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Brendon Woodford imageNZCDP(Stage III), BSc, PGCertTertT, PGDipSci, MSc, PhD (Otago)
Senior Lecturer

Room 3.47, Otago Business School
Tel +64 3 479 5432
Email brendon.woodford@otago.ac.nz

Background and interests

Dr Brendon Woodford lectures in the diverse areas of knowledge engineering, machine learning, information systems development, and health informatics.

He conducts research for the Knowledge, Intelligence and Web Informatics (KIWI) Laboratory in the areas of artificial neural networks, fuzzy systems, data visualisation, and image processing and recognition. Since 1998 the overall aim of this research is in the area of computational intelligence. The main objective of his work has been to create adaptive learning systems which generate new knowledge from data that they process and allow for improved decision making in difficult real-world domains.

In the past the application of this work has been improving upon existing machine learning techniques to support decision making and data mining primarily in the horticultural domain but the current focus is now in the health data analytics domain.

This research has contributed to 27 publications to date in both international journals and in some of the top international conferences. In 2008 he completed a PhD which primarily looked at the development and implementation of intelligent decision support systems for New Zealand's horticulture industry.

Dr Woodford is also a member of the research group:
Intelligent Computing and Networking

Papers

  • COMP 111 Information and Communications Technology
  • COMP 120 Practical Data Science
  • INFO 204 Introduction to Data Science
  • INFO 411 Machine Learning and Data Mining

