance online publication. doi: 10.1111/tgis.13100 Journal - Research Article

Nakhoda, M., Whigham, P., & Zwanenburg, S. (2023). Quantifying and addressing uncertainty in the measurement of interdisciplinarity. Scientometrics, 128, 6107-6127. doi: 10.1007/s11192-023-04822-2 Journal - Research Article

Owen, C. A., Dick, G., & Whigham, P. A. (2023). Using decomposed error for reproducing implicit understanding of algorithms. Evolutionary Computation. Advance online publication. doi: 10.1162/evco_a_00321 Journal - Research Article

Owen, C. A., Dick, G., & Whigham, P. A. (2022). Towards explainable AutoML using error decomposition. Advances in artificial intelligence: Lecture notes in artificial intelligence (Vol. 13728). (pp. 177-190). Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22695-3_32 Conference Contribution - Published proceedings: Full paper

Rahimi, S., Moore, A. B., & Whigham, P. A. (2022). A vector-agent approach to (spatiotemporal) movement modelling and reasoning. Scientific Reports, 12(1), 21179. doi: 10.1038/s41598-022-22056-9 Journal - Research Article

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