Evolutionary Computation and Machine Learning Research Group: Publications

Our publications are organised by year, or you can see the full list here.

2026 2025 2024 2023 2022 2021
2020 2019 2018 2017 2016 2015
2014 2013 2012 2011 2010 2009
2008 2007 2006 2005 2004 2003
2002 2001 2000 Older

Our 20 most recent publications:

  • Sun, F., Chen, G., Ma, H., & Hartmann, S. (2026) "Multi-objective IoT service composition with replication using memetic NSGA-II with bottleneck-driven local search". Future Generation Computer Systems, 175. doi:10.1016/j.future.2025.108039
  • Saeed, A., Chen, G., Ma, H., & Fu, Q. (2026) "A genetic algorithm with selective repair method under combined-criteria for deadline-constrained IoT workflow scheduling in Fog–Cloud computing". Future Generation Computer Systems, 175. doi:10.1016/j.future.2025.108050
  • Ai, G., Zuo, X., Chen, G., Zhou, M., Wu, B., & Zhao, X. (2026) "XRL-TO: An explainable reinforcement learning-based approach for bus timetable dynamic optimization". Expert Systems with Applications, 297. doi:10.1016/j.eswa.2025.129271
  • Sun, Y., Gomes, H. M., Lee, A., Gunasekara, N., Weigert Cassales, G., Liu, J. J., . . . Bifet, A. (2026) "Machine Learning for Data Streams with CapyMOA". In Unknown Book (Vol. 16022, pp. 438-443). doi:10.1007/978-3-032-06129-4_27
  • Nguyen, B. H., Nguyen, B. P., Truong, H. V., & Le, V. T. (2026) "Differential Evolutionary for Label Ordering in Multi-label Classification". In Unknown Book (Vol. 16200 LNCS, pp. 84-99). doi:10.1007/978-981-95-3462-3_7
  • Gupta, S., Rezayat, S., Burmester, G., Durak, U., Ma, H., & Hartmann, S. (2026) "From ConOps to an Operational Domain Model: Harnessing LLMs for Conceptual Model Design". In Unknown Book (Vol. 16190 LNCS, pp. 137-156). doi:10.1007/978-3-032-08620-4_9
  • Doherty, W., Lee, A., & Gomes, H. M. (2026) "CLOFAI: A Dataset of Real And Fake Image Classification Tasks for Continual Learning". In Unknown Book (Vol. 2292 CCIS, pp. 348-362). doi:10.1007/978-981-96-6688-1_24
  • Yang, Z., Zuo, X., Huang, H., Chen, G., Zhao, X., & Zhang, T. (2025) "IMPACT: Irregular Multi-Patch Adversarial Composition Based on Two‑Phase Optimization". In Advances in Neural Information Processing Systems.
  • Wood, J., Nguyen, B., Xue, B., Zhang, M., & Killeen, D. (2025) "Hook, line, and spectra: machine learning for fish species identification and body part classification using rapid evaporative ionization mass spectrometry". Intelligent Marine Technology and Systems, 3(1). doi:10.1007/s44295-025-00066-3
  • Palli, A. S., Jaafar, J., Md Saad, M. H., Mokhtar, A. A., Gomes, H. M., Soomro, A. A., & Gilal, A. R. (2025) "Smart adaptive ensemble model for multiclass imbalanced nonstationary data streams". Scientific Reports, 15(1). doi:10.1038/s41598-025-05122-w
  • Chen, Z., Blommaert, J., Mei, Y., Jesson, L., Wellenreuther, M., & Zhang, M. (2025) "Machine learning for genomic prediction of growth traits in aquaculture: a case study of the Australasian snapper (Chrysophrys auratus)". BMC Bioinformatics, 26(1). doi:10.1186/s12859-025-06287-x
  • Bai, M., Gao, Y., Gao, X., & Ma, J. (2025) "Multi-objective genetic programming for binary classification with adaptive thresholds and a generalization-optimizing fitness function". Applied Soft Computing, 185. doi:10.1016/j.asoc.2025.113956
  • Sun, Y., Pfahringer, B., Gomes, H. M., & Bifet, A. (2025) "Dynamic Ensemble Member Selection for Data Stream Classification". In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (pp. 2821-2831). ACM. doi:10.1145/3746252.3761072
  • Neto, R., Alencar, B., Gomes, H. M., Bifet, A., Gama, J., Cassales, G., & Rios, R. (2025) "RMIDDM: an unsupervised and interpretable concept drift detection method for data streams". Data Mining and Knowledge Discovery, 39(6). doi:10.1007/s10618-025-01155-x
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2025) "Meta-Learning Adaptive Loss Functions". __. doi:10.48550/arxiv.2301.13247
  • Maddigan, P., Lensen, A., & Shaw, R. C. (2025) "Re-Identifying Kākā with AI-Automated Video Key Frame Extraction". __. doi:10.48550/arxiv.2510.08775
  • Yang, S., Xu, Z., Zhang, F., Mei, Y., Pan, Q., & Zhang, M. (2025) "Dynamic cooperative scheduling toward distributed and reconfigurable manufacturing via multi-agent deep reinforcement learning". Swarm and Evolutionary Computation, 98. doi:10.1016/j.swevo.2025.102122
  • Xu, H., Xue, B., & Zhang, M. (2025) "Probe Population-Based Initialization and Genetic Pool-Based Reproduction for Evolutionary Bi-Objective Feature Selection". IEEE Transactions on Evolutionary Computation, 29(5), 1849-1863. doi:10.1109/TEVC.2024.3403655
  • Tang, S., Chen, Q., Xue, B., Huang, M., & Zhang, M. (2025) "Regularized multi-task learning with individual-feature-based task correlations for Alzheimer's cognitive score prediction". Computer Methods and Programs in Biomedicine, 270. doi:10.1016/j.cmpb.2025.108954
  • Igual, J., Gomes, H. M., Pfahringer, B., & Bifet, A. (2025) "Linear adaptive filtering for regression in data streams". International Journal of Data Science and Analytics, 20(5), 5017-5032. doi:10.1007/s41060-025-00766-3
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