From here to the world. 从这里走向世界. ここから世界へ.
SHORT BIOGRAPHY
Renhe Jiang is a lecturer at Center for Spatial Information Science, The University of Tokyo. He received his B.E. degree in Software Engineering from Dalian University of Technology in 2012, M.S. degree in Information Science from Nagoya University in 2015, and Ph.D. degree in Civil Engineering from The University of Tokyo in 2019. From 2019 to 2022, he was an assistant professor at Information Technology Center, The University of Tokyo. His research interests include spatiotemporal data mining, time series forecasting, graph neural networks, and general machine learning.
NEWS
[2024/04/17] Two papers have been accepted by IJCAI 2024 Main Track.
[2024/03/25] One co-authored paper has been accepted by IEEE TVT.
[2024/03/22] One paper has been accepted by Artificial Intelligence, "Open-World AI" special issue.
[2024/03/15] One co-authored paper has been accepted by DASFAA 2024 full paper.
[2024/03/10] One co-authored paper has been accepted by ICDE 2024.
[2024/02/28] One co-authored paper has been accepted by IEEE TKDE.
[2023/10/24] Our special issue "Deep Neural Networks for Traffic Forecasting" on Neural Computing and Applications is released.
[2023/09/08] One paper has been accepted as a full paper (oral) by SIGSPATIAL 2023.
[2023/09/01] Our special issue "High-Performance Recommender Systems Based on Spatiotemporal Data" on IEEE TBD is released.
[2023/08/25] One paper has been accepted by IEEE TMC.
[2023/08/21] Our special issue "Advancing Recommendation Systems with Foundation Models" on WWW Journal is released.
[2023/08/05] One long paper and one short paper have been accepted by CIKM 2023.
[2023/06/20] One paper has been accepted by ACM TKDD.
[2023/06/06] One paper has been accepted by ECML PKDD 2023 Applied Data Science Track.
[2023/04/20] One paper has been accepted by IJCAI 2023 Main Track.
[2023/04/13] Invited talk at Temporal Graph Reading Group.
[2023/01/31] Promoted to Lecturer at Center for Spatial Information Science, The University of Tokyo, from April 1st, 2023.
[2023/01/30] Our special issue "Modeling and Understanding of Big HumanMobility Data" on GeoInformatica is released.
[2023/01/26] One paper has been accepted by WWW2023 (TheWebConf2023).
[2022/12/02] Two talks have been accepted by WSDM 2023 Smart City Day.
[2022/11/22] Our special issue "Machine Learning and Location Data" on ACM Transactions on Spatial Algorithms and Systems is released.
[2022/11/19] Two papers have been accepted by AAAI 2023 Main Track.
[2022/11/01] Three papers have been accepted by IEEE BigData 2022 (special session, workshop, poster).
[2022/10/30] One co-authored paper has been accepted by IEEE TKDE.
[2022/08/23] One co-authored paper has been accepted by SIGSPATIAL 2022.
[2022/07/31] One co-authored paper has been accepted by WWW Journal.
[2022/07/22] Our Special Issue on Remote Sensing has been postponed to 15 January 2023.
[2022/06/16] One paper has been accepted by 25th IEEE Intelligent Transportation Systems Conference (ITSC 2022).
[2022/06/15] One paper has been accepted by ECML PKDD 2022 Applied Data Science Track.
[2022/05/24] One survey paper in collaboration with FIU has been accepted by ACM Computing Surveys CSUR.
[2022/04/05] One paper has been accepted by GeoInformatica.
[2022/04/01] One co-authored paper has been accepted by IEEE COMPSAC 2022.
[2022/03/22] One paper has been accepted by IEEE Transactions on Visualization and Computer Graphics (TVCG).
[2022/01/26] One paper (extended abstract) has been accepted by ICDE 2022 TKDE Poster Track.
[2021/12/01] One paper has been accepted by AAAI 2022 Main Track, 1,349 papers out of 9,251 submissions, only 15% acceptance rate.
[2021/11/04] Our paper has been selected as CIKM21 Best Resource Paper Runner Up.
