Xun Zhou

Professor

HARBIN INSTITUTE OF TECHNOLOGY, SHENZHEN

Education Background

Educational Background：

  • 2009-2014: University of Minnesota, USA, Computer Science, PhD (Full-time)
  • 2007-2009: Harbin Institute of Technology, Computer Science and Technology, MS (Full-time)
  • 2003-2007: Harbin Institute of Technology, Computer Science and Technology, BS (Full-time)

 

Work Experience：

  • 2023-Present: Harbin Institute of Technology, Shenzhen, School of Computer Science and Technology, Professor, Doctoral Supervisor
  • 2020-2023: Tippie College of Business, University of Iowa, USA, Tenured Associate Professor
  • 2014-2020: Tippie College of Business, University of Iowa, USA, Assistant Professor
Research Field
Spatio-temporal data deep learning, Spatio-temporal large models and foundational pre-training models, graph data mining, Spatio-temporal data generative learning, reinforcement learning and imitation learning，Smart cities and intelligent transportation
Email
xunzhou@slai.edu.cn
Biography

Xun Zhou is a Professor and Doctoral Supervisor at the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen. He received his Ph.D. in Computer Science from the University of Minnesota, USA, and formerly served as a tenured Associate Professor and Henry B. Tippie Research Fellow at the University of Iowa. His main research areas are data mining, machine learning, and spatio-temporal big data intelligence for smart cities. He has published over 120 papers in top-tier conferences and journals including KDD, NeurIPS, AAAI and TKDE, and has led multiple projects funded by the U.S. NSF and national-level grants in China. Collaborations in AI, spatiotemporal data mining, urban intelligence, as well as applications from outstanding students, are welcome.

Academic Publications

Representative Publications ：

1. Zhuoning Yuan, **Xun Zhou**, Tianbao Yang. Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data. In Proc. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), pp. 984-992, August 2018, London, UK. ACM. (DOI: 10.1145/3219819.3219922)

2. Amin Vahedian Khezerlou, **Xun Zhou**, Ling Tong, W. Nick Street, Yanhua Li. Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019, 33(01): 5199-5206. (DOI: 10.1609/aaai.v33i01.33015199)

3. Bang An, **Xun Zhou**, Yongjian Zhong, Tianbao Yang. SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data. In Proc. 37th Neural Information Processing Systems, 2023, 36: 9919-9930. (CCF-A类会议)

4. Bang An, **Xun Zhou**, Zirui Zhou, Ronilo Ragodos, Zenglin Xu and Jun Luo. GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models through Statistically-Guided Geo-Prototyping. In AAAI Conference on Artificial Intelligence (AAAI'25), 2025, 39(11): 11427-11435. (DOI: 10.1609/aaai.v39i11.33243)

5. Amin Vahedian Khezerlou, **Xun Zhou**, Ling Tong, Yanhua Li, Jun Luo. Forecasting Gathering Events through Trajectory Destination Prediction: a Dynamic Hybrid Model. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019, 33(3): 991-1004. (DOI: 10.1109/TKDE.2019.2937082)

6. Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, **Xun Zhou**, Rahul Ghosh and Praveen Ravirathinam. A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity, 2021 IEEE international conference on data mining. IEEE, 2021: 767-776. (DOI: 10.1109/ICDM51629.2021.00088) [Best Paper Award]

7. Menghai Pan, Yanhua Li, **Xun Zhou**, Zhenming Liu, Rui Song, Hui Lu, Jun Luo. Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. Proceedings of the 2019 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2019: 783-791. (DOI 10.1137/1.9781611975673.88) [Best Applied Data Science Paper Award]

8. Huimin Ren, Menghai Pan, Yanhua Li, **Xun Zhou** and Jun Luo. ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification. Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining, 2020: 1306-1315. (DOI: 10.1145/3394486.3403183)

9. Menghai Pan, Weixiao Huang, Yanhua Li, **Xun Zhou** and Jun Luo. xgail: Explainable generative adversarial imitation learning for explainable human decision analysis. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020: 1334-1343. (DOI: 10.1145/3394486.3403186)

10. Yingxue Zhang, Yanhua Li, **Xun Zhou**, Xiangnan Kong and Jun Luo. Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks, Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. 2020: 842-852. (DOI:10.1145/3394486.3403127)

 

   Books/Monographs：

  1.    Encyclopedia of GIS, 2nd Edition. Springer. 2017. Editor-in-Chief.

   

Patents：

  1.    A Method and Device for Training Urban Foundation Models Using Heterogeneous Spatio-Temporal Data. Patent No. ZL202511117196.7, 2025. First Inventor.

   

Research Awards：

  1.   IEEE ICDM Best Paper Award. 2021. IEEE ICDM Organizing Committee. (5/7)
  2.   SIAM Data Mining (SDM) Best Applied Data Science Paper Award. 2019. SDM Organizing Committee. (3/7)
  3.   International Symposium on Spatial and Temporal Databases (SSTD) Best Research Paper Award. 2011. (3/4)
  4.   NDBC Sa Shixuan Outstanding Graduate Thesis Award, China Computer Federation Database Technical Committee, 2009. (1/3)