🧐 About Me

Hello everyone, welcome to my personal homepage. I am Xie Lindong (Chinese name is 谢淋东), a PhD student at The Hong Kong Polytechnic University, under the supervision of Professor Edward Chung. Before joining PolyU, I completed my Master’s degree at the Southern University of Science and Technology, where I was supervised by Dr. Zhenkun Wang and Dr. Genghui Li.

My main area of research focuses on data-driven optimization (e.g., surrogate-assisted evolutionary optimization and Bayesian optimization) and large language models tailored for addressing expensive black-box optimization problems. If you are interested in my research, I welcome you to reach out for collaboration and communication opportunities. For more information, please visit my ORCID and GitHub.

🔥 News

2024.06: 🎉🎉 The thesis titled ‘Research on Surrogate-Assisted Expensive Optimization Algorithms’ has been awarded the Outstanding Master’s Thesis (Top 1%) by Southern University of Science and Technology.
2023.11: 🎉🎉 Lindong Xie has become a candidate for the exemplary graduate student at Southern University of Science and Technology.
2023.10: 🎉🎉 Lindong Xie has been awarded the National Graduate Scholarship.
2023.06: 🎉🎉 The paper titled ‘Surrogate-Assisted Evolutionary Algorithm with Model and Infill Criterion Auto-Configuration’ has been accepted by IEEE Transactions on Evolutionary Computation.
2023.03: 🎉🎉 The paper titled ‘Evolutionary Algorithm with Individual-Distribution Search Strategy and Regression-Classification Surrogates for Expensive Optimization’ has been accepted by Information Sciences.

📝 Publications

Z. Wang, L. Xie, G. Li, et al. “Customized Evolutionary Expensive Optimization: Efficient Search and Surrogate Strategies for Continuous and Categorical Variables.” IEEE Transactions on Systems Man Cybernetics-Systems (Coming Soon).
Z. Wang, Y. Chen, G. Li, and L. Xie, et al. “Batch Subproblem Coevolution with Gaussian Process-driven Linear Models for Expensive Multi-objective Optimization.” Swarm and Evolutionary Computation 91 (2024): 101700.
L. Xie, G. Li, Z. Wang, L. Cui, and M. Gong, “Surrogate-Assisted Evolutionary Algorithm with Model and Infill Criterion Auto-Configuration,” in IEEE Transactions on Evolutionary Computation, vol. 28, no. 4, pp. 1114-1126, Aug. 2024.
L. Xie, G. Li, K. Lin, and Z. Wang. “Dual-state-driven Evolutionary Optimization for Expensive Optimization Problems with Continuous and Categorical Variables.” 2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2023.
Li G¹, Xie L¹, Z. Wang, et al. Evolutionary Algorithm with Individual-distribution Search Strategy and Regression-classification Surrogates for Expensive Optimization[J]. Information Sciences, 2023, 634: 423-442.

🎖 Selected Honors and Awards

2024.05 Outstanding Master’s Thesis, Southern University of Science and Technology.
2024.05 Outstanding Master’s Graduate, Southern University of Science and Technology.
2023.09 Outstanding Master’s Student, Southern University of Science and Technology.
2023.09 National Scholarship.

📖 Educations

2024.09 - Present, PhD Student, Hong Kong Polytechnic University.
2021.09 - 2024.06, Master, Southern University of Science and Technology.

✒️ Professional Service

Journal Reviewer