[2021/10/10] One co-authored paper has been accepted by ACM TSAS SI: Understanding the Spread of COVID-19.
[2021/10/04] The dataset called "Yahoo! Bousai Crowd Data" used in our TKDE 2021 paper "DeepCrowd" has been published by Yahoo! Japan Research. [English] [Japanese] [GitHub]
[2021/08/31] One Co-PI research project has been awarded by JST-NSF SICROP Digital Science for Post-COVID-19 Society. [English] [Japanese]
[2021/08/09] Two papers have been accepted by Research Track and Resource Track of CIKM 2021 respectively.
[2021/07/01] Funded Collaborative Research with TOYOTA MOTOR CORPORATION has started.
[2021/06/21] One paper has been accepted by ACM TIST 2021 SI: Deep Learning for Spatio-Temporal Data.
[2021/06/19] One paper has been accepted by ECML PKDD 2021 Applied Data Science Track.
[2021/06/04] Our research has been added as one of Data Platform Initiative Projects by UTokyo Future Society Initiative (UTokyo FSI). [English] [Japanese]
[2021/05/16] One co-authored paper has been accepted by KDD 2021 Research Track.
[2021/04/27] One paper collaborated with Yahoo! Japan Research has been accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
PUBLICATION (* denotes Equal Contribution and # denotes Corresponding Author) [Google Scholar]
[Preprint] [arXiv] Jiawei Wang, Renhe Jiang#, Chuang Yang, Zengqing Wu, Makoto Onizuka, Ryosuke Shibasaki, Chuan Xiao, “Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation”.
[IJCAI24] [arXiv] Haotian Gao, Renhe Jiang#, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song, “Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting”, Proc. of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.
[IJCAI24] Jiewen Deng, Renhe Jiang#, Jiaqi Zhang, Xuan Song#, “Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning”, Proc. of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.
[TVT24] Xiangjie Kong, Hang Lin, Renhe Jiang, Guojiang Shen, “Anomalous Sub-Trajectory Detection with Graph Contrastive Self-Supervised Learning”, IEEE Transactions on Vehicular Technology, 2024.
[AI24] Zhaonan Wang, Renhe Jiang#, Hao Xue, Flora D. Salim, Xuan Song, Ryosuke Shibasaki, Wei Hu, Shaowen Wang, “Learning Spatio-Temporal Dynamics on Mobility Networks for Adaptation to Open-World Events”, Artificial Intelligence (AI), 2024.
[DASFAA24] Lele Zheng, Yang Cao, Renhe Jiang, Kenjiro Taura, Yulong Shen, Sheng Li, Masatoshi Yoshikawa, “Enhancing Privacy of Spatiotemporal Federated Learning against Gradient Inversion Attacks”, Proc. of the 29th International Conference on Database Systems for Advanced Applications (DASFAA), 2024.
[ICDE24] [arXiv] Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng, “Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Anomaly Detection”, Proc. of the 40th IEEE International Conference on Data Engineering (ICDE), 2024.
[TKDE24] [arXiv] Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, Ivor W. Tsang, “Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
[SIGSPATIAL23] [arXiv] Xiaohang Xu, Toyotaro Suzumura, Jiawei Yong, Masatoshi Hanai, Chuang Yang, Hiroki Kanezashi, Renhe Jiang, Shintaro Fukushima, “Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation”, Proc. of 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPAITAL), 2023.
[TMC23] Zekun Cai, Renhe Jiang#, Xinlei Lian, Chuang Yang, Zhaonan Wang, Zipei Fan, Kota Tsubouchi, Hill Hiroki Kobayashi, Xuan Song, Ryosuke Shibasaki, “Forecasting Citywide Crowd Transition Process via Convolutional Recurrent Neural Networks”, IEEE Transactions on Mobile Computing (TMC), 2023.
[CIKM23] [arXiv] Zekun Cai, Renhe Jiang#, Xinyu Yang, Zhaonan Wang, Diansheng Guo#, Hill Hiroki Kobayashi, Xuan Song, Ryosuke Shibasaki, "MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation", Proc. of 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023.
