School of Engineering and Computer Science Te Kura Mātai Pūkaha, Pūrorohiko

Research Outputs

Authored Book

  1. Yanan Sun, Gary G. Yen, Mengjie Zhang, “Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances” Springer, 09 November 2022. DOI: https://doi.org/10.1007/978-3-031-16868-0 (XVI + 331 pages, the first book on evolutionary neural architecture search)
  2. Fangfang Zhang, Su Nguyen, Yi Mei, and Mengjie Zhang. Genetic Programming for Production Scheduling: An Evolutionary Learning Approach, Springer Book Series on Machine Learning: Foundations, Methodologies, and Applications, 2021, DOI: https://doi.org/10.1007/978-981-16-4859-5.
  3. Ying Bi, Bing Xue, and Mengjie Zhang. Genetic Programming for Image Classification: An Automated Approach to Feature Learning, Springer International Publishing 2021, DOI: https://doi.org/10.1007/978-3-030-65927-1. Code is available here

Refereed Journal Papers (selected)

  1. Zeng, Dylon, Ivy Liu, Ying Bi, Ross Vennell, Dana Briscoe, Bing Xue, and Mengjie Zhang. "A new multi-object tracking pipeline based on computer vision techniques for mussel farms." Journal of the Royal Society of New Zealand (2023): 1-20. (Q1)
  2. Bi, Ying, Xue, Bing, Mesejo, Pablo, Cagnoni, Stefano and Zhang, Mengjie. "A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends", IEEE Transactions on Evolutionary Computation, 2022. (Q1)
  3. Fernández, Daniel, Louise McMillan, Richard Arnold, Martin Spiess, and Ivy Liu. "Goodness-of-fit and generalized estimating equation methods for ordinal responses based on the stereotype model." Stats 5, no. 2 (2022): 507-520.
  4. Huang, Junhao, Xue, Bing, Sun, Yanan and Zhang, Mengjie. "Particle Swarm Optimization for Compact Neural Architecture Search for Image Classification", IEEE Transactions on Evolutionary Computation, 2022. (Q1))
  5. Preedalikit, Kemmawadee, Daniel Fernández, Ivy Liu, Louise McMillan, Marta Nai Ruscone, and Roy Costilla. "Row mixture-based clustering with covariates for ordinal responses." Computational Statistics (2023): 1-45.
  6. Liu, Ivy, Thomas Suesse, Samuel Harvey, Peter Yongqi Gu, Daniel Fernández, and John Randal. "Generalized Mantel–Haenszel Estimators for Simultaneous Differential Item Functioning Tests." Educational and Psychological Measurement (2022): 00131644221128341.
  7. Wang, Alex X., Stefanka S. Chukova, and Binh P. Nguyen. "Ensemble k-nearest neighbors based on centroid displacement." Information Sciences, 629 (2023): 313-323. (Q1)
  8. Owen, Caitlin A., Grant Dick, and Peter A. Whigham. "Using Decomposed Error for Reproducing Implicit Understanding of Algorithms." Evolutionary Computation (2023): 1-20. (Q1)
  9. Owen, Caitlin A., Grant Dick, and Peter A. Whigham. "Standardization and Data Augmentation in Genetic Programming." IEEE Transactions on Evolutionary Computation 26, no. 6 (2022): 1596-1608. (Q1)
  10. Babu, Krishna Moorthy, Daniel Bentall, David T. Ashton, Morgan Puklowski, Warren Fantham, Harris T. Lin, Nicholas PL Tuckey, Maren Wellenreuther, and Linley K. Jesson. "Computer vision in aquaculture: a case study of juvenile fish counting." Journal of the Royal Society of New Zealand 53, no. 1 (2023): 52-68. (Q1)
  11. Bi, Ying, Bing Xue, Dana Briscoe, Ross Vennell, and Mengjie Zhang. "A new artificial intelligent approach to buoy detection for mussel farming." Journal of the Royal Society of New Zealand 53, no. 1 (2023): 27-51. (Q1)
  12. Yang, Cuie, Bing Xue, Kay Chen Tan, and Mengjie Zhang. "A Co-Training Framework for Heterogeneous Heuristic Domain Adaptation." IEEE Transactions on Neural Networks and Learning Systems (2022). (Q1)
  13. Al-Helali, Baligh, Qi Chen, Bing Xue, and Mengjie Zhang. "Multitree Genetic Programming With Feature-Based Transfer Learning for Symbolic Regression on Incomplete Data." IEEE Transactions on Cybernetics (2023). (Q1)
  14. Bi, Ying, Jing Liang, Bing Xue, and Mengjie Zhang. "A Genetic Programming Approach with Building Block Evolving and Reusing to Image Classification." IEEE Transactions on Evolutionary Computation (2023). (Q1)
