Rui Cao (曹瑞), Ray

Research_Assistant_Professor @HongKongPolyU

Our Research

We focus on the research of urban informatics and responsible AI applied in the geospatial domain. Our ultimate goal is using GIScience and AI responsibly to help build human-centred smart cities for the benefit of society.

List of Publications


  • Rui Cao, Wei Tu, Jixuan Cai, Tianhong Zhao, Jie Xiao, Jinzhou Cao, Qili Gao, Hanjing Su. Machine learning-based economic development mapping from multi-source open geospatial data. ISPRS Congress 2022. (Accepted)

  • Tianhong Zhao, Zhengdong Huang*, Wei Tu*, Biao He, Rui Cao, Jinzhou Cao, Mingxiao Li. “Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction”, Computers, Environment and Urban Systems, 94, 101776, 2022. [Paper]

  • Dongsheng Chen, Wei Tu*, Rui Cao, Tiezhu Shi, Yatao Zhang, Biao He, Chisheng Wang, Qingquan Li. A hierarchical approach for fine-grained urban villages recognition fusing remote and social sensing data. International Journal of Applied Earth Observation and Geoinformation, 106:102661, 2022. [Paper]

  • Jianghai Liao, Yuanhao Yue, Dejin Zhang, Wei Tu, Rui Cao, Qin Zou, Qingquan Li*. Automatic Tunnel Crack Inspection Using an Efficient Mobile Imaging Module and a Lightweight CNN. IEEE Transactions on Intelligent Transportation Systems, 2022. [Paper]

  • Qing Li#, Rui Cao#, Jiasong Zhu*, Xianxu Hou, Jun Liu, Sen Jia, Qingquan Li, Guoping Qiu. Improving synthetic 3D model-aided indoor image localization via domain adaptation. ISPRS Journal of Photogrammetry and Remote Sensing, 183:66-78, 2022. (Co-first author#) [Paper]

  • Dongsheng Chen, Qingquan Li, Wei Tu*, Rui Cao, Zhengdong Huang, Biao He, Wenxiu Gao. Hierarchical spatial recognition method for urban villages by integrating multi-source geospatial data. Geomatics and Information Science of Wuhan University, 2022. (In Chinese with English abstract) (Accepted)


  • Shuhui Gong, Xiaopeng Mo, Rui Cao*, Yu Liu, Wei Tu, Ruibin Bai. Spatio-temporal parking behaviour forecasting and analysis before and during COVID-19. DeepSpatial '21: 2nd ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems, Virtual Conference, August, 2021. (Oral presentation, Corresponding author*) [Paper] [Arxiv]

  • Jinzhou Cao, Qingquan Li, Wei Tu*, Qili Gao, Rui Cao, Chen Zhong. Resolving urban mobility networks from individual travel graphs using massive-scale mobile phone tracking data. Cities, 110:103077, 2021. [Paper]

  • Qing Li, Jiasong Zhu, Rui Cao, Ke Sun, Jonathan M. Garibaldi, Qingquan Li, Bozhi Liu, and Guoping Qiu*. Relative geometry-aware siamese neural network for 6DOF camera relocalization. Neurocomputing, 426:134-146, 2021. [Paper] [Arxiv]

  • Ruitao Xie, Jingxin Liu, Rui Cao, Connor S. Qiu, Jiang Duan*, Jon Garibaldi, Guoping Qiu. End-to-end fovea localisation in colour fundus images with a hierarchical deep regression network. IEEE Transactions on Medical Imaging, 40(1):116-128, 2021. [Paper]


  • Wei Tu*, Jinzhou Cao, Qili Gao, Rui Cao, Zhixiang Fang, Yang Yue, Qingquan Li. Sensing urban dynamics by fusing multi-sourced spatiotemporal big data. Geomatics and Information Science of Wuhan University, 45(12):1875-1883, 2020. (Review Paper. In Chinese with English abstract) [Paper]

  • Qing Li, Jiasong Zhu*, Jun Liu, Rui Cao, Qingquan Li, Sen Jia, Guoping Qiu. Deep learning based monocular depth prediction: Datasets, methods and applications. arXiv:2011.04123, 2020. (Review Paper) [Arxiv]

  • Jun Liu, Qing Li, Rui Cao, Wenming Tang, and