[CIKM23] [arXiv] Hangchen Liu*, Zheng Dong*, Renhe Jiang#, Jiewen Deng, Jinliang Deng, Quanjun Chen, Xuan Song#, "Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting", Proc. of 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023.
[ECMLPKDD23] Yizhuo Wang, Renhe Jiang#, Hangchen Liu, Du Yin, Xuan Song#, "Sequence-Graph Fusion Neural Networks for User Mobile App Behavior Prediction", Proc. of the 27th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2023.
[TKDD23] Jiewen Deng*, Jinliang Deng*, Du Yin, Renhe Jiang#, Xuan Song#, "TTS-Norm: Forecasting Tensor Time Series via Multi-way Normalization", ACM Trans. Knowl. Discov. Data, 2023.
[IJCAI23] [arXiv] Jiewen Deng, Jinliang Deng, Renhe Jiang#, Xuan Song, "Learning Gaussian Mixture Representations for Tensor Time Series Forecasting", Proc. of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
[WSDM23] [Smart City Day Talk] Zhaonan Wang, Renhe Jiang, Zipei Fan, Xuan Song, Ryosuke Shibasaki, "Towards an Event-Aware Urban Mobility Prediction System", Proc. of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023.
[WSDM23] [Smart City Day Talk] Zipei Fan, Renhe Jiang, R. Shibasaki, "Metropolitan-scale Mobility Digital Twin", Proc. of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023.
[WWW23] Renhe Jiang*, Zhaonan Wang*, Yudong Tao*, Chuang Yang, Xuan Song#, Ryosuke Shibasaki, Shu-Ching Chen#, Mei-Ling Shyu, "Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster", Proc. of the ACM Web Conference (WWW), 2023.
[AAAI23] [arXiv] Renhe Jiang*, Zhaonan Wang*, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura, "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting", Proc. of Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.
[AAAI23] [arXiv] Hongjun Wang, Jiyuan Chen, Tong Pan, Zipei Fan, Boyuan Zhang, Renhe Jiang, Lingyu Zhang, Yi Xie, Zhongyi Wang, Xuan Song, "Easy Begun is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout", Proc. of Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.
[BigData22] Renhe Jiang, Zekun Cai, Zhaonan Wang, Chuang Yang, Zipei Fan, Quanjun Chen, Kota Tsubouchi, Xuan Song, Ryosuke Shibasaki, "Yahoo! Bousai Crowd Data: A Large-Scale Crowd Density and Flow Dataset in Tokyo and Osaka", Proc. of 2022 IEEE International Conference on Big Data (BigData), 2022.
[BigData22] Xinchen Hao, Renhe Jiang#, Jiewen Deng, Xuan Song, "The Impact of COVID-19 on Human Mobility: A Case Study on New York", Proc. of 2022 IEEE International Conference on Big Data (BigData), 2022.
[BigData22] Zheng Dong, Quanjun Chen#, Renhe Jiang#, Huanchen Wang, Xuan Song, Hao Tian, "Learning Latent Road Correlations from Trajectories", Proc. of 2022 IEEE International Conference on Big Data (BigData), 2022.
[TKDE22] [arXiv] Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang, “A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
[SIGSPATIAL22] [arXiv] Zipei Fan, Xiaojie Yang, Wei Yuan, Renhe Jiang, Quanjun Chen, Xuan Song, R. Shibasaki, "Online Trajectory Prediction for Metropolitan Scale Mobility Digital Twin", Proc. of 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), 2022.
[ITSC22] Haoyuan Ma, Mintao Zhou, Xiaodong Ouyang, Du Yin, Renhe Jiang#, Xuan Song#, "Forecasting Regional Multimodal Transportation Demand with Graph Neural Networks: An Open Dataset", Proc. of 2022 IEEE International Intelligent Transportation Systems Conference (ITSC), 2022.
[WWWJ22] Yongkang Li, Zipei Fan, Du Yin, Renhe Jiang, Jinliang Deng, Xuan Song, "HMGCL: Heterogeneous Multigraph Contrastive Learning for LBSN Friend Recommendation", World Wide Web (2022).