  15. Xue, Bing, Richard Green, and Mengjie Zhang. "Artificial Intelligence in New Zealand: applications and innovation." Journal of the Royal Society of New Zealand 53, no. 1 (2023): 1-5. (Q1)
  16. Jiao, Ruwang, Bing Xue, and Mengjie Zhang. "Benefiting From Single-Objective Feature Selection to Multiobjective Feature Selection: A Multiform Approach." IEEE Transactions on Cybernetics (2022). (Q1)
  17. Zhang, Fangfang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Multitask multiobjective genetic programming for automated scheduling heuristic learning in dynamic flexible job-shop scheduling." IEEE Transactions on Cybernetics (2022). (Q1)
  18. Ruigrok, Mike, Xue, Bing, Catanach, Andrew, Zhang, Mengjie, Jesson, Linley, Davy, Marcus, Wellenreuther Wellenreuther Maren. "The relative power of structural genomic variation versus SNPs in explaining the quantitative trait growth in the marine teleost Chrysophrys auratus", Genes, vol. 13, no. 7, pp.1129, 2022
  19. Huang, Zhixing, Yi Mei, Fangfang Zhang, and Mengjie Zhang. "Multitask Linear Genetic Programming with Shared Individuals and its Application to Dynamic Job Shop Scheduling." IEEE Transactions on Evolutionary Computation (2023). (Q1)
  20. Zhang, Fangfang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Task relatedness based multitask genetic programming for dynamic flexible job shop scheduling." IEEE Transactions on Evolutionary Computation (2022). (Q1)
  21. Zhang, Fangfang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Multitask genetic programming-based generative hyperheuristics: A case study in dynamic scheduling." IEEE Transactions on Cybernetics 52, no. 10 (2021): 10515-10528. (Q1)
  22. Wang, Shaolin, Yi Mei, and Mengjie Zhang. "A multi-objective genetic programming algorithm with α dominance and archive for uncertain capacitated arc routing problem." IEEE Transactions on Evolutionary Computation (2022). (Q1)
  23. Ying Bi, Bing Xue, Dana Briscoe, Ross Vennell, and Mengjie Zhang. "A New Artificial Intelligent Approach to Buoy Detection for Mussel Farming". Journal of the Royal Society of New Zealand. 24pp, 2022 (Q1)
  24. Atalah Javier, Paul M. South, Dana K. Briscoe, and Ross Vennell. "Inferring parental areas of juvenile mussels using hydrodynamic modelling." Aquaculture, 555, 738227, 2022 (Q1) Valenza‐Troubat Noemie, Elena Hilario, Sara Montanari, Peter Morrison‐Whittle, David Ashton, Peter Ritchie, and Maren Wellenreuther. "Evaluating new species for aquaculture: A genomic dissection of growth in the New Zealand silver trevally (Pseudocaranx georgianus)." Evolutionary Applications, 15(4), 591-602, 2022. (Q1)
  25. Nicholas P. L. Tuckey, David T. Ashton, Jiakai Li, Harris T. Lin, Seumas P. Walker, Jane E. Symonds, Maren Wellenreuther. "Automated image analysis as a tool to measure individualised growth and population structure in Chinook salmon (Oncorhynchus tshawytscha)" in Aquaculture, Fish and Fisheries, 2022 (Q1)
  26. Sara Montanari, Cecilia Deng, Emily Koot, Chris Kirk, Nahla V. Bassil, Peter Morrison-Whittle, Margaret L. Worthington, Julien Pradelles, Maren Wellenreuther, David Chagné. A multi-species plant-animal SNP chip enables diverse breeding and management applications (in press) PlosOne (Q1)
  27. Quang H.Nguyena, Binh P.Nguyenb, Minh T.Nguyena, Matthew C.H.Chuac, Trang T.T.Do, Nhung Nghieme. Bone age assessment and sex determination using transfer learning, Expert Systems with Applications, 2022 (Q1)
  28. Vennell, Ross, Max Scheel, Simon Weppe, Ben Knight, and Malcolm Smeaton. "Fast lagrangian particle tracking in unstructured ocean model grids." Ocean Dynamics 71, no. 4, 423-437, 2021 (Q2)
  29. Vien T. Truong, Binh P. Nguyen, Thanh-Hoang Nguyen-Vo, Wojciech Mazur, Eugene S. Chung, Cassady Palmer, Justin T. Tretter, Tarek Alsaied, Vy T. Pham, Huan Q. Do, Phuong T. N. Do, Vinh N. Pham, Ban N. Ha, Hoa N. Chau & Tuyen K. Le, Application of machine learning in screening for congenital heart diseases using fetal echocardiography, The International Journal of Cardiovascular Imaging, 2022 (Q2)
