I am currently an Associate Professor with the Institute of Marine Science and Technology, Shandong University, China. Before joining Shandong University, I was a Research Fellow with the Singtel-NTU Corp Lab (SCALE@NTU) in Nanyang Technological University, Singapore. I received my PhD degree from School of Computer Science and Engineering, Nanyang Technological University (NTU), in 2018. I received my bachelor’s and master’s degree from Shandong University, in 2011 and 2014, respectively. 

My research mainly lies in the intersection of Artificial Intelligence and Operations Research. I am particularly interested in learning to optimize, which aims to leverage Deep Learning and Reinforcement Learning to solve challenging optimization problems in various practical domains such as transportation, manufacturing, and maritime logistics.

More information can be found at my personal homepage: https://songwenas12.github.io/.

Selected Publications:

1. Wen Song, Nan Mi, Qiqiang Li, Jing Zhuang and Zhiguang Cao. Stochastic Economic Lot Scheduling via Self-Attention based Deep Reinforcement Learning. IEEE Transactions on Automation Science and Engineering (TASE), 2023.

2. Jingwen Li, Yining Ma, Zhiguang Cao, Yaoxin Wu, Wen Song*, Jie Zhang and Yeow Meng Che. Learning Feature Embedding Refiner for Solving Vehicle Routing Problems. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

3. Jianan Zhou, Yaoxin Wu*, Zhiguang Cao, Wen Song*, Jie Zhang and Zhenghua Chen. Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.

4. Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Wen Song*, and Jie Zhang. Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift. Advances in Neural Information Processing Systems (NeurIPS), 2023.

5. Jianan Zhou, Yaoxin Wu*, Wen Song*, Zhiguang Cao, and Jie Zhang. Towards Omni-generalizable Neural Methods for Vehicle Routing Problems. International Conference on Machine Learning (ICML), 2023.

6. Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song*, Zhang Le, Zhiguang Cao, Jie Zhang. A review on learning to solve combinatorial optimisation problems in manufacturing. IET Collaborative Intelligent Manufacturing, 2023.

7. Wen Song, Yi Liu, Zhiguang Cao, Yaoxin Wu and Qiqiang li. Instance-specific algorithm configuration via unsupervised deep graph clustering. Engineering Applications of Artificial Intelligence, 2023.

8. Xin Jin, Zhentang Duan, Wen Song* and Qiqiang Li*. Container stacking optimization based on Deep Reinforcement Learning. Engineering Applications of Artificial Intelligence, 2023.

9. Wen Song, Xinyang Chen, Qiqiang Li and Zhiguang Cao. Flexible Job Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning. IEEE Transactions on Industrial Informatics (TII), 2022.

10. Rongkai Zhang, Cong Zhang, Zhiguang Cao, Wen Song*, Puay Siew Tan, Jie Zhang, Bihan Wen and Justin Dauwels. Learning to Solve Multiple-TSP with Time Window and Rejection via Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems (TITS), 2022.
    

11. Zhizheng Zhang, Wen Song* and Qiqiang Li*. Dual Aspect Self-Attention based on Transformer for Remaining Useful Life Prediction. IEEE Transactions on Instrumentation and Measurement (TIM), 2022

12. Wen Song, Zhiguang Cao, Jie Zhang and Andrew Lim. Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems. Engineering Applications of Artificial Intelligence, 2022.

13. Zhonghao Zhang, Qiqiang Li*, Wen Song*, Pengfei Wei, Jing Guo. A novel concavity based method for automatic segmentation of touching cells in microfluidic chips. Expert Systems with Applications, 2022.

14. Yaoxin Wu, Wen Song(#), Zhiguang Cao, and Jie Zhang. Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs. International Conference on Learning Representations (ICLR), 2022.

15. Yaoxin Wu, Wen Song*, Zhiguang Cao*, Jie Zhang and Andrew Lim. Learning Improvement Heuristics for Solving Routing Problems. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

16. Zhiguang Cao, Tingbo Liao, Wen Song*, Zhenghua Chen and Chongshou Li. Detecting the shuttlecock for a badminton robot: A YOLO based approach. Expert Systems with Applications, 2021.

17. Yaoxin Wu, Wen Song*, Zhiguang Cao, and Jie Zhang. Learning Large Neighborhood Search Policy for Integer Programming. Advances in Neural Information Processing Systems (NeurIPS), 2021.

18. Yining Ma, Jingwen Li, Zhiguang Cao*, Wen Song*, Le Zhang, Zhenghua Chen, and Jing Tang. Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer. Advances in Neural Information Processing Systems (NeurIPS), 2021.

19. Liang Xin(#), Wen Song(#), Zhiguang Cao and Jie Zhang. Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems. 35th AAAI Conference on Artificial Intelligence (AAAI), 2021.

20. Liang Xin, Wen Song*, Zhiguang Cao and Jie Zhang. Step-wise Deep Learning Models for Solving Routing Problems. IEEE Transactions on Industrial Informatics (TII), 2020.

21. Cong Zhang(#), Wen Song(#), Zhiguang Cao, Jie Zhang, Puay Siew Tan and Chi Xu. Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2020.

22. Wen Song, Donghun Kang, Jie Zhang, Zhiguang Cao and Hui Xi. A Sampling Approach for Proactive Project Scheduling under Generalized Time-dependent Workability Uncertainty. Journal of Artificial Intelligence Research (JAIR), 64:385-427, 2019.

23. Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Risk-aware Proactive Scheduling via Conditional Value-at-Risk. Thirty-second AAAI Conference on Artificial Intelligence (AAAI), 2018.

24. Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Decentralized Multi-Project Scheduling via Multi-Unit Combinatorial Auction. 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2016.