[ECMLPKDD22] [PDF] [Long Version] Qi Cao, Renhe Jiang#, Chuang Yang, Zipei Fan, Xuan Song, Ryosuke Shibasaki, "MepoGNN: Metapopulation Epidemic Forecasting with Graph Neural Networks", Proc. of the 26th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2022.
[ISPRS22] Puneet Jeph, Hiroshi Takayasu, Tianqi Xia, Hiroshi Kanasugi, Renhe Jiang, Hiroto Mizuseki, Ryosuke Shibasaki, "RAILDASH: A DASHBOARD SYSTEM TO ANALYZE EFFECTS OF EVENTS ON RAILWAY TRAFFIC USING BIG GPS DATA", ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4/W3-2022, 89–96, 2022.
[COMPSAC22] Hangli Ge, Lifeng Lin, Renhe Jiang, Takashi Michikata, Noboru Koshizuka, "Multi-weighted Graphs Learning for Passenger Count Prediction on Railway Network," 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 2022.
[CSUR22] Yudong Tao, Chuang Yang, Tianyi Wang, Erik Coltey, Yanxiu Jin, Yinghao Liu, Renhe Jiang, Zipei Fan, Xuan Song, Ryosuke Shibasaki, Shu-Ching Chen, Mei-Ling Shyu, Steven Luis, "A Survey on Data-Driven COVID-19 and Future Pandemic Management", ACM Computing Surveys (CSUR), 2022.
[ICDE22] Renhe Jiang*, Zekun Cai*, Zhaonan Wang, Chuang Yang, Zipei Fan, Quanjun Chen, Kota Tsubouchi, Xuan Song, Ryosuke Shibasaki. "DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction (Extended abstract)", Proc. of the 38th IEEE International Conference on Data Engineering (ICDE), 2022.
[GeoInformatica22] Du Yin, Renhe Jiang#, Jiewen Deng, Yongkang Li, Yi Xie, Zhongyi Wang, Yifan Zhou, Xuan Song#, Jedi S Shang, "MTMGNN: Multi-Time Multi-Graph Neural Network for Metro Passenger Flow Prediction", GeoInformatica, 2022.
[IEEE22][arXiv] mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
[TVCG22] [arXiv] Chuang Yang*, Zhiwen Zhang*, Zipei Fan*, Renhe Jiang#, Quanjun Chen, Xuan Song#, Ryosuke Shibasaki, “EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control”, IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022.
[TSAS22] Zipei Fan, Chuang Yang, Zhiwen Zhang, Xuan Song, Yinghao Liu, Renhe Jiang, Quanjun Chen, Ryosuke Shibasaki. 2022. Human Mobility-based Individual-level Epidemic Simulation Platform. ACM Trans. Spatial Algorithms Syst (ACM-TSAS). 8, 3, Article 19 (September 2022), 16 pages.
[TIST22] Renhe Jiang, Zekun Cai, Zhaonan Wang, Chuang Yang, Zipei Fan, Quanjun Chen, Xuan Song, Ryosuke Shibasaki. 2022. Predicting Citywide Crowd Dynamics at Big Events: A Deep Learning System. ACM Trans. Intell. Syst. Technol (ACM-TIST). 13, 2, Article 21 (April 2022), 24 pages.
[AAAI22] Zhaonan Wang, Renhe Jiang#, Hao Xue, Flora D. Salim, Xuan Song, Ryosuke Shibasaki, “Event-Aware Multimodal Mobility Nowcasting”, Proc. of Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022.
[CIC21] Yudong Tao, Renhe Jiang, Erik Coltey, Chuang Yang, Xuan Song, Ryosuke Shibasaki, Mei-Ling Shyu, Shu-Ching Chen, “Data-Driven In-Crisis Community Identification for Disaster Response and Management”, Proc. of IEEE 7th International Conference on Collaboration and Internet Computing (CIC), 2021.
[CIKM21] [arXiv] [CIKM21 Best Resource Paper Runner-Up] Renhe Jiang*, Du Yin*, Zhaonan Wang, Yizhuo Wang, Jiewen Deng, Hangchen Liu, Zekun Cai, Jinliang Deng, Xuan Song, Ryosuke Shibasaki, "DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction", Proc. of 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021.