  30. Valenza-Troubat Noemie, Sara Montanari, Peter Ritchie, and Maren Wellenreuther. "Unraveling the complex genetic basis of growth in New Zealand silver trevally (Pseudocaranx georgianus)." G3, 12(3), 2022 (Q2)
  31. Sandoval-Castillo Jonathan, Luciano B. Beheregaray, and Maren Wellenreuther. "Genomic prediction of growth in a commercially, recreationally, and culturally important marine resource, the Australian snapper (Chrysophrys auratus)." G312, no. 3, 2022 (Q2)
  32. Irving Kate, Wellenreuther Maren, Ritchie Peter A. "Description of the growth hormone gene of the Australasian snapper, Chrysophrys auratus, and associated intra- and interspecific genetic variation". Journal of Fish Biology. 2021, 11pp (Q2)
  33. Mike Ruigrok, Bing Xue, Andrew Catanach, Mengjie Zhang, Linley Jesson, Marcus Davy, Maren Wellenreuther. “The Relative Power of Structural Genomic Variation versus SNPs in Explaining the Quantitative Trait Growth in the Marine Teleost Chrysophrys auratus”. Genes in press (Q2)
  34. Anastasiadi D, Piferrer F, WELLENREUTHER M, Burraco AB. “Fish as model systems to study epigenetic drivers in human self-domestication and neurodevelopmental cognitive disorders”, Genes, 2022 (Q2)
  35. Peng Wang, Bing Xue, Jing Liang and Mengjie Zhang. "Differential Evolution Based Feature Selection: A Niching-based Multi-objective Approach", IEEE Transactions on Evolutionary Computation, 2022. DOI: 10.1109/TEVC.2022.3168052 (Q1)
  36. Xinye Cai, Qi Sun, Zhenhua Li, Xiao Yushun, Yi Mei, Qingfu Zhang, and Xiaoping Li. Cooperative coevolution with knowledge-based dynamic variable decomposition for bilevel multiobjective optimization. IEEE Transactions on Evolutionary Computation, 2022 (Q1)
  37. Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang, and Kay Chen Tan. Surrogate-assisted evolutionary multitasking genetic programming for dynamic flexible job shop scheduling. IEEE Transactions on Evolutionary Computation, 25(4):651--665, 2021 (Q1)
  38. Shaolin Wang, Yi Mei, Mengjie Zhang, and Xin Yao. Genetic programming with niching for uncertain capacitated arc routing problem. IEEE Transactions on Evolutionary Computation, 26(1):73--87, 2022 (Q1)
  39. Qinglan Fan, Ying Bi, Bing Xue, and Mengjie Zhang. "Genetic Programming for Image Classification: A New Program Representation with Flexible Feature Reuse". IEEE Transactions on Evolutionary Computation. 2022. 15pp.  DOI: 10.1109/TEVC.2022.3169490. (Q1)
  40. Andrew Lensen, Bing Xue and Mengjie Zhang." Genetic Programming for Manifold Learning: Preserving Local Topology ", IEEE Transactions on Evolutionary Computation, vol. 26, no. 4, pp. 661-675, Aug. 2022, doi: 10.1109/TEVC.2021.3106672. (Q1)
  41. Ying Bi, Bing Xue, and Mengjie Zhang, "Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning," in IEEE Transactions on Evolutionary Computation, vol. 26, no. 2, pp. 218-232, April 2022, doi: 10.1109/TEVC.2021.3097043. (Q1)
  42. Ke Chen, Bing Xue, Mengjie Zhang and Fengyu Zhou, "Evolutionary Multitasking for Feature Selection in High-Dimensional Classification via Particle Swarm Optimization," in IEEE Transactions on Evolutionary Computation, vol. 26, no. 3, pp. 446-460, June 2022, doi: 10.1109/TEVC.2021.3100056. (Q1)
  43. Ke Chen, Bing Xue, Mengjie Zhang, and Fengyu Zhou. "Correlation-Guided Updating Strategy for Feature Selection in Classification with Surrogate-Assisted Particle Swarm Optimisation", IEEE Transactions on Evolutionary Computation, 2021. (DOI: 10.1109/TEVC.2021.3134804) (Q1)
  44. Bach Hoai Nguyen, Bing Xue, and Mengjie Zhang."A Constrained Competitive Swarm Optimiser with an SVM-based Surrogate Model for Feature Selection". IEEE Transactions on Evolutionary Computation. 2022. 15pp. (Accepted on 7-May-2022) (Q1)
  45. C. A. Owen, G. Dick and P. A. Whigham, "Standardisation and Data Augmentation in Genetic Programming," in IEEE Transactions on Evolutionary Computation, doi: 10.1109/TEVC.2022.3160414. (Q1)
