Xiaofen Lu (陆晓芬)Research Assistant Professor
Email : luxf@sustech.edu.cn
Office : Room 646B, Southern Building, College of Engineering, SUSTech Campus
Research Interests
My research interesets lie in the areas of Evolutionary Computation and Machine Learning with emphasis on the following topics:
Dynamic Optimization
Co-evolutionary Optimization
Optimization with Costly Function Evaluation
Multi-disciplinary Design Optimization
Interplay between Machine Learning and Evolutionary Computation
Work Experience
2020-Present, Research Assistant Professor, Southern University of Science and Technology
2018-2019, Research Associate, Southern University of Science and Technology
Education
2013-2018, Computer Science, University of Birmingham, Ph.D
2011-2017, Applied Computer Science and Technology, University of Science and Technology of China, Ph.D
2009-2011, Applied Computer Science and Technology, University of Science and Technology of China, Master
2005-2009, Computer Science and Technology, University of Science and Technology of China, Bachelor
Publications
[1] Chang Cao, Xiaofen Lu*, Yachen Li, Junda Zhu, Ke Tang, "The Performance Effect of Model Accuracy on Classification-Assisted Evolutionary Algorithms", Accepted by IEEE Congress on Evolutionary Computation, 2021.
[2] Bo Yuan, Xiaofen Lu, Ke Tang, Xin Yao, "Cooperative Coevolution-based Design Space Exploration for Multi-mode Dataflow Mapping", ACM Transactions on Embedded Computing Systems, 20(3):1-25, 2021.
[3] Xiaofen Lu, Ke Tang, Stefan Menzel, Xin Yao, "A Competitive Co-evolutionary Optimization Method for the Dynamic Vehicle Routing Problem", IEEE Symposium Series on Computational Intelligence, 2020.
[4] Xiaofen Lu, Ke Tang, Stefan Menzel, Xin Yao, "Competitive Coevolution as an Adversarial Approach to Dynamic Optimization", https://arxiv.org/abs/1907.13529
[5] Haohao, Jinyuan Zhang, Xiaofen Lu, AiminZhou, "Binary Relation Learning and Classifying for Preselection in Evolutionary Algorithms", IEEE Transactions on Evolutionary Computation PP(99):1-1, DOI: 10.1109/TEVC.2020.**.
[6] Xiaofen Lu, Tao Sun, and Ke Tang, "Evolutionary optimization with hierarchical surrogates," Swarm and Evolutionary Computation, 47:21-32, 2019.
[7] Xiaofen Lu, Stefan Menzel, Ke Tang, and Xin Yao, "Cooperative co-evolution-based design optimization: A concurrent engineering perspective," IEEE Transactions on Evolutionary Computation, vol. 22, no. 2, pp. 173–188, 2018.
[8] Guiying Li, Chao Qian, Chunhui Jiang, Xiaofen Lu, and Ke Tang, "Optimization based layer-wise magnitudebased pruning for dnn compression." in Proceedings of the 2018 International Joint Conference on Artificial Intelligence (IJCAI'18), 2018, pp. 2383–2389.
[9] Yaoyao He, Rui Liu, Haiyan Li, Shuo Wang, Xiaofen Lu, "Short-term power load probability density forecasting method using kernel-based support vector quantile regression and Copula theory, vol. 185, part 1, pp. 254-266, 2017.
[10] Xiaofen Lu, Ke Tang, and Xin Yao, "Speciated evolutionary algorithm for dynamic constrained optimisation," in Proceedings of the 14th International Conference on Parallel Problem Solving from Nature (PPSN XIV), vol. 9921. Lecture Notes in Computer Science, Springer, 2016, pp.203–213.
[11] Peng Yang, Ke Tang, and Xiaofen Lu, "Improving estimation of distribution algorithm on multimodal problems by detecting promising areas," IEEE Transactions on Cybernetics, vol. 45, no. 8, pp. 1438–1449, 2015.
[12] Xiaofen Lu, Ke Tang, Bernhard Sendhoff, and Xin Yao, "A new self-adaptation scheme for differential evolution," Neurocomputing, vol. 146, pp. 2–16, 2014.
[13] Xiaofen Lu, Ke Tang, Bernhard Sendhoff, and Xin Yao, "A review of concurrent optimisation methods," International Journal of Bio-Inspired Computation, vol. 6, no. 1, pp. 22–31, 2014.
[14] Xiaofen Lu, Stefan Menzel, Ke Tang, and Xin Yao, "The performance effects of interaction frequency in parallel cooperative coevolution," in Proceedings of the 2014 International Conference on Simulated Evolution and Learning (SEAL'14). Springer, 2014, pp. 82–93.
[15] Xiaofen Lu and Ke Tang, "Classification-and regression-assisted differential evolution for computationally expensive problems,"Journal of Computer Science and Technology, vol. 27, no. 5, pp.1024–1034, 2012.
[16]Xiaofen Lu, Ke Tang, and Xin Yao, "Classification-assisted differential evolution for computationally expensive problems," in Proceedings of the 2011 IEEE Congress of Evolutionary Computation (CEC'11). IEEE, 2011, pp. 1986–1993.
[17]Xiaofen Lu, Ke Tang, and Xin Yao? "Evolving neural networks with maximum auc for imbalanced data classification," in Proceedings of the 2010 International Conference on Hybrid Artificial Intelligence Systems (HAIS'10). Springer, 2010, pp. 335–342.
