教育背景

◆ 2005-2010，博士学位(信号与信息处理) ---北京大学, 北京中国

◆ 2001-2005，学士学位 (信息工程) ---吉林大学, 吉林省, 中国

工作经历

◆ 2010---2012 博士后研究员, 东京大学，空间信息科学中心，日本

◆ 2012---2015特任助理教授, 东京大学，空间信息科学中心，日本

◆ 2015--201 特任副教授, 东京大学，空间信息科学中心，日本

◆ 2018---2019 主任研究员（终身职位）, 日本国家产业技术综合研究所，人工智能研究中心，日本

◆ 2019年1月---至今 副教授，南方科技大学

荣誉与奖项

◆ 日本卓越研究员，颁发机构：日本文部科学省，2017年。（日本国家最高级别青年人才计划，当年共计72人入选，唯一的中国籍入选者）

◆ ACM普适计算年会（UbiComp）最佳论文提名奖，颁发机构：国际计算机学会（ACM），2015年。

◆ 北京大学信息学院学术十杰，颁发机构：北京大学，2010年。

代表性论文

(Authors associated with * are/were doctoral or master student I have supervised)

1. Z. Fan*, X. Song, T. Xia, R. Jiang, R. Shibasaki and R. Sakuramachi, “Online Deep Ensemble Learning for Predicting Citywide Human Mobility”, Proc. of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) (UbiComp 2018), 2018.

2. H. Zhang*, X. Song, T. Xia, M. Yuan, Z. Fan, R. Shibasaki, Y. Liang, “Battery electric vehicles in Japan: Human mobile behavior based adoption potential analysis and policy target response”, Applied Energy, 2018.

3. R. Jiang*, X. Song, Z. Fan, T. Xia, Q. Chen, Q. Chen, and R. Shibasaki, “Deep ROI-Based Modeling for Urban Human Mobility Prediction”, Proc. of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) (UbiComp 2018), 2018.

4. R.Jiang*, X. Song, Z. Fan, T. Xia, Q. Chen, S. Miyazawa, R. Shibasaki, “DeepUrbanMomentum: An Online Deep-Learning System for Short-Term Urban Mobility Prediction”, to appear in Proc. of Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.

5. X. Song, R. Shibasaki, N. Yuan, X. Xie, T. Li, R. Adachi, “DeepMob: Learning Deep Knowledge of Human Emergency Behavior and Mobility from Big and Heterogeneous Data”, ACM Transactions on Information Systems (ACM TOIS), 35(4): 41, 19 pages, 2017.

6. X. Song, Q. Zhang, Y. Sekimoto, R. Shibasaki, N. Yuan, X. Xie, “Prediction and Simulation of Human Mobility Following Natural Disasters”, ACM Transactions on Intelligent Systems and Technology (ACM-TIST), 8(2): 29, 2017.

7. Z. Fan*, X. Song, R. Shibasaki, T. Li,R. Adachi,“CityCoupling: Bridging Intercity Human Mobility”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2016.

8. X. Song, H. Kanasugi, R. Shibasaki, “DeepTransport: Prediction and Simulation of Human Mobility and Transportation Mode at a Citywide Level”, Proc. of 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.

9. Z. Fan*, A. Arai, X. Song, A. Witayangkurn, H. Kanasugi, R. Shibasaki, ”A Collaborative Filtering Approach to Citywide Human Mobility Completion from Sparse Call Records”, Proc. of 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.

10. Q. Chen*, X. Song, H. Yamada, R. Shibasaki, “Learning Deep Representation from Big and Heterogeneous Data for Traffic Accident Inference”, Proc. of Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 338-344, 2016.

11. X. Song, Q. Zhang, Y. Sekimoto, R. Shibasaki, N. Yuan, X. Xie, “A Simulator of Human Emergency Mobility following Disasters: Knowledge Transfer from Big Disaster Data”, Proc. of Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 730-736, 2015.

12. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki,”Object Discovery: Soft Attributed Graph Mining”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 38(3): 532-545, 2016.

13. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki, “From RGB-D Images to RGB Images: Single Labeling for Structural Model Mining”, ACM Transactions on Intelligent Systems and Technology (ACM-TIST), 6(2): 16, 2015.

14. Z. Fan*, X. Song, R. Shibasaki, R. Adachi, “CityMomentum: An Online Approach for Crowd Behavior Prediction at a Citywide Level”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp),pp. 559-569,2015.(Honorable Mention Award)

15. X. Song, Q. Zhang, Y. Sekimoto, R. Shibasaki, “Prediction of Human Emergency Behavior and their Mobility following Large-scale Disaster”, Proc. of 20th SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2014), pp. 5-14, 2014.