  46. Ying Bi, Bing Xue, and Mengjie Zhang. "Dual-Tree Genetic Programming for Few-Shot Image Classification".  IEEE Transactions on Evolutionary Computation. 2021. 15pp.  DOI: 10.1109/TEVC.2021.3100576. (Q1)
  47. Ying Bi, Bing Xue, and Mengjie Zhang. "Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning". IEEE Transactions on Evolutionary Computation. 2021. 15pp. DOI: 10.1109/TEVC.2021.3097043. (Q1)
  48. Yanan Sun, Ziyao Ren, Gary G. Yen, Bing Xue, Mengjie Zhang,and Jiancheng Lv."ArcText: An Unified Text Approach to Describing Convolutional Neural Network Architectures", IEEE Transactions on Artificial Intelligence. Accepted Nov 2021 (DOI: 10.1109/TAI.2021.3128502) (Q1)
  49. Cuie Yang, Yiu-ming Cheung, Jinliang Ding, Kay Chen Tan, Bing Xue, and Mengjie Zhang."Contrastive Learning Assisted Alignment for Partial Domain Adaptation", IEEE Transactions on Neural Networks and Learning Systems, 2022 (DOI: 10.1109/TNNLS.2022.3145034) (accepted Jan 2022) (Q1)
  50. Emrah Hancer, Bing Xue, and Mengjie Zhang."Fuzzy filter cost-sensitive feature selection with differential evolution", Knowledge-Based Systems, vol. 241 , no. , pp.108259, 9 pages, 2022 (Q1)
  51. Peng Wang, Bing Xue, Jing Liang and Mengjie Zhang."Multi-objective Differential Evolution for Feature Selection in Classification", IEEE Transactions on Cybernetics, pp. 1-15, 2021. (DOI: 10.1109/TCYB.2021.3128540) (Q1)
  52. Qurrat Ul Ain, Bing Xue, Harith Al-Sahaf and Mengjie Zhang. "Automatically Diagnosing Skin Cancers from Multi-Modality Images Using Two-Stage Genetic Programming".  IEEE Transactions on Cybernetics. 2022. 14pp. (Accepted on 04-Jun-2022) (Q1)
  53. Ruwang Jiao, Bing Xue, and Mengjie Zhang. " A Multiform Optimization Framework for Constrained Multi-Objective Optimization".  IEEE Transactions on Cybernetics. 2022. 14pp. DOI: 10.1109/TCYB.2022.3178132 (Q1)
  54. Ying Bi, Bing Xue, and Mengjie Zhang."Multitask Feature Learning as Multiobjective Optimisation: A New Genetic Programming Approach to Image Classification", IEEE Transactions on Cybernetics, DOI: DOI: 10.1109/TCYB.2021.3128540. (Accepted May 2022) (Q1)
  55. Ying Bi, Bing Xue, and Mengjie Zhang. "Instance Selection Based Surrogate-Assisted Genetic Programming for Feature Learning in Image Classification".  IEEE Transactions on Cybernetics. 2021. 14pp. DOI: 10.1109/TCYB.2021.3105696 (Q1)
  56. Wenlong Fu, Bing Xue, Xiaoying Gao, and Mengjie Zhang."Transductive transfer learning based Genetic Programming for balanced and unbalanced document classification using different types of features", Applied Soft Computing, Vol. 103, pp. 107172, 2021 (Q1)
  57. Xiangning Xie, Yuqiao Liu, Yanan Sun, Gary G. Yen, Bing Xue and Mengjie Zhang ."BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search", IEEE Transactions on Evolutionary Computation, 2022. (DOI: 10.1109/TEVC.2022.3147526) (Q1)
  58. Qurrat Ul Ain, Harith Al-Sahaf, Bing Xue and Mengjie Zhang."Genetic Programming for Automatic Skin Cancer Image Classification", Expert Systems with Applications, vol. 197, no. , pp.116680, 15 pages 2022 (Q1)
  59. Ying Bi, Bing Xue, and Mengjie Zhang."Using a small number of training instances in genetic programming for face image classification", Information Sciences, vol. 593, pp. 488-504, 2022 (Q1)
  60. Qinglan Fan, Ying Bi, Bing Xue, and Mengjie Zhang."Genetic programming for feature extraction and construction in image classification", Applied Soft Computing, vol. 118, pp. 108509, 13 pages, 2022 (Q1)
  61. Wenbin Pei, Bing Xue, Lin Shang, and Mengjie Zhang. "High-dimensional Unbalanced Binary Classification by Genetic Programming with Multi-criterion Fitness Evaluation and Selection Evolutionary Computation". Evolutionary Computation. 2021. 25pp.  DOI: 10.1162/evco_a_00304. (Q1)
  62. Fernandez, D., McMillan, L., Arnold, R., Spiess, M. and Liu, I. Goodness-of-Fit and Generalized Estimating Equation Methods for Ordinal Responses based on the Stereotype Model. Stats 5(2), 507-520. DOI: 10.3390/stats5020030, 2022

