Dr. Wen Song
Personal website: https://songwenas12.github.io/
Bachelor, School of Control Science and Engineering, Shandong University, China (2011)
Master, School of Control Science and Engineering, Shandong University, China (2014)
Ph.D., School of Computer Science and Engineering, Nanyang Technological University, Singapore (2018)
Research Fellow, SCALE@NTU Corp Lab, Nanyang Technological University, Singapore (2018-2019)
Associate Research Scientist, Shandong University (2019-)
Artificial Intelligence, Deep Learning, Reinforcement Learning, Multi-agent Systems, Automated Planning, Combinatorial Optimization
1. Wen Song, Donghun Kang, Jie Zhang, Zhiguang Cao, Hui Xi. A Sampling Approach for Proactive Project Scheduling under Generalized Time-dependent Workability Uncertainty. Journal of Artificial Intelligence Research., vol. 64, pp. 385-427, 2019.
2. Luhao Wang, Bingying Zhang, Qiqiang Li, Wen Song and Guanguan Li. Robust distributed optimization for energy dispatch of multi-stakeholdermultiple microgrids under uncertainty. Applied Energy, 2019. (accepted)
3. Sa Gao, Chunyang Chen, Zhenchang Xing, Yukun Ma, Wen Song and Shang-Wei Lin. A neural model for method name generation from functional description. IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2019.
4. 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. (Oral presentation)
5. WenSong, Hui Xi, Donghun Kang and Jie Zhang. An Agent-based Simulation System for Multi-Project Scheduling under Uncertainty. Simulation Modelling Practice and Theory, 86:187-203, 2018.
6. Wen Song, Donghun Kang, Jie Zhang and Hui Xi. A Multi-Unit Combinatorial Auction based Approach for Decentralized Multi-Project Scheduling. Journal of Autonomous Agents and Multiagent Systems (JAAMAS), 31:1548–1577, 2017.
7. Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Proactive Project Scheduling with Time-dependent Workability Uncertainty. 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017. (Oral presentation)
8. Wen Song, Donghun Kang, Jie Zhang and Hui Xi. A Sampling based Approach for Proactive Project Scheduling with Time-dependent Duration Uncertainty (Student Abstract). Thirty-first AAAI Conference on Artificial Intelligence (AAAI), 2017.
9. Wen Song. Project Scheduling in Complex Business Environment (Doctoral Consortium). Thirty-first AAAI Conference on Artificial Intelligence (AAAI), 2017.
10. 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. (Oral presentation)
宋文，计算机科学博士，现任海洋研究院副研究员，并入选山东大学青年学者未来计划。 长期从事人工智能方面的研究工作，在多智能体系统、自动规划与调度、随机优化及风险控制等方面取得了多项代表性成果，并在AAAI、AAMAS、Journal of Artificial Intelligence Research (JAIR)、Autonomous Agents and Multi-agent Systems (JAAMAS)等国际主流人工智能学术会议和期刊上（CCF B类以上）发表多篇长文。担任IJCAI、AAAI等顶级学术会议的程序委员会成员（PC Member），同时担任Journal of Artificial Intelligence Research、IIE Transactions、Computers & Operations Research、Simulation Modelling Practice and Theory、International Transactions in Operational Research等多个国际期刊的审稿人。目前主要的研究方向为基于深度强化学习的复杂动态优化问题求解，以及基于机器视觉和深度学习的海洋生物细胞芯片检测等。
Dr. Wen Song holds PhD degree in Computer Science, and is now an associated research scientist at the Institute of Marine Science and Technology. He has also been elected to the young scholar “Future Plan” program of Shandong University. He has been actively conducting research in the field of Artificial Intelligence (AI), and achieved a number of representative works in multiple sub-domains of AI including Multi-agent Systems, Automated Planning and Scheduling, Stochastic Optimization and Risk Control, etc. He has published a few full papers in top-tier AI conferences and journals, such as AAAI, AAMAS, Journal of Artificial Intelligence Research (JAIR), and Autonomous Agents and Multi-agent Systems (JAAMAS). He served as PC Members for top-tier conferences such as IJCAI and AAAI, and reviewer for many international journals including Journal of Artificial Intelligence Research, IIE Transactions, Computers & Operations Research, Simulation Modelling Practice and Theory, International Transactions in Operational Research, etc. His current research interests are mainly on solving complex dynamic optimization problems based on deep reinforcement learning, and developing marine cell detection algorithms based on computer vision and deep learning.