AG百家乐代理-红桃KAG百家乐娱乐城_百家乐筹码片_新全讯网网址xb112 (中国)·官方网站

師資

EN       返回上一級       師資搜索
宋軒
副教授、研究員
songx@sustech.edu.cn


研究方向:

人工智能,大數據分析,城市計算,智慧城市

教育背景

◆ 2005-2010,博士學位(信號與信息處理) ---北京大學, 北京中國

◆ 2001-2005,學士學位 (信息工程) ---吉林大學, 吉林省, 中國

工作經歷

◆ 2010---2012 博士后研究員, 東京大學,空間信息科學中心,日本

◆ 2012---2015特任助理教授, 東京大學,空間信息科學中心,日本

◆ 2015--201 特任副教授, 東京大學,空間信息科學中心,日本

◆ 2018---2019 主任研究員(終身職位), 日本國家產業技術綜合研究所,人工智能研究中心,日本

◆ 2019年1月---至今 副教授,南方科技大學

榮譽與獎項

◆ 日本卓越研究員,頒發機構:日本文部科學省,2017年。(日本國家最高級別青年人才計劃,當年共計72人入選,唯一的中國籍入選者)

◆ ACM普適計算年會(UbiComp)最佳論文提名獎,頒發機構:國際計算機學會(ACM),2015年。

◆ 北京大學信息學院學術十杰,頒發機構:北京大學,2010年。

代表文章

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

 

(33) 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.

(32) 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.

(31) 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.

(30) 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.

(29)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.

(28)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.

(27) 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.

(26) 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.

(25) 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.

(24) 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.

(23)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.

(22) 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.

(21) 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.

(20) 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)

(19)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.

(18) 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.

(16) 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.

(15) 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.

(14) 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.

(13) 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.

(12) 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.

(11) 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.

(10) 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.

(9) 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.

(8) 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.

(7) 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.

(6) 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.

(5) 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.

(4) 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.

(3) 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.

(2) 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.

(1) 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.


百家乐官网反缆公式| 百家乐德州扑克桌布| 百家乐官网正确的打法| 百家乐官网游戏发展| 百家乐网络公式| 百家乐有什么打法| 伟博娱乐城| 百家乐玩法说明| 贺兰县| 百家乐官网详解| 尊龙百家乐娱乐平台| 大赢家足球即时比分| 百家乐官网机器图片| 百家乐真人游戏| 贵族百家乐官网的玩法技巧和规则 | 皇冠足球網| 百家乐园sun811.com| 百家乐官网tt娱乐城娱乐城| 利都百家乐国际赌场娱乐网规则| 平湖市| sz新全讯网网站112| 百家乐官网开户送10彩金| 威尼斯人娱乐城信誉好吗| 新百家乐官网的玩法技巧和规则 | 玉环县| 新太阳城娱乐城| 风水24山那个排第一| 新葡京百家乐官网现金网| 洛克百家乐的玩法技巧和规则| 百家乐官网庄闲作千| 大发888娱乐场下载 zhidu| 星期八百家乐官网的玩法技巧和规则 | 百家乐官网自动算牌软件| 全讯网hg33.com| 百家乐心态研究| 鹤岗市| 咸丰县| 贝博百家乐的玩法技巧和规则| 百家乐官网事一箩筐的微博| 华亭县| 德州扑克游戏规则|