[CIKM21] Zhaonan Wang, Renhe Jiang#, Zekun Cai, Zipei Fan, Xin Liu, Kyoung-Sook Kim, Xuan Song#, Ryosuke Shibasaki, "Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction", Proc. of 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021.
[ECMLPKDD21] [PDF] Renhe Jiang*, Zhaonan Wang*, Zekun Cai, Chuang Yang, Zipei Fan, Tianqi Xia, Go Matsubara, Hiroto Mizuseki, Xuan Song, Ryosuke Shibasaki, "Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19", Proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021.
[KDD21] Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang, "ST-Norm Spatial and Temporal Normalization for Multi-variate Time Series Forecasting", Proc. of 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
[TKDE21] Renhe Jiang*, Zekun Cai*, Zhaonan Wang, Chuang Yang, Zipei Fan, Quanjun Chen, Kota Tsubouchi, Xuan Song, Ryosuke Shibasaki, "DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction." IEEE Transactions on Knowledge and Data Engineering (2021).
[TKDD21] Jinliang Deng, Xiusi Chen, Zipei Fan, Renhe Jiang, Xuan Song, Ivor W. Tsang. 2021. "The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting." ACM Trans. Knowl. Discov. Data 15, 6, Article 103 (May 2021), 25 pages.
[ICDE21] Zhaonan Wang, Tianqi Xia, Renhe Jiang#, Xin Liu, Kyoung-Sook Kim, Xuan Song, Ryosuke Shibasaki, "Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-graph Convolution Network", Proc. of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
[AAAI21] Xiaodan Shi, Xiaowei Shao, Guangming Wu, Haoran Zhang, Zhiling Guo, Renhe Jiang, Ryosuke Shibasaki, “Social-DPF: Socially acceptable distribution prediction of futures”, Proc. of Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021.
[TDS21] Renhe Jiang, Xuan Song, Zipei Fan, Tianqi Xia, Zhaonan Wang, Quanjun Chen, Zekun Cai, Ryosuke Shibasaki, “Transfer Urban Human Mobility via POI Embedding over Multiple Cities”, ACM/IMS Trans. Data Sci. 2, 1, Article 04 (2021).
[Neurocomputing20] Renhe Jiang*, Quanjun Chen*#, Zekun Cai, Zipei Fan, Xuan Song, Kota Tsubouchi, Ryosuke Shibasaki, “Will You Go Where You Search? A Deep Learning Framework for Estimating User Search-and-Go Behavior”, Neurocomputing, 2020.
[SIGSPATIAL20] Quanjun Chen*, Renhe Jiang*, Yang Chuang, Zekun Cai, Zipei Fan, Kota Tsubouchi, Ryosuke Shibasaki, Xuan Song, “DualSIN: Dual Sequential Interaction Network for Human Intentional Mobility Prediction”, Proc. of 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPAITAL), 2020.
[ISPRS20] Satoshi Miyazawa, Xuan Song, Renhe Jiang, Zipei Fan, Ryosuke Shibasaki, T. Sato. (2020). CITY-SCALE HUMAN MOBILITY PREDICTION MODEL BY INTEGRATING GNSS TRAJECTORIES AND SNS DATA USING LONG SHORT-TERM MEMORY. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 87-94, 2020.
[SIGSPATIAL LETTER20] Zipei Fan, Xuan Song, Yinghao Liu, Zhiwen Zhang, Chuang Yang, Quanjun Chen, Renhe Jiang, Ryosuke Shibasaki, "Human Mobility Based Individual-Level Epidemic Simulation Platform", SIGSPATIAL Special 12, 1 (March 2020), 34–40.
[AAAI20] Xiaodan Shi, Xiaowei Shao, Zipei Fan, Renhe Jiang, Haoran Zhang, Zhiling Guo, Guangming Wu, Wei Yuan, Ryosuke Shibasaki, “Multimodal Interaction-Aware Trajectory Prediction in Crowded Space”, Proc. of Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
[UbiComp20] Zipei Fan, Xuan Song, Renhe Jiang, Ryosuke Shibasaki, “Decentralized Attention-based Personalized Human Mobility Prediction”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2020.
