◎Research Interests
I focus on theoretical and algorithmic research in intelligent optimization and machine learning, with the aim of empowering oil and gas development through AI technologies. Main research interests include:
(1) Intelligent Optimization Theory and Algorithms (e.g., transfer optimization, surrogate models, meta-optimization)
(2) Machine Learning Theory and Algorithms (e.g., physics-informed learning, transfer learning, intelligent agents)
(3) Intelligent Oilfields (e.g., surrogate modeling for numerical simulations, history matching, production optimization)
(4) AI for Science (e.g., PDE Discovery)
◎Research Projects
1. Intelligent Transfer Optimization of Petroleum Reservoir Development, NSFC for Excellent Young Scientists Fund Program (Overseas), PI, 2026-2028.
◎Paper And Publications
1. X. Xue, C. Yang*, L. Feng*, K. Zhang, L. Song, K. C. Tan, “A Scalable Test Problem Generator for Sequential Transfer Optimization,” IEEE Transactions on Cybernetics, vol. 55, no. 5, pp. 2110–2123, 2025.
2. X. Xue, L. Feng, Y. Feng, R. Liu, K. Zhang, K. C. Tan*, “A Theoretical Analysis of Analogy-Based Evolutionary Transfer Optimization,” IEEE Congress on Evolutionary Computation, pp. 1–8, 2025. (Best Paper Award)
3. Y. Lu, K. Zhang*, X. Xue*, L. Zhang, G. Chen, C. Cao, P. Liu, and K. C. Tan, “Multitask Surrogate-Assisted Search with Bayesian Competitive Knowledge Transfer for Expensive Optimization,” IEEE Transactions on Evolutionary Computation, Early Access, 2025.
4. X. Xue, Y. Hu, L. Feng*, K. Zhang, L. Song*, K. C. Tan, “Surrogate-Assisted Search with Competitive Knowledge Transfer for Expensive Optimization,” IEEE Transactions on Evolutionary Computation, vol. 29, no. 6, pp. 2416–2430, 2024.
5. C. Cao, X. Xue*, K. Zhang*, L. Song, L. Zhang, X. Yan, Y. Yang, J. Yao, W. Zhou, and C. Liu, “Competitive Knowledge Transfer-Enhanced Surrogate-Assisted Search for Production Optimization,” SPE Journal, vol. 29, no. 6, pp. 3277–3292, 2024.
6. C. Cao, K. Zhang*, X. Xue*, K. C. Tan, J. Wang, L. Zhang, P. Liu, and X. Yan, “Global and Local Search Experience-Based Evolutionary Sequential Transfer Optimization,” IEEE Transactions on Evolutionary Computation, vol. 29, no. 4, pp. 1269–1283, 2024.
7. X. Xue, L. Feng, C. Yang, S. Liu, L. Song, K. C. Tan*, “Multiobjective Sequential Transfer Optimization: Benchmark Problems and Preliminary Results,” IEEE Congress on Evolutionary Computation, pp. 1–8, 2024.
8. X. Xue, C. Yang*, L. Feng*, K. Zhang, L. Song*, K. C. Tan, “Solution Transfer in Evolutionary Optimization: An Empirical Study on Sequential Transfer,” IEEE Transactions on Evolutionary Computation, vol. 28, no. 6, pp. 1776–1793, 2023.
9. X. Xue, G. Chen, K. Zhang*, L. Zhang, X. Zhao, L. Song, M. Wang, P. Wang, “A Divide-And-Conquer Optimization Paradigm for Waterflooding Production Optimization,” Journal of Petroleum Science and Engineering, vol. 211, pp. 110050, 2022.
10. X. Xue, C. Yang*, Y. Hu, K. Zhang, Y. M. Cheung, L. Song, K. C. Tan, “Evolutionary Sequential Transfer Optimization for Objective-Heterogeneous Problems,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1424–1438, 2021.
11. X. Xue, K. Zhang*, R. Li, L. Zhang, C. Yao, J. Wang, J. Yao, “A Topology-Based Single-Pool Decomposition Framework for Large-Scale Global Optimization,” Applied Soft Computing, vol. 92, pp. 106295, 2020.
12. X. Xue, K. Zhang*, K. C. Tan, L. Feng, J. Wang, G. Chen, X. Zhao, L. Zhang, J. Yao, “Affine Transformation-Enhanced Multifactorial Optimization for Heterogeneous Problems,” IEEE Transactions on Cybernetics, vol. 52, no. 7, pp. 6217–6231, 2020. (ESI Highly Cited Paper) |
