宋文，海洋研究院副教授，硕士生导师，入选山东大学青年学者未来计划。本硕毕业于山东大学控制科学与工程学院，博士毕业于新加坡南洋理工大学计算机科学与工程学院。长期从事深度学习、强化学习、组合优化、时间序列预测等方面的研究，主要研究方向为数据与智能驱动的优化决策技术。主持国自然青年、山东省自然青年、企业委托横向等项目，以第一/通讯作者发表高水平SCI/EI论文30余篇，包括TNNLS、TII、TKDE等中科院1区/CCF-A类期刊论文，ICML、NeurIPS、ICLR、AAAI等CCF-A类/顶级人工智能会议论文，谷歌学术引用1500余次，H-index 21。担任NeurIPS、ICLR、AAAI、IJCAI、KDD等顶级会议的程序委员，以及TPAMI、TNNLS、TCYB等十余个高水平SCI期刊的审稿人。更多信息可见个人主页：https://songwenas12.github.io/。
招生信息：
欢迎有意攻读深度学习、强化学习、最优化方法等方向硕士学位的同学联系我。课题组长期与南洋理工大学、新加坡管理大学、埃因霍温理工大学以及北航、浙大、北理工等国内外知名高校进行合作研究，表现优秀者可推荐读博机会。课题组欢迎计算机、控制、信息、数学等专业的本科生进组参与研究和发表论文，有意向的同学欢迎联系。
部分代表性论文：
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.
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.
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.
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.
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.
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.
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.
Xin Jin, Zhentang Duan, Wen Song* and Qiqiang Li*. Container stacking optimization based on Deep Reinforcement Learning. Engineering Applications of Artificial Intelligence, 2023.
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.
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.
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
Wen Song, Zhiguang Cao, Jie Zhang and Andrew Lim. Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems. Engineering Applications of Artificial Intelligence, 2022.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
