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Data Science

Data Science studies the tools and methods to organise and process data sets. As data sets become larger and more interconnected, they carry a greater potential for detecting patterns that prove useful for science, industry, and healthcare. Yet large sets of complex data, often composed of both structured and unstructured data, also present significant challenges with regard to organising, storing, and processing them.

The Data Sciences Research Group studies the use of large databases, distributed databases, and cloud computing. We also develop and adopt various methods including evolutionary computing, statistical methods, visualisation, agents, pattern recognition, and machine learning.
Our work and that of our postgraduate students directly informs our teaching in the Master of Business Data Science (MBusDataSci).

Group Members

Core members:

Adjunct members:

Selected Publications

  • Dick, G. (2012). Niche allocation in spatially-structured evolutionary algorithms with gradients. Proceedings of the IEEE Congress on Evolutionary Computation (CEC). doi: 10.1109/CEC.2012.6256542
  • Dick, G., & Whigham, P. A. (2011). Weighted local sharing and local clearing for multimodal optimisation. Soft Computing, 15, 1707-1721. doi: 10.1007/s00500-010-0612-0
  • Whigham, P.A. & Withanawasam, R. "Evolving a Robust Trader in a Cyclic Double Auction Market", GECCO’11 Proceedings of the 13th annual conference on Genetic and Evolutionary computation. 1451 – 1458, (2011).
  • Whigham, P.A., Withanawasam R., Crack, T. and I.M. Premachandra. "Evolving trading strategies for a limit-order book generator”, WCCI 2010 IEEE World Congress on Computational Intelligence July, 18-23, 2010 - CCIB, Barcelona, Spain, 2467 - 2474 (2010). http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5586114
  • Whigham, P. A., & Dick, G. (2010). Implicitly controlling bloat in genetic programming. IEEE Transactions on Evolutionary Computation, 14(2), 173-190. http://dx.doi.org/10.1109/tevc.2009.2027314
  • Dick, G. (2010). Automatic identification of the niche radius using spatially-structured clearing methods. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), (pp. 1264-1271). IEEE. http://dx.doi.org/10.1109/CEC.2010.5586085
  • Dick, G. (2010). The utility of scale factor adaptation in differential evolution. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), (pp. 4355-4362). IEEE. http://dx.doi.org/10.1109/CEC.2010.5586480
  • Woodford, B. J. (2010). Automatic optimization of pruning in evolving fuzzy neural networks using an entropy measure. Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), (pp. 1053-1059). IEEE. http://dx.doi.org/10.1109/IJCNN.2010.5596728
  • Whigham, P. A., Aldridge, C., & de Lange, M. (2009). Constrained evolutionary art: Interactive flag design. Proceedings of the IEEE Congress on Evolutionary Computation, (pp. 2194-2200). IEEE. http://dx.doi.org/10.1109/CEC.2009.4983213
  • McKay, R. I., Hoai, N. X., Whigham, P. A., Shan, Y., & O'Neill, M. (2010). Grammar-based genetic programming: A survey. Genetic Programming & Evolvable Machines, 11, 365-396. http://dx.doi.org/10.1007/s10710-010-9109-y

[taken from PRML]

  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image Vision Comput. 38: 52-64 (2015) DOI
  • Yuwei Xu, Jeremiah D. Deng, Mariusz Nowostawski, Martin K. Purvis: Optimized routing for video streaming in multi-hop wireless networks using analytical capacity estimation. J. Comput. Syst. Sci. 81(1): 145-157 (2015) [A*] DOI
  • Femi A. Aderohunmu, Davide Brunelli, Jeremiah D. Deng, Martin K. Purvis: A data acquisition protocol for a reactive wireless sensor network monitoring application, MDPI Sensors 15: 10221-10254 (2015)DOI
  • Munir Shah, Jeremiah D. Deng, Brendon J. Woodford: Video background modeling: recent approaches, issues and our proposed techniques. Mach. Vis. Appl. 25(5): 1105-1119 (2014) DOI
  • Xianbin Gu, Jeremiah D. Deng, Martin K. Purvis: Improving superpixel-based image segmentation by incorporating color covariance matrix manifolds. ICIP 2014: 4403-4406 DOI
  • Yong, S.-P., Deng, J. D., & Purvis, M. K. (2013). Wildlife video key-frame extraction based on novelty detection in semantic context. Multimedia Tools & Applications. 62(2): 359-376 (2013). DOI
  • Yong, S.-P., Deng, J. D., & Purvis, M. K. (2012). Novelty detection in wildlife scenes through semantic context modelling. Pattern Recognition, 45(9), 3439-3450. DOI [A*]
  • G. Guan, Z. Wang, S. Lu, J. D. Deng, D. D. Feng (2012). Keypoint based key frame selection, IEEE Transactions on Circuits and Systems for Video Technology, 2012. DOI
  • Suet-Peng Yong, Jeremiah D. Deng, Martin K. Purvis: Key-frame extraction of wildlife video based on semantic context modeling. IJCNN 2012: 1-8 [CORE A]
  • H. Lin, J. D. Deng, B. J. Woodford (2012). Video Manifold Modelling: Finding the Right Parameter Settings for Anomaly Detection, Proc. International Conference on Imaging and Vision Computing New Zealand, 168-173, 2012.
  • Yong, S.-P., Deng, J. D., & Purvis, M. K. (2010). Modelling semantic context for novelty detection in wildlife scenes. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), (pp. 1254-1259). IEEE. DOI

