RENHE JIANG (姜 仁河)


Lecturer, Center for Spatial Information Science, The University of Tokyo

jiangrh[*at mark*]csis.u-tokyo.ac.jp


〒277-8568  Room 414, Research Complex Building, Kashiwanoha 5-1-5, Kashiwa, Chiba, Japan [Map] [Access]

〒277-8568 千葉県柏市柏の葉5-1-5 総合研究棟4階414号室 

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

[2024/03/25] 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]

SERVICE

FUNDING

                                          [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.

                                          Digital Science for Post-COVID-19 Society

                                     Project: Multimodal Data Analytics and Integration for Effective COVID-19, Pandemics and Compound Disaster Response and Management

                                     Acknowledgment: This work was supported by JST SICORP Grant Number JPMJSC2104.

                                          Project: Large-Scale Car GPS Trajectory Data Analysis with Deep Learning

                                     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.

    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

                                   Artificial Intelligence Research Center (AIRC), 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

EDUCATION

                                          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

                                          Supervisor: Yoshiharu Ishikawa, Chuan Xiao

                                          Theme: Database, Data Engineering, Data Mining

                                          Thesis: A Study on Mining Density-Based Semantic Trajectory Patterns

                        B.E. (Software Engineering) & B.A. (Japanese), ranking top1.5% (3.85/4.0)