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Jeremiah Deng imageBSc(UESTC), MSc(SCUT), PhD(SCUT), MIEEE, MACM
Associate Professor

Room 3.34, Otago Business School
Tel +64 3 479 8090

Background and interests

Associate Professor Jeremiah Deng is interested in developing intelligent algorithms for pattern recognition, machine learning, and optimization of computer and network systems. His recent work investigates online adaptive learning algorithms for anomaly detection, scene categorization, semantic video analysis, event detection, and performance modeling and optimization of wireless networks. He has authored/co-authored more than 100 papers published in peer-reviewed journals and conference proceedings, or as book chapters. Dr. Deng is a member of ACM and IEEE, and serves on the editorial board of Cognitive Computation (Springer). He co-chairs the Machine Learning for Sensory Data Analysis (MLSDA) workshops (in conjunction with PAKDD), and has served on the program committees of a number of international conferences such as IJCAI, PRICAI, ACCV, GlobeCom, ICC and ECE.

Dr. Deng teaches a variety of undergraduate and postgraduate courses in Information Science and Telecommunications (Applied Science). He is currently the Director of the Telecommunications Programme and supports ongoing curriculum development for BAppSc/PGDip/MAppSc qualifications.

For more information, including recent publications, see his personal website (link above).



Currently supervising

  • Sean Lee
  • Ahmad Shahi
  • Sophie Zareei
  • Robert Hou
  • Chontira Chumsaeng


Yuan, S., Zhao, W., Deng, J. D., Xia, S., & Li, X. (2024). Quantum image edge detection based on Laplacian of Gaussian operator. Quantum Information Processing, 23(5), 178. doi: 10.1007/s11128-024-04392-z Journal - Research Article

Tetereva, A., Li, J., Gibson, B., van der Vliet, W., Deng, J., & Pat, N. (2023). Benchmark machine-learning based multimodal MRI to capture cognitive abilities across the lifespan: Predictability, reliability and generalisability. Proceedings of the Psycolloquy Symposium. (pp. 35). Dunedin, New Zealand: Department of Psychology, University of Otago. Retrieved from Conference Contribution - Published proceedings: Abstract

Pang, Y., Zhang, H., Deng, J. D., Peng, L., & Teng, F. (2023). Collaborative learning with heterogeneous local models: A rule-based knowledge fusion approach. IEEE Transactions on Knowledge & Data Engineering. Advance online publication. doi: 10.1109/TKDE.2023.3341808 Journal - Research Article

Fernando, E. N., & Deng, J. D. (2023). Enhancing hate speech detection in Sinhala language on social media using machine learning. Proceedings of the Australasian Conference on Information Systems (ACIS). 52. Retrieved from Conference Contribution - Published proceedings: Full paper

Zwanenburg, S. P., Vincent, K., Deng, J., Gurtner, M., Gage, R., Smith, M., & Signal, L. (2023). Kids’ digital distractions: An observation study of recorded everyday screentime by 12-year-olds. Proceedings of the Australasian Conference on Information Systems (ACIS). 110. Retrieved from Conference Contribution - Published proceedings: Full paper

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