Publications

Rahimi, S., Moore, A. B., & Whigham, P. A. (2020). Beyond objects in space-time: Towards a movement analysis framework with ‘How ’and ‘Why’ elements. Journal of Spatial Information Science. Advance online publication. Retrieved from http://josis.org/index.php

Easton, L. J., Bishop, P. J., & Whigham, P. A. (2020). Balancing act: Modelling sustainable release numbers for translocations. Animal Conservation, 23, 434-442. doi: 10.1111/acv.12558

Sharma, P., Savarimuthu, B. T. R., & Stanger, N. (2020). Mining decision-making processes in open source software development: A study of Python Enhancement Proposals (PEPs) using email repositories. Proceedings of the Evaluation and Assessment in Software Engineering (EASE). (pp. 200-209). ACM. doi: 10.1145/3383219.3383240

Dick, G., Owen, C. A., & Whigham, P. A. (2020). Feature standardisation and coefficient optimisation for effective symbolic regression. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). (pp. 306-314). ACM. doi: 10.1145/3377930.3390237

Meredith-Jones, K., Haszard, J., Stanger, N., & Taylor, R. (2018). Precision of DXA-derived visceral fat measurements in a large sample of adults of varying body size. Obesity, 26(3), 505-512. doi: 10.1002/oby.22108

Journal - Research Article

Rahimi, S., Moore, A. B., & Whigham, P. A. (2020). Beyond objects in space-time: Towards a movement analysis framework with ‘How ’and ‘Why’ elements. Journal of Spatial Information Science. Advance online publication. Retrieved from http://josis.org/index.php

Easton, L. J., Bishop, P. J., & Whigham, P. A. (2020). Balancing act: Modelling sustainable release numbers for translocations. Animal Conservation, 23, 434-442. doi: 10.1111/acv.12558

Meredith-Jones, K., Haszard, J., Stanger, N., & Taylor, R. (2018). Precision of DXA-derived visceral fat measurements in a large sample of adults of varying body size. Obesity, 26(3), 505-512. doi: 10.1002/oby.22108

Easton, L. J., Rawlence, N. J., Worthy, T. H., Tennyson, A. J. D., Scofield, R. P., Easton, C. J., … Whigham, P. A., Dickinson, K. J. M., & Bishop, P. J. (2018). Testing species limits of New Zealand’s leiopelmatid frogs through morphometric analyses. Zoological Journal of the Linnean Society, 183(2), 431-444. doi: 10.1093/zoolinnean/zlx080

Whigham, P. A., Dick, G., & Maclaurin, J. (2017). On the mapping of genotype to phenotype in evolutionary algorithms. Genetic Programming & Evolvable Machines, 18(3), 353-361. doi: 10.1007/s10710-017-9288-x

Whigham, P. A., Dick, G., & Maclaurin, J. (2017). Just because it works: A response to comments on "On the mapping of genotype to phenotype in evolutionary algorithms". Genetic Programming & Evolvable Machines, 18(3), 399-405. doi: 10.1007/s10710-017-9289-9

Stanger, N., Alnaghaimshi, N., & Pearson, E. (2017). How do Saudi youth engage with social media? First Monday, 22(5). doi: 10.5210/fm.v22i5.7102

Whigham, P. A., de Graaf, B., Srivastava, R., & Glue, P. (2016). Managing distance and covariate information with point-based clustering. BMC Medical Research Methodology, 16(1), 115. doi: 10.1186/s12874-016-0218-z

