Hi, I am currently pursuing my Ph.D. degree in the College of Computer Science and Technology at Jilin University (JLU), under the supervision of Prof. You Zhou. Previously, I was a visiting Ph.D. student at Nanyang Technological University (NTU), working with Senior Research Fellow Di Wang, with support from the China Scholarship Council (CSC). I received my B.Sc. from JLU in 2020, advised by Prof. Chunguo Wu.

I have published over ten papers in top-tier conferences and journals, including KDD, AAAI, TNNLS, TEVC, etc. You can find a full list of my publications and CV. Please feel free to contact me if you are interested in collaborating! 🤝🤝🤝

💡 Research Interests

My research interests lie in the emerging field of Learning to Optimize (L2Opt), with a particular focus on leveraging deep neural networks to solve challenging combinatorial optimization problems (COPs). I am also interested in exploring the automatic design of algorithms with the help of large language models (LLMs).

📚 Education

Jilin University, China

Ph.D. in the College of Computer Science and Technology
Sep. 2022 – Present

Nanyang Technological University, Singapore

Visiting Ph.D. Student in the College of Computing and Data Science
Nov. 2023 – Nov. 2024

Jilin University, China

M.Sc. in the College of Computer Science and Technology
Sep. 2020 – Jul. 2022

Jilin University, China

B.Sc. in the College of Computer Science and Technology
Sep. 2016 – Jul. 2020

📑 Selected Publications

★ equal contributions, † corresponding authors

Conference Proceedings

• KDD 2025 X. Wu, D. Wang, C. Wu, Y. Xiao, Y. Zhou, et al., “Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language Models.” paper code
• KDD 2025 W. Song★, X. Wu★, B. Yang, Y. Zhou, C. Wu, et al., “Towards Efficient Few-shot Graph Neural Architecture Search via Partitioning Gradient Contribution.” paper code

  Journal Articles

• TEVC X. Wu, D. Wang, H. Chen, Y. Zhou, C. Wu, et al., “Neural architecture search for text classification with limited computing resources using efficient Cartesian genetic programming,” 2024. paper code
• SWEVO X. Wu, J. Han, D. Wang, Y. Zhou, C. Wu, et al., “Incorporating Surprisingly Popular Algorithm and Euclidean distance-based adaptive topology into PSO,” 2023. paper code
• Electronics Z. Cao★, X. Wu★, C. Wu, Y. Xiao, Y. Zhou, et al., “KeypointNet: An Efficient Deep Learning Model with Multi-View Recognition Capability for Sitting Posture Recognition,” 2025. paper
• Neural Networks Y. Xiao, D. Wang, X. Wu†, Y. Zhou†, et al., “Improving generalization of neural vehicle routing problem solvers through the lens of model architecture,” 2025. paper code

  Pre-prints

• X. Wu, D. Wang, C. Wu, Y. Xiao, Y. Zhou, et al., “Efficient Neural Combinatorial Optimization Solver for the Min-max Heterogeneous Capacitated Vehicle Routing Problem,” arXiv 2507.21386, 2025. paper
• X. Wu, D. Wang, L. Wen, Y. Xiao, Y. Zhou, et al., “Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives,” arXiv 2406.00415, 2024. paper
• Y. Xiao, D. Wang, X. Wu†, Y. Zhou†, et al., “GELD: A Unified Neural Model for Efficiently Solving Traveling Salesman Problems Across Different Scales,” arXiv 2506.06634, 2025. paper code

💼 Services

Conference Reviewer

• ICLR’2025

• AAAI’2026

Journal Reviewer

• IEEE TNNLS

• IEEE TEVC