Outline

Faculty Members

SONG Xuan

(Associate Professor/Division of Environmental Studies)

Department of Socio-Cultural Environmental Studies//Artificial Intelligence and Big Data

Career Summary

2010: Doctoral Degree of Engineering (Peking University,China)
2010: Project Researcher, Center for Spatial Information Science, The University of Tokyo, Japan.
2012: Project Assistant Professor, Center for Spatial Information Science, The University of Tokyo, Japan.
2015: Project Associate Professor, Center for Spatial Information Science, The University of Tokyo, Japan.
2017: Excellent Young Researcher of Japan MEXT.
2018: Senior Researcher (With Tenure), AI Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Japan.

Educational Activities

Graduate school: Spatial Information Analysis
Graduate school:Spatial Information Analysis Exercises

Research Activities

With the rapid population growth and urbanization, smart cities and urban computing are emerging as the priority for research and development across the world. Big human mobility and urban sensing data are increasingly produced by the sensors of Internet of Things (IoT) via emerging communication technologies. The effective use of these big data can certainly help create smart cities where infrastructure and resources are used in a more efficient manner. Motivated by the opportunities of building more intelligent cities, my research will aim to unlock the power of knowledge from big and heterogeneous data collected in urban spaces and apply this powerful information to solve major issues our cities face today. More specifically, my research is aim to develop a novel big data and deep learning platform called UrbanBrain (as shown in below Figure) that will enable urban intelligence with big data and perform the next-generation urban management. The proposed research will develop advanced data analytics and deep models to understand human mobility, urban dynamics, and human transportation behavior to tackle the major challenges that cities face, e.g. natural disasters and emergency events, air pollution, increasing energy consumption and traffic congestion. My research will also implement several real-world intelligent systems (e.g. DeepDisaster, DeepMob, DeepTransport, and etc.) to perform more effective emergency response and disaster management, transportation scheduling, and urban planning.

Literature

(1) 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.
(2) 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.
(3) X. Song, X. Shao, Q. Zhang, R. Shibasaki, H. Zhao, H. Zha, "A Novel Dynamic Model for Multiple Pedestrians Tracking in Extremely Crowded Scenarios", Information Fusion, Elsevier, 14(3), pp. 301-310, 2013.
(4) 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.
(5) 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.

Other Activities

(1) Guest Editor, IEEE Transactions on Multimedia,(2018)
(2) Guest Editor, World Wide Web Journal (WWW Journal), (2018)
(3) Associate Editor, IEEE Intelligent Transportation Systems Conference, (2018)
(4) Associate Editor, Big Data Journal, (2014-2015)
(5) Area Chair, IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR),(2018)

URL

https://shiba.iis.u-tokyo.ac.jp/song/