[SIGSPATIAL19] Zipei Fan, Xuan Song, Quanjun Chen, Renhe Jiang, Kota Tsubouchi, Ryosuke Shibasaki, “Deep Multiple Instance Learning for Human Trajectory Identification”, Proc. of 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPAITAL), 2019.
[KDD19] Renhe Jiang, Xuan Song, Dou Huang, Xuan Song, Tianqi Xia, Zekun Cai, Zhaonan Wang, Kyoung-Sook Kim, Ryosuke Shibasaki, “DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events”, Proc. of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.
[MIPR19] Dou Huang, Xuan Song, Zipei Fan, Renhe Jiang, Ryosuke Shibasaki, Yu Zhang, Haizhong Wang, Yugo Kato, "A Variational Autoencoder Based Generative Model of Urban Human Mobility", Proc. of 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 2019.
[UbiComp18] Renhe Jiang, Xuan Song, Zipei Fan, Tianqi Xia, Qi Chen, Quanjun Chen, Ryosuke Shibasaki, “Deep ROI-Based Modeling for Urban Human Mobility Prediction”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2018.
[AAAI18] Renhe Jiang, Xuan Song, Zipei Fan, Tianqi Xia, Quanjun Chen, Satoshi Miyazawa, Ryosuke Shibasaki, “DeepUrbanMomentum: An Online Deep-Learning System for Short-Term Urban Mobility Prediction”, Proc. of Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.
[UbiComp18] Zipei Fan, Xuan Song, Tianqi Xia, Renhe Jiang, Ryosuke Shibasaki, Ritsu Sakuramachi, “Online Deep Ensemble Learning for Predicting Citywide Human Mobility”, Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2018.
[MIPR18] Tianqi Xia, Xuan Song, Zipei Fan, Hiroshi Kanasugi, Quanjun Chen, Renhe Jiang, Ryosuke Shibasaki, “DeepRailway: A Deep Learning System for Forecasting Railway Traffic”, Proc. of IEEE 2018 International Conference on Multimedia Information Processing and Retrieval (MIPR), 2018.
[BigData17] Tianqi Xia, Xuan Song, Dou Huang, Satoshi Miyazawa, Zipei Fan, Renhe Jiang, Ryosuke Shibasaki, “Outbound Behavior Analysis Through Social Network Data: a case study of Chinese people in Japan”, Proc. of Big Social Media Data Management and Analysis, IEEE Big Data, 2017.
[TENCON15] Renhe Jiang, Jing Zhao, Tingting Dong, Yoshiharu Ishikawa, Chuan Xiao, Yuya Sasaki, “A Density-based Approach for Mining Movement Patterns from Semantic Trajectories”, IEEE TENCON 2015. IEEE Region 10 Conference, Macau, November 2015.
[DEIM15] 姜 仁河, 趙 菁, 董 テイテイ, 佐々木 勇和, 石川 佳治,「密度に基づく意味的な軌跡パターンの発見」，第7回データ工学と情報マネジメントに関するフォーラム (DEIM 2015), E8-3, 2015年3月.
[DEIM15] 趙 菁, 姜 仁河, 董 テイテイ, 佐々木 勇和, 肖 川, 石川 佳治,「参加型センシングのためのタスク割当手法」，第7回データ工学と情報マネジメントに関するフォーラム (DEIM 2015), C6-5, 2015年3月.
[IPSJ14] 姜 仁河, 杉山 武至, 石川 佳治，「人気経路の推薦のための大規模移動軌跡データ処理」，情報処理学会第76回全国大会, 1N-3, 2014年3月.