Supervision

Currently supervising

  • Nuzla Ismail

Currently co-supervising

  • Ahmad Shahi

Publications

Woodford, B. J. (2023). Automatic parameter optimisation framework for ECoS-based models. Proceedings of the International Joint Conference on Neural Networks (IJCNN). IEEE. doi: 10.1109/IJCNN54540.2023.10191789
Conference Contribution - Published proceedings: Full paper
Ghandour, A., Woodford, B. J., Almutairy, A., & Al-Srehan, H. S. (2022). Means to support the ends: Forums that escape the official gaze in the educational institutions. Proceedings of the International Arab Conference on Information Technology (ACIT). IEEE. doi: 10.1109/ACIT57182.2022.9994133
Conference Contribution - Published proceedings: Full paper
Woodford, B. J. (2022). Boosted self-evolving neural networks for pattern recognition. Advances in artificial intelligence: Lecture notes in artificial intelligence (Vol. 13728). (pp. 456-469). Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22695-3_32
Conference Contribution - Published proceedings: Full paper
Cornwall, J., English, S., Woodford, B., Elliot, J., & McAuley, K. (2022). An exploration of Aotearoa New Zealanders' attitudes and perceptions on the use of posthumous healthcare data. New Zealand Medical Journal, 135(1554), 44-54. Retrieved from https://www.nzma.org.nz/journal
Journal - Research Article
Ghandour, A., & Woodford, B. J. (2021). Regulating Internet of Things: The case of the United Arab Emirates. TEM Journal, 10(3), 1031-1038. doi: 10.18421/TEM103-04
Journal - Research Article
Shahi, A., Woodford, B. J., & Lin, H. (2017). Dynamic real-time segmentation and recognition of activities using a multi-feature windowing approach. In U. Kang, E.-P. Lim, J. X. Yu & Y.-S. Moon (Eds.), Trends and applications in knowledge discovery and data mining: PAKDD Workshops, revised selected papers: Lecture notes in artificial intelligence (Vol. 10526). (pp. 26-38). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-67274-8_3
Chapter in Book - Research
Lin, H., Deng, J. D., & Woodford, B. J. (2016). Shot boundary detection using multi-instance incremental and decremental one-class support vector machine. In J. Bailey, L. Khan, T. Washio, G. Dobbie, J. Z. Huang & R. Wang (Eds.), Advances in knowledge discovery and data mining: Proceedings of the 20th Pacific-Asia Conference PAKDD, part 1: Lecture Notes in Artificial Intelligence (Vol. 9651). (pp. 165-176). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-31753-3_14
Chapter in Book - Research
Shah, M., Deng, J., & Woodford, B. (2013). Illumination invariant background model using mixture of Gaussians and SURF features. In J.-I. Park & J. Kim (Eds.), Computer vision: ACCV 2012 International Workshops, revised selected papers, part 1: Lecture notes in computer science (Vol. 7728). (pp. 308-314). Berlin, Germany: Springer. doi: 10.1007/978-3-642-37410-4_27
Chapter in Book - Research
Kasabov, N. K., Israel, S. A., & Woodford, B. J. (1999). Adaptive, evolving, hybrid connectionist systems for image pattern recognition. In S. Pal, A. Ghosh & M. Kundu (Eds.), Soft Computing for Image Processing. (pp. 318-336). Heidleberg, Germany: Springer Verlag.
Chapter in Book - Research
Cornwall, J., English, S., Woodford, B., Elliot, J., & McAuley, K. (2022). An exploration of Aotearoa New Zealanders' attitudes and perceptions on the use of posthumous healthcare data. New Zealand Medical Journal, 135(1554), 44-54. Retrieved from https://www.nzma.org.nz/journal
Journal - Research Article
Ghandour, A., & Woodford, B. J. (2021). Regulating Internet of Things: The case of the United Arab Emirates. TEM Journal, 10(3), 1031-1038. doi: 10.18421/TEM103-04
Journal - Research Article
Stamou, G., Garcia-Palacios, A., Woodford, B. J., Suso-Ribera, C., & Botella, C. (2021). The combination of cognitive-behavioural therapy with virtual reality for the treatment of postnatal depression in a brief intervention context: A single-case study trial. Journal of Healthcare Engineering, 2021, 5514770. doi: 10.1155/2021/5514770
Journal - Research Article
Shah, M., Deng, J. D., & Woodford, B. J. (2015). A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image & Vision Computing, 38, 52-64. doi: 10.1016/j.imavis.2015.02.001
Journal - Research Article
Shah, M., Deng, J. D., & Woodford, B. J. (2014). Video background modeling: Recent approaches, issues and our proposed techniques. Machine Vision & Applications, 25(5), 1105-1119. doi: 10.1007/s00138-013-0552-7
Journal - Research Article
Mann, S. L., Marshall, M. R., Woodford, B. J., Holt, A., & Williams, A. B. (2012). Predictive performance of Acute Physiological and Chronic Health Evaluation releases II to IV: A single New Zealand centre experience. Anaesthesia & Intensive Care, 40(3), 479-489.
Journal - Research Article
Mann, S. L., Marshall, M. R., Holt, A., Woodford, B., & Williams, A. B. (2010). Illness severity scoring for Intensive Care at Middlemore Hospital, New Zealand: Past and future. New Zealand Medical Journal, 123(1316). Retrieved from http://journal.nzma.org.nz/journal/123-1316/4157/content.pdf
Journal - Research Article
Woodford, B. J. (2008). Evolving neurocomputing systems for horticulture applications. Applied Soft Computing, 8, 564-578. doi: 10.1016/j.asoc.2006.05.006
Journal - Research Article
Shaw, D., Woodford, B. J., & Benwell, G. L. (2007). Educating future IS professionals through real-world integration. International Journal of Teaching & Case Studies, 1(1/2), 66-83.
Journal - Research Article
Kasabov, N. K., Israel, S. A., & Woodford, B. J. (2000). The application of hybrid evolving connectionist systems to image classification. International Journal of Advanced Computational Intelligence, 4(1), 57-65.
Journal - Research Article
Woodford, B. J. (2023). Automatic parameter optimisation framework for ECoS-based models. Proceedings of the International Joint Conference on Neural Networks (IJCNN). IEEE. doi: 10.1109/IJCNN54540.2023.10191789
Conference Contribution - Published proceedings: Full paper
Ghandour, A., Woodford, B. J., Almutairy, A., & Al-Srehan, H. S. (2022). Means to support the ends: Forums that escape the official gaze in the educational institutions. Proceedings of the International Arab Conference on Information Technology (ACIT). IEEE. doi: 10.1109/ACIT57182.2022.9994133
Conference Contribution - Published proceedings: Full paper
Woodford, B. J. (2022). Boosted self-evolving neural networks for pattern recognition. Advances in artificial intelligence: Lecture notes in artificial intelligence (Vol. 13728). (pp. 456-469). Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22695-3_32
Conference Contribution - Published proceedings: Full paper
Woodford, B. J., & Ghandour, A. (2021). An information retrieval-based approach to activity recognition in Smart Homes. In H. Hacid, F. Outay, H.-Y. Paik, A. Alloum, M. Petrocchi, M. R. Bouadjenek, … A. Maaradji (Eds.), Service-oriented computing: ICSOC 2020 Workshops: Lecture notes in computer science (Vol. 12632). 12632 LNCS, (pp. 583-595). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-76352-7_51
Conference Contribution - Published proceedings: Full paper
Ghandour, A., & Woodford, B. J. (2020). COVID-19 impact on e-commerce in UAE. Proceedings of the 21st International Arab Conference on Information Technology (ACIT). IEEE. doi: 10.1109/ACIT50332.2020.9300077
Conference Contribution - Published proceedings: Full paper
Ghandour, A., & Woodford, B. J. (2019). Ethical issues in artificial intelligence in UAE. Proceedings of the International Arab Conference on Information Technology (ACIT). (pp. 262-266). IEEE. [Full Paper]
Conference Contribution - Published proceedings: Full paper
Ismail, F. N., Woodford, B. J., & Licorish, S. A. (2019). Evaluating the boundaries of big data environments for machine learning. In J. Liu & J. Bailey (Eds.), Advances in artificial intelligence: Lecture notes in artificial intelligence (Vol. 11919). (pp. 253-264). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-35288-2_21
Conference Contribution - Published proceedings: Full paper
Shahi, A., Deng, J. D., & Woodford, B. J. (2017). A streaming ensemble classifier with multi-class imbalance learning for activity recognition. Proceedings of the International Joint Conference on Neural Networks (IJCNN). (pp. 3983-3990). IEEE. doi: 10.1109/IJCNN.2017.7966358
Conference Contribution - Published proceedings: Full paper
Shahi, A., Deng, J. D., & Woodford, B. J. (2017). Online hidden conditional random fields to recognize activity-driven behavior using adaptive resilient gradient learning. In D. Liu, S. Xie, Y. Li, D. Zhao & E.-S. M. El-Alfy (Eds.), Neural Information Processing: Lecture notes in computer science (Vol. 10634). (pp. 515-525). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-70087-8
Conference Contribution - Published proceedings: Full paper
Lin, H., Deng, J. D., Woodford, B. J., & Shahi, A. (2016). Online weighted clustering for real-time abnormal event detection in video surveillance. Proceedings of the Association for Computing Machinery (ACM) on Multimedia Conference. (pp. 536-540). New York, NY: ACM. doi: 10.1145/2964284.2967279
Conference Contribution - Published proceedings: Full paper
Lin, H., Deng, J. D., & Woodford, B. J. (2015). Anomaly detection in crowd scenes via online adaptive one-class support vector machines. Proceedings of the International Conference on Image Processing (ICIP). (pp. 2434-2438). IEEE. doi: 10.1109/icip.2015.7351239
Conference Contribution - Published proceedings: Full paper
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