16. Z. Fan*, X. Song, R. Shibasaki, “CitySpectrum: A Non-negative Tensor Factorization Approach”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), pp. 213-223, 2014.

17. X. Song, Q. Zhang, Y. Sekimoto, R. Shibasaki, “Intelligent System for Urban Emergency ManagementDuring Large‐scale Disaster”, Proc. of Twenty-Eighth AAAI Conference onArtificial Intelligence (AAAI),pp. 458-464, 2014.

18. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki, “When 3D Reconstruction Meets Ubiquitous RGB-D Images”, Proc. of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 700-707, 2014.

19. Q. Zhang*,X. Song, X. Shao, H. Zhao, R. Shibasaki, “Attributed Graph Mining and Matching: An Attempt to Define and Extract Soft Attributed Patterns”, Proc. of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp.1394-1401, 2014.

20. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki, “Semi-supervised Learning of 3D Object Models and Point Labeling from a Large and Complex Environment”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp. 3082-3089, 2014.

21. X. Song, Q. Zhang, Y. Sekimoto, T. Horanont, S. Ueyama, R. Shibasaki, “Modeling and Probabilistic Reasoning of Population Evacuation During Large-scale Disaster”, Proc. of 19th SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2013),pp. 1231-1239, 2013.

22. X. Song, Q. Zhang, Y. Sekimoto, T. Horanont, S. Ueyama, R. Shibasaki, "Intelligent System for Human Behavior Analysis and Reasoning Following Large-Scale Disasters," IEEE Intelligent Systems, vol. 28, no. 4, pp. 35-42, July-Aug. 2013.

23. X. Song, X. Shao, Q. Zhang, R. Shibasaki, H. Zhao, J. Cui, H. Zha, "A Fully Online and Unsupervised System for Large and High Density Area Surveillance: Tracking, Semantic Scene Learning and Abnormality Detection",ACM Transactions on Intelligent Systems and Technology (ACM-TIST), 4(2): 20, 2013.

24. X. Song, H. Zhao, J. Cui, X. Shao, R. Shibasaki, H. Zha, "An Online System for Multiple Interacting Targets Tracking: Fusion of Laser and Vision, Tracking and Learning",ACM Transactions on Intelligent Systems and Technology (ACM-TIST), 4(1): 18, 2013.

25. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki, “Learning Graph Matching: Oriented to Category Modeling from Cluttered Scenes”,Proc. of IEEE International Conference on Computer Vision (ICCV),pp. 1329-1336, 2013.

26. Q. Zhang*, X. Song, X. Shao, H. Zhao, R. Shibasaki, “Unsupervised 3D Category Discovery and Point Labeling from a Large Urban Environment”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp. 2685-2692, 2013.

27. Q. Zhang*, X. Song,X. Shao, H. Zhao, R. Shibasaki, "Category Modeling from Just a Single Labeling: Use Depth Information to Guide the Learning of 2D Models",Proc. of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR),pp. 193-200, 2013.

28. X. Song, X. Shao, Q. Zhang, R. Shibasaki, H. Zhao, H. Zha, "Laser-based Intelligent Surveillance and Abnormality Detection in Extremely Crowded Scenarios", Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp. 2170-2176, 2012.

29. X. Song, X. Shao, R. Shibasaki, H. Zhao, J. Cui, H. Zha, "A novel laser-based system: Fully online detection of abnormal activity via an unsupervised method", Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp.1317-1322, 2011.

30. X. Song, X. Shao, H. Zhao, J. Cui, R. Shibasaki, H. Zha, "An Online Approach: Learning-Semantic-Scene-by-Tracking and Tracking-by-Learning-Semantic-Scene", Proc. of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp.1652-1659, 2010.

31. X. Song, H. Zhao, J. Cui, X. Shao, R. Shibasaki, H. Zha, "Fusion of Laser and Vision for Multi-target Tracking via On-line Learning", Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp.406-411, 2010.

32. X. Song, J. Cui, H. Zha, H. Zhao, "Vision-based Multiple Interacting Targets Tracking via On-line Supervised Learning", Proc. of European Conference on Computer Vision (ECCV), pp.642-655, 2008.

33. X. Song, J. Cui, X. Wang, H. Zhao, H. Zha, "Tracking Interacting Targets with Laser Scanner via On-line Supervised Learning", Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp.2271-2276, 2008.