| 2025 | AAAI | Learning Robust and Privacy-Preserving Representations via Information Theory. | Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang |
| 2025 | CEC | Learning-based Bi-level Multi-objective Optimization for Container Stowage Planning Problem. | Meihan Guo, Yun Dong |
| 2025 | CVPR | Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations. | Jiate Li, Meng Pang, Yun Dong, Binghui Wang |
| 2025 | GECCO | A Learning-assisted Discrete Differential Evolution for Resource Constrained Project Scheduling. | Yun Dong, Lixin Tang, Weiyan Jia |
| 2025 | GECCO | Multi-objective Evolutionary Algorithm for Production Planning in Cold-Rolling. | Weiyan Jia, Lixin Tang, Yang Yang, Yun Dong, Yanyan Zhang |
| 2025 | ICLR | Provably Robust Explainable Graph Neural Networks against Graph Perturbation Attacks. | Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang |
| 2024 | AAAI | Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks. | Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang |
| 2024 | GECCO | Bi-objective approach for lot-sizing problem in cold rolling production planning. | Weiyan Jia, Lixin Tang, Yang Yang, Yun Dong |
| 2024 | ICML | Graph Neural Network Explanations are Fragile. | Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang |
| 2023 | CVPR | Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural Networks. | Binghui Wang, Meng Pang, Yun Dong |
| 2018 | COMPSAC | Improving Fitness Function for Language Fuzzing with PCFG Model. | Xiaoshan Sun, Yu Fu, Yun Dong, Zhihao Liu, Yang Zhang |
| 2016 | CEC | A contribution-guided discrete differential evolution algorithm for the quadratic multiple knapsack problem. | Xiangling Zhao, Yun Dong, Lixin Tang |
| 2013 | CEC | A pointer-based discrete differential evolution. | Yun Dong, Qingxin Guo, Lixin Tang |