  63. Ying Bi, Bing Xue, and Mengjie Zhang. A Divide-and-Conquer Genetic Programming Algorithm with Ensembles for Image Classification. IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2021.3082112. 15pp, May 2021.(ARC/ERA Tier A*, Q1, SCI, EI and DBLP indexed, IF = 11.554)

  64. Baligh Al-Helali, Qi Chen, Bing Xue and Mengjie Zhang. "Multi-Tree Genetic Programming with New Operators for Transfer Learning in Symbolic Regression with Incomplete Data". IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2021.3079843, 15pp, May 2021 (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 11.554*)

  65. Bin Wang, Bing Xue, Mengjie Zhang. "Surrogate-assisted Particle Swarm Optimisation for Evolving Variable-length Transferable Blocks for Image Classification". IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2021.3054400. 14pp, Feb 2021 (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 10.451*)

  66. Owen, C. A., Dick, G., & Whigham, P. A. (2020). Characterizing Genetic Programming Error Through Extended Bias and Variance Decomposition. IEEE Transactions on Evolutionary Computation, 24(6), 1164-1176. Dec. 2020 (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 11.554*

  67. Damien O'Neill, Bing Xue, Mengjie Zhang. "Evolutionary Neural Architecture Search for High-Dimensional Skip-Connection Structures on DenseNet Style Networks". IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2021.3083315. May 2021. 15pp. (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 11.554*)

  68. Qi Chen, Bing Xue, Mengjie Zhang. "Preserving Population Diversity Based on Transformed Semantics in Genetic Programming for Symbolic Regression". IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2020.3046569. 15pp. Dec. 2020 (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 11.554*)

  69. Ying Bi, Bing Xue, and Mengjie Zhang. “Genetic Programming-Based Discriminative Feature Learning for Low-Quality Image Classification”. IEEE Transactions on Cybernetics. DOI: 10.1109/tcyb.2021.3049778. 14pp, Feb 2021. (ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF = 11.448)

  70. Wenbin Pei, Bing Xue, Lin Shang, Mengjie Zhang. "Developing Interval-based Cost-sensitive Classifiers by Genetic Programming for Binary High-dimensional Unbalanced Classification". IEEE Computational Intelligence Magazine. Vol. 16, No. 1, pp. 84-98, Feb. 2021(ARC/ERA Tier A, Q1, SCI, EI and DBLP indexed, IF=11.356)

  71. Harith Al-Sahaf, Ausama Al-Sahaf, Bing Xue, Mengjie Zhang. "Automatically Evolving Texture Image Descriptors using the Multi-tree Representation in Genetic Programming using Few Instances". Evolutionary Computation Journal (ECJ, MIT Press). DOI: 10.1162/evco_a_00284. June 2021. 34pp. (ARC/ERA Tier A, Q2, SCI, EI and DBLP indexed)

  72. Anda Li, Bing Xue, Mengjie Zhang. "Improved Binary Particle Swarm Optimization for Feature Selection with New Initialization and Search Space Reduction Strategies". Applied Soft Computing. DOI: https://doi.org/10.1016/j.asoc.2021.107302, July 2021. (Q1, SCI, EI and DBLP indexed, impact factor =6.725)

  73. Valenza-Troubat N, Hilario E, Monanari S, Morrison-Whittle P, Ashton D, Ritchie P, WELLENREUTHER M. "Evaluating new species for aquaculture: A genomic dissection of growth in the New Zealand silver trevally (Pseudocaranx georgianus)". Evolutionary Applications. DOI: https://doi.org/10.1111/eva.13281, 12pp. 2021.

  74. Irving Kate, Wellenreuther Maren, Ritchie Peter A.. "Description of the growth hormone gene of the Australasian snapper, Chrysophrys auratus, and associated intra- and interspecific genetic variation". Journal of Fish Biology. DOI: https://doi.org/10.1111/jfb.14810. 2021, 11pp.

