Jeremiah D. Deng
Associate Professor
Department of Information Science
University of Otago
Po Box 56, Dunedin, New Zealand
Tel: 64-3-479 8090, Fax: 64-3-479 8311
E-mail - jeremiah dot deng at otago dot ac dot nz

Office: OBS 3.34, Commerce Bld., Cnr Union St. & Clyde St.


Teaching for 2022

S2: INFO411 - Machine Learning and Data Mining FY: INFO501/580 Data Science Project

I am coordinating these programmes: MBusDataSc, MAppSci in Telecommunications.

Research

I lead the PRML Lab.

Selected recent publications:

Machine learning & computational intelligence

Biomedical signal analysis
  • A Tetereva, J Li, J D Deng, A Stringaris, N Pat. Capturing Brain-Cognition Relationship: Integrating Task-Based fMRI Across Tasks Markedly Boosts Prediction and Reliability and Reveals the Role of Frontoparietal Areas. bioRXiv, 2022; Preprint in NeuroImage.
  • J Li, JD Deng, D De Ridder, D Adhia. Gender classification of EEG signals using a motif attribute classification ensemble. Inter. Joint Conf. on Neural Networks (IJCNN) 2020: 1-8
  • J Li, JD Deng, D De Ridder, D Adhia. Resting-state EEG sex classification using selected brain connectivity representation. To appear in Advances in Artificial Intelligence, Computation, and Data Science in Medicine and Life Science, Springer. arXiv
Image segmentation
  • J Hou, X Ding, JD Deng. Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations. WACV 2022: 1769-1778.
  • X Gu, JD Deng, A multi-feature bipartite graph ensemble for image segmentation, accepted by Pattern Recognition Letters, 2019 (doi)
  • X. Gu, J. D. Deng, M. K. Purvis, Improving superpixel-based image segmentation by incorporating color covariance matrix Manifolds, Proc. ICIP'14 Paris. (Top 10% Paper)
Deep learning and domain adaptation
  • J Hou, X Ding, JD Deng, S Cranefield. Deep adversarial transition learning using cross-grafted generative stacks. Neural Networks 149: 172-183 (2022) arXiv
  • J Hou, JD Deng, S Cranefield, X Ding. Cross-domain latent modulation for variational transfer learning, Proc. WACV'2021. arXiv
  • J Hou, JD Deng, S Cranefield, X Ding. Variational Transfer Learning using Cross-Domain Latent Modulation, arXiv, 2022.
Video surveillance and anomaly detection
  • H. Lin, J. D. Deng, D. Alberts, F. Wilhelm, Helmet use detection of tracked motorcycles using cnn-based multi-task learning, IEEE Access, 2020 (doi)
  • H. Lin, J. D. Deng, B. J. Woodford, A. Shahi: Online weighted clustering for real-time abnormal event detection in video surveillance. ACM Multimedia 2016: 536-540. (doi)
  • H. Lin, J. D. Deng, B. J. Woodford, Anomaly detection in crowd scenes via online adaptive one-class support vector machines, Proc. ICIP'15 Quebec.
Stochastic optimization and computational intelligence
  • F-F Wei; W-N Chen; Q. Yang; J. Deng; X-N Luo; H. Jin; J. Zhang: Classifier-assisted level-based learning swarm optimizer for expensive optimization. IEEE Transactions on Evolutionary Computation, 25(2):219-233, IEEExplore
  • Q. Liu; W-N Chen; J. D. Deng; T. Gu; H. Zhang; Z. Yu; J. Zhang. Benchmarking stochastic algorithms for global optimization problems by visualizing confidence intervals, IEEE Transactions on Cybernetics, 2017, 47(9):2924 - 2937. (doi)
  • Q. Yang; W. N. Chen; J. D. Deng; Y. Li; J. Zhang, A level-based learning swarm optimizer for large scale optimization, IEEE Transactions on Evolutionary Computation, 22:578-594, 2017. (doi)
  • Q. Yang; W-N Chen; T. Gu; H. Zhang; J. D. Deng; Y. Li; J. Zhang. Segment-based predominant learning swarm optimizer for large-scale optimization, IEEE Transactions on Cybernetics, 2017, 47(9):2896 - 2910. (doi)

    Other recent papers

  • Kids Online Aotearoa: An objective protocol to study the nature and extent of children’s online world, JMIR Protocols, preprint, 7/2022.
  • J. D. Deng, Online outlier detection of energy data streams using incremental and kernel PCA algorithms, Proc. 2016 IEEE ICDM Workshops, December 12, Barcelona, pp.390-397. (doi)
  • A. Shahi, J. D. Deng, B. Woodford, A streaning ensemble with multi-class imbalance learning for activity recognition, Proc. IEEE Inter. Joint Conf. on Neural Networks (IJCNN) 2017: 3983-3990. (doi)
  • S H-S Lee, J. D. Deng, L. Peng, M. K. Purvis, M. Purvis: Top-k merit weighting PBIL for optimal coalition structure generation of smart grids. ICONIP (4) 2017: 171-181 (doi)
  • A. Shahi, J. D. Deng, B. J. Woodford: Online hidden conditional random fields to recognize activity-driven behavior using adaptive resilient gradient learning. ICONIP (1) 2017: 515-525
  • M. Shah, J. D. Deng, B. J. Woodford: A Self-adaptive CodeBook (SACB) model for real-time background subtraction. Image Vision Comput. 38: 52-64 (2015)
  • J. D. Deng, C. Simmermacher and S. Cranefield. A study on feature analysis for musical instrument classification. IEEE Trans. System, Man and Cybernetics - Part B, vol. 38, no. 2, pp.429-438, 2008. [preprint]
  • D. Deng, Content-based image collection summarization and comparison using self-organizing maps. Pattern Recognition, 40:2, pp.718-727, 2007. [doi]

Performance modeling and mobile computing

  • J. D. Deng, Performance Modelling of Synchronized Predictive Sensing for Clustered Wireless Sensor Networks, APCC'19, Ho Chi Minh City, 2019.
  • S. Zareei, A. Sedigh, J. D. Deng, M. Purvis, Buffer management using integrated queueing models for mobile energy harvesting sensors, PIMRC'17, 2017.
  • X-F Liu; Z-H Zhan; J. D. Deng; Y. Li; T. Gu; J. Zhang. An energy efficient ant colony system for virtual machine placement in cloud computing, IEEE Transactions on Evolutionary Computation, 2016, online. (doi)
  • Y. Xu, J. D. Deng, M. Nowostawski, M. K. Purvis, Optimized routing for video streaming in multi-hop wireless networks using analytical capacity estimation, ournal of Computer and System Sciences, 81(1): 145-157, 2015.

Edited books

  • Proceedings of the Australasian Joint Conference on Artificial Intelligence - Workshops (AIW'19), J. D. Deng and A. Rahman Eds., ACM, 2019.
  • Proceedings of the 2nd Workshop on Machine Learning for Sensory Data Analysis (MLSDA'14), A. Rahman, J. D. Deng and J. Li Eds., ACM, 2014 (in conjunction with PRICAI'14).
  • Proceedings of the 1st Workshop on Machine Learning for Sensory Data Analysis (MLSDA'13), J. D. Deng and H. Zhang Eds., ACM, 2013 (in conjunction with AI'13).
  • Proceedings of the 27th Conf. on Image and Vision Computing New Zealand (IVCNZ'12), edited by B. McCane, S. Mills and J. D. Deng, ACM, 2012.

Other stuff

I blog on maths/computing in Julia, and on 神學.

My daughter Modi (默笛) is a pianist and a published writer.


Last modified: 13/8/2022