Mark, A. F., Molau, U., Whigham, P., Little, L., & Nielsen, J. (2016). Periglacial tarn on the Rock and Pillar Range crest, south-central South Island, New Zealand, and its surrounding snowbank community. Austral Ecology, 41(3), 282-290. doi: 10.1111/aec.12310

Nielsen, J. A., Frew, R. D., Whigham, P. A., Callaway, R. M., & Dickinson, K. J. M. (2016). Thyme travels: 15N isoscapes of Thymus vulgaris L. invasion in lightly grazed pastoral communities. Austral Ecology, 41(1), 28-39. doi: 10.1111/aec.12284

Whigham, P. A., Dick, G., & Parry, M. (2016). Network rewiring dynamics with convergence towards a star network. Proceedings of the Royal Society A, 472(2194), 20160236. doi: 10.1098/rspa.2016.0236

Easton, L. J., Dickinson, K. J. M., Whigham, P. A., & Bishop, P. J. (2016). Habitat suitability and requirements for a threatened New Zealand amphibian. Journal of Wildlife Management. doi: 10.1002/jwmg.1071

Cranston, B. H., Monks, A., Whigham, P. A., & Dickinson, K. J. M. (2015). Variation and response to experimental warming in a New Zealand cushion plant species. Austral Ecology, 40, 642-650. doi: 10.1111/aec.12231

Nielsen, J. A., Whigham, P. A., Frew, R. D., Callaway, R. M., & Dickinson, K. J. M. (2015). Thyme and space invasion: Thymus vulgaris decreases exotic plant species diversity in Central Otago, New Zealand. Biological Invasions, 17(8), 2261-2274. doi: 10.1007/s10530-015-0872-9

Nielsen, J. A., Frew, R. D., Whigham, P. A., Callaway, R. M., & Dickinson, K. J. M. (2015). Germination and growth responses of co-occurring grass species to soil from under invasive Thymus vulgaris. Allelopathy, 35(1), 139-152.

Whigham, P. A., Owen, C. A., & MacDonell, S. G. (2015). A baseline model for software effort estimation. ACM Transactions on Software Engineering & Methodology, 24(3), 20. doi: 10.1145/2738037

Nielsen, J. A., Frew, R. D., Whigham, P. A., Callaway, R. M., & Dickinson, K. J. M. (2014). Thyme invasion and soil properties in the Central Otago region of New Zealand. Geoderma Regional, 1, 48-58. doi: 10.1016/j.geodrs.2014.08.002

Angrosh, M. A., Cranefield, S., & Stanger, N. (2014). Contextual information retrieval in research articles: Semantic publishing tools for the research community. Semantic Web, 5(4), 261-293. doi: 10.3233/SW-130097

Harris, K. M., Dickinson, K. J. M., & Whigham, P. A. (2014). Functional connectivity and matrix quality: Network analysis for a critically endangered New Zealand lizard. Landscape Ecology, 29(1), 41-53. doi: 10.1007/s10980-013-9967-9

Nielsen, J. A., Whigham, P. A., Frew, R. D., Callaway, R. M., & Dickinson, K. J. M. (2014). Invasion essentials: Does secondary chemistry plasticity contribute to the invasiveness of Thymus vulgaris L.? Chemoecology, 24(1), 15-27. doi: 10.1007/s00049-013-0142-1

Angrosh, M. A., Cranefield, S., & Stanger, N. (2013). Context identification of sentences in research articles: Towards developing intelligent tools for the research community. Natural Language Engineering, 19(4), 481-515. doi: 10.1017/S1351324912000277

Withanawasam, R. M., Whigham, P. A., & Crack, T. F. (2013). Characterising trader manipulation in a limit-order driven market. Mathematics & Computers in Simulation, 93, 43-52. doi: 10.1016/j.matcom.2012.09.012

Gebauer, K., Dickinson, K. J. M., Whigham, P. A., & Seddon, P. J. (2013). Matrix matters: Differences of grand skink metapopulation parameters in native tussock grasslands and exotic pasture grasslands. PLoS ONE, 8(10), e76076. doi: 10.1371/journal.pone.0076076

Withanawasam, R. M., Whigham, P. A., & Crack, T. F. (2013). Characterizing limit order prices. Physica A, 392(21), 5346-5355. doi: 10.1016/j.physa.2013.06.060

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Journal - Research Other

Whigham, P. A. (2014). Wolfgang Banzhaf: Genetic programming and emergence. Genetic Programming & Evolvable Machines, 15(1), 99-101. doi: 10.1007/s10710-013-9204-y

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