International Conference Papers

  1. Wood, Jesse, Nguyen Hoai, Bach, Killeen, Daniel, Xue, Bing and Zhang, Mengjie. "Automated Fish Classification Using Unprocessed Fatty Acid Chromatographic Data: A Machine Learning Approach". Proceedings of the Australasian Joint Conference on Artificial Intelligence (AJCAI), Springer. December 2022.
  2. Lin, Jiabin, Qi Chen, Bing Xue, and Mengjie Zhang. "AMTEA-Based Multi-task Optimisation for Multi-objective Feature Selection in Classification." In International Conference on the Applications of Evolutionary Computation (Part of EvoStar), pp. 623-639. Cham: Springer Nature Switzerland, 2023.
  3. Sargisson, Finn, Xiaoying Gao, and Bing Xue. "Learning CNN architecture for multi-view text classification using genetic algorithms." In IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1507-1514. IEEE, 2022.
  4. Ain, Qurrat UI, Bing Xue, Harith Al-Sahaf, and Mengjie Zhang. "A Genetic Programming Approach to Automatically Construct Informative Attributes for Mammographic Density Classification." In IEEE International Conference on Data Mining Workshops (ICDMW), pp. 378-387. IEEE, 2022. (Tier A)
  5. Gao, Guanqiang, Bin Xin, Yi Mei, Shengyu Lu, and Shuxin Ding. "A multi-objective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problem." In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1182-1190. 2022. (Tier A)
  6. Owen, Caitlin A., Grant Dick, and Peter A. Whigham. "Towards Explainable AutoML Using Error Decomposition." In Australasian Joint Conference on Artificial Intelligence, pp. 177-190. Cham: Springer International Publishing, 2022.
  7. Masood, Atiya, Gang Chen, Yi Mei, Harith Al-Sahaf, and Mengjie Zhang. "Genetic Programming Hyper-heuristic with Gaussian Process-based Reference Point Adaption for Many-Objective Job Shop Scheduling." In IEEE Congress on Evolutionary Computation (CEC), pp. 1-8. IEEE, 2022.
  8. Zhang, Fangfang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling." In IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1218-1225. IEEE, 2022.
  9. Wang, Alex X., Stefanka S. Chukova, and Binh P. Nguyen. "Implementation and analysis of centroid displacement-based k-nearest neighbors. "In International Conference on Advanced Data Mining and Applications, pp. 431-443. Cham: Springer Nature Switzerland, 2022.
  10. Hamish O'Keeffe, Bing Xue, Mengjie Zhang, Nicola Hawes and Cris Lovell-Smith. “Real-Time Instance Segmentation Techniques using Neural Networks for the Assessment of Green-Lipped Mussels”, International Conference on Image and Vision Computing New Zealand, 2023. (submitted)
  11. Zhao, Junhong, McMillan, Carl, Xue, Bing, Vennell, Ross and Zhang, Mengjie. “Buoy Detection under Extreme Low-light Illumination for Intelligent Mussel Farming”, International Conference on Image and Vision Computing New Zealand, 2023.
  12. McMillan, Carl, Zhao, Junhong, Xue, Bing, Vennell, Ross and Zhang, Mengjie. “Automating Buoy Detection in Mussel Farming Using Deep Learning”，International Conference on Image and Vision Computing New Zealand, 2023.
  13. Zhao, Junhong, Xue, Bing, Vennell, Ross and Zhang, Mengjie, “Large-Scale Mussel Farm Reconstruction with GPS Auxiliary”, International Conference on Image and Vision Computing New Zealand, 2023.
  14. Zeng, Dylon, Ying, Bi, Ivy, Liu, Bing, Xue, Vennell, Ross, and Zhang, Mengjie. “A New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images”, International Conference on Image and Vision Computing New Zealand, 2023. (submitted)
  15. Hoai Bach Nguyen; Bing Xue; Mengjie Zhang. "Automated and Efficient Sparsity-based Feature Selection via a Dual-component Vector". Proceedings of the International Conference on Data Mining (ICDM 2021). IEEE Press. Auckland, New Zealand, 7-10 December, pp 833-842, 2021 (A)
  16. Kaan Demir, Bach Nguyen, Bing Xue, and Mengjie Zhang. "Automated and Efficient Sparsity-based Feature Selection via a Dual-component Vector". Proceedings of the International Conference on Data Mining (ICDM). IEEE Press. Auckland, New Zealand, 7-10 December, pp 823-832, 2021 (A)
  17. Grant Dick. Genetic programming, standardisation, and stochastic gradient descent revisited: initial findings on SRBench. In Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, New York, NY, USA, 2265–2273, 2022.(A)
  18. Grant Dick and Peter A. Whigham. Initialisation and grammar design in grammar-guided evolutionary computation. In Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, New York, NY, USA, 534–537, 2022 (A)
  19. Yunhan Yang, Bing Xue, Linley Jesson and Mengjie Zhang. "Genetic Programming for Symbolic Regression: A Study on Fish Weight Prediction." IEEE Congress on Evolutionary Computation (CEC). Krakow, Poland, 28 June - 1 July 2021, 8pp (A)
  20. Bin Wang, Bing Xue, and Mengjie Zhang. "An Efficient Evolutionary Deep Learning Framework Based on Multi-source Transfer Learning to Evolve Deep Convolutional Neural Networks". Proceedings of 2021 Genetic and Evolutionary Computation Conference (GECCO). ACM Press. July 10-14, 2021, pp 287–288, Online-only Conference. (A)
  21. Bin Wang, Wenbin Pei, Bing Xue, and Mengjie Zhang. "Evolving Local Interpretable Model-agnostic Explanations for Deep Neural Networks in Image Classification". Proceedings of 2021 Genetic and Evolutionary Computation Conference (GECCO). ACM Press. July 10-14, 2021, pp 173–174, Online-only Conference. (A)
  22. Ramya Anasseriyil Viswambaran, Gang Chen, Bing Xue and Mohammad Nekooei. "Two-Stage Genetic Algorithm for Designing Long Short Term Memory (LSTM) Ensembles." IEEE Congress on Evolutionary Computation (CEC). Krakow, Poland, 28 June - 1 July 2021, 8pp (A)
  23. Peng Wang, Bing Xue, Jing Liang and Mengjie Zhang. " A Grid-dominance based Multi-objective Algorithm for Feature Selection in Classification." IEEE Congress on Evolutionary Computation (CEC). Krakow, Poland, 28 June - 1 July 2021, 8pp. (A)
  24. Zichu Yan, Ying Bi, Bing Xue and Mengjie Zhang. "Automatically Extracting Features Using Genetic Programming for Low-Quality Fish Image Classification." IEEE Congress on Evolutionary Computation (CEC). Krakow, Poland, 28 June - 1 July 2021, 8pp (A)
  25. Shaolin Wang, Yi Mei, and Mengjie Zhang. A two-stage multi-objective genetic programming with archive for uncertain capacitated arc routing problem. In Proceedings of the ACM Genetic and Evolutionary Computation Conference (GECCO), pages 287--295. ACM, 2021 (A)
  26. Shaolin Wang, Yi Mei, and Mengjie Zhang. A multi-objective genetic programming approach with self-adaptive alpha dominance to uncertain capacitated arc routing problem. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 636--643. IEEE, 2021 (A)
  27. Yunhan Yang, Bing Xue, Linley Jesson, Matthew Wylie, and Mengjie Zhang. "Deep Convolutional Neural Networks for Fish Weight Prediction from Images". Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE Press. Tauranga, New Zealand, 9-10 December, 2021, (DOI: 10.1109/IVCNZ54163.2021.9653412) (B)
  28. Alistair John McLeay, Abigail McGhie, Dana Briscoe, Ying Bi, Bing Xue, Ross Vennell and Mengjie Zhang. "Deep Convolutional Neural Networks with Transfer Learning for Waterline Detection in Mussel Farms". Proceedings of 2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Press. Orlando, FL, USA, 5-7 December, pp 01-08, 2021 (DOI: 10.1109/SSCI50451.2021.9659987) (B)
  29. Caleb Buchanan, Ying Bi, Bing Xue, Ross Vennell, Simon Childerhouse, Matthew K. Pine, Dana Briscoe, Mengjie Zhang. "Deep Convolutional Neural Networks for Detecting Dolphin Echolocation Clicks". Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ 2021). Tauranga, New Zealand. 9-10 Dec. 2021. (B)
  30. Gonglin Yuan, Bing Xue and Mengjie Zhang. "A Two-Stage Efficient Evolutionary Neural Architecture Search Method for Image Classification". The 18th Pacific Rim International Conference on Artificial Intelligence (PRICAI). Lecture Notes in Computer Science. Vol. 13031, virtually in Hanoi, Vietnam between November 8-12, 2021. pp. 469-484 (B)
  31. Ziyi Wang, Yujie Zhou, Chun Li, Lin Shang and Bing Xue. "MGEoT: A Multi-Grained Ensemble Method for Time Series Classification". The 18th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2021). Lecture Notes in Computer Science. Vol. 13031, Springer, Cham, virtually in Hanoi, Vietnam, 8-12 November 2021. pp. 397-410 (B)
  32. Fergus Currie, Yi Mei, Mengjie Zhang, Linley Jesson, and Maren Wellenreuther. An investigation on multi-objective fish breeding program design. In Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), pages 1--8. IEEE, 2021 (B)
  33. Shaolin Wang, Yi Mei, and Mengjie Zhang. An improved multi-objective genetic programming hyper-heuristic with archive for uncertain capacitated arc routing problem. In Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), pages 1--8. IEEE, 2021 (B)