SERVICE
AAAI Program Committee Member 2021, 2022, 2023, 2024
IJCAI Program Committee Member 2020, 2022, 2023, 2024
KDD Research Track Program Committee Member 2022, 2023, 2024
WWW (TheWebConf) Program Committee Member 2024
CIKM Program Committee Member 2021, 2022, 2023, 2024
ECML PKDD Program Committee Member 2021, 2022, 2023, 2024
SDM Program Committee Member 2024
PAKDD Program Committee Member 2023, 2024
IEEE BigData Program Committee Member 2022, 2023
Session Chair for IJCAI 2020, IEEE BigData 2022
External Reviewer for IEEE TKDE, IEEE TAI, IEEE TITS, IEEE TIOT, ACM TIST, ACM IMWUT, WWW Journal, Sustainability
Guest Editor for Remote Sensing, ACM TSAS, GeoInformatica, IEEE TBD, WWW Journal, Neural Computing and Applications
FUNDING
2021/04 ~ 2026/03 AIP challenge program, CREST, Japan Science and Technology Agency (JST) [1,000,000 Yen]
[Society 5.0 System Software] Creation of System Software for Society 5.0 by Integrating Fundamental Theories and System Platform Technologies
Project: 実応用に即したプライバシー保護解析とセキュアデータ基盤
Sub-project Name: Graph Neural Networks for Spatiotemporal Data
Acknowledgment: This work was supported by JST CREST Grant Number JPMJCR21M2 including AIP challenge program, Japan.
2021/10 ~ 2025/03 Strategic International Collaborative Research Program (SICORP), Japan Science and Technology Agency (JST) [16,500,000 Yen]
Digital Science for Post-COVID-19 Society
Acknowledgment: This work was supported by JST SICORP Grant Number JPMJSC2104.
2021/07 ~ 2024/03 Funded Collaborative Research with TOYOTA MOTOR CORPORATION [4,300,000 Yen]
Project: Large-Scale Car GPS Trajectory Data Analysis with Deep Learning
2020/04 ~ 2022/03 Grant-in-Aid for Early-Career Scientists (20K19859), Japan Society for the Promotion of Science (JSPS) [4,290,000 Yen]
Project Name: A Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
Acknowledgment: This work was supported by JSPS KAKENHI Grant Number JP20K19859.
2020/04 ~ 2022/03 Strategic International Collaborative Research Program (SICORP), Japan Science and Technology Agency (JST) [825,000 Yen]
Japan(JST)-US(NSF) Joint Research 2019
Project: Multimodal Data Analytics and Integration for Emergency Response and Disaster Management
Acknowledgment: This work was supported by JST SICORP Grant Number JPMJSC2002.
EXPERIENCE
2023/04 ~ present The University of Tokyo, Center for Spatial Information Science, Lecturer
2022/11 ~ 2023/03 Georgia Institute of Technology, Visiting Scholar
2019/04 ~ 2023/03 The University of Tokyo, Information Technology Center, Assistant Professor
2019/04 ~ 2023/03 The University of Tokyo, Center for Spatial Information Science, Visiting Researcher
2018/04 ~ 2019/03 National Institute of Advanced Industrial Science and Technology (AIST)
Artificial Intelligence Research Center (AIRC), Research Assistant
2016/04 ~ 2018/03 The University of Tokyo, School of Engineering, Research Assistant
The University of Tokyo, Center for Spatial Information Science, Research Assistant
The University of Tokyo, Earth Observation Data Integration & Fusion Research Initiative, Research Assistant
2015/04 ~ 2016/03 Accenture Japan, Digital Analytics, Data Analyst
EDUCATION
2016/04 ~ 2019/03 The University of Tokyo, School of Engineering, Doctor of Engineering
Supervisor: Ryosuke Shibasaki, Xuan Song
Theme: Urban Computing, Smart City, Artificial Intelligence, Deep Learning
Dissertation: A Study on Modeling and Analyzing Urban Human Mobility with Deep Learning
2012/10 ~ 2015/03 Nagoya University, School of Information Science, Master of Information Science (Japanese Government MEXT Scholarship)
Supervisor: Yoshiharu Ishikawa, Chuan Xiao
Theme: Database, Data Engineering, Data Mining
Thesis: A Study on Mining Density-Based Semantic Trajectory Patterns
2008/09 ~ 2012/06 Dalian University of Technology, School of Software Engineering, Double Degree
B.E. (Software Engineering) & B.A. (Japanese), ranking top1.5% (3.85/4.0)