  34. Zichu Yan, Ying Bi, Bing Xue and Mengjie Zhang. “Automatically Extracting Features Using Genetic Programming for Low-Quality Fish Image Classification”. Proceedings of IEEE Congress on Evolutionary Computation (CEC 2021). Online-only Conference, 28 June - 1 July 2021, 8pp. (ARC/ERA Tier A)

  35. Yunhan Yang, Bing Xue, Linley Jesson and Mengjie Zhang. “Genetic Programming for Symbolic Regression: A Study on Fish Weight Prediction”. Proceedings of IEEE Congress on Evolutionary Computation (CEC 2021). Online-only Conference, 28 June - 1 July 2021, (ARC/ERA Tier A)

  36. Dick Grant, Caitlin A. Owen, and Peter A. Whigham. “Feature standardisation and coefficient optimisation for effective symbolic regression”. Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pp. 306-314, 2020. (ARC/ERA CORE Tier A)

  37. Baligh Al-Helali, Qi Chen, Bing Xue and Mengjie Zhang. “GP with a Hybrid Tree-vector Representation for Instance Selection and Symbolic Regression on Incomplete Data”. Proceedings ofIEEE Congress on Evolutionary Computation (CEC 2021). Krakow, Poland, 28 June - 1 July 2021, (ARC/ERA Tier A)

  38. Arka Ghosh, Bing Xue and Mengjie Zhang. “Binary Differential Evolution based Feature Selection Method with Mutual Information for Imbalanced Classification Problems”. Proceedings ofIEEE Congress on Evolutionary Computation (CEC 2021). Krakow, Poland, 28 June - 1 July 2021 (ARC/ERA Tier A)

  39. Bin Wang, Wenbin Pei, Bing Xue, and Mengjie Zhang. “Evolving Local Interpretable Model-agnostic Explanations for Deep Neural Networks in Image Classification”. Proceedings of 2021 Genetic and Evolutionary Computation Conference (GECCO 2021 Companion). ACM Press. Lille, France July 10-14, 2021 (ARC/ERA CORE Tier A)

  40. Shaolin Wang, Yi Mei, and Mengjie Zhang. “A multi-objective genetic programming approach with self-adaptive alpha dominance to uncertain capacitated arc routing problem”. Proceedings of the IEEE Congress on Evolutionary Computation (CEC). Online-only Conference, 28 June - 1 July 2021, 8pp. (ARC/ERA Tier A)

  41. Shaolin Wang, Yi Mei, and Mengjie Zhang. “A two-stage multi-objective genetic programming with archive for uncertain capacitated arc routing problem”. Proceedings of the ACM Genetic and Evolutionary Computation Conference (GECCO). ACM Press. Lille, Franceïc, July 10-14, 2021, Online-only Conference. (ARC/ERA CORE Tier A)

  42. Webin Pei, Bing Xue, Lin Shang, Mengjie Zhang. "Genetic Programming for Borderline Instance Detection in High-dimensional Unbalanced Classification". Proceedings of 2021 Genetic and Evolutionary Computation Conference (GECCO 2021). Lille, France. 10-14 July 2021. (ARC/ERA CORE Tier A)

  43. Demelza Robinson, Qi Chen, Bing Xue, Michael Price, Paul Hume, Kai Chen, Justin Hodgkiss, and Mengjie Zhang. "Particle Swarm Optimisation for Analysing Time-Dependent Photoluminescence Data". Proceedings of 2021 IEEE Congress on Evolutionary Computation (CEC 2021). Krasow, Poland. 28 June - 01 July 2021. (ARC/ERA Tier A)

  44. Anda Li, Bing Xue, Mengjie Zhang. "A Forward Search Inspired Particle Swarm Optimization Algorithm for Feature Selection in Classification". Proceedings of 2021 IEEE Congress on Evolutionary Computation (CEC 2021). Krasow, Poland. 28 June - 01 July 2021. (ARC/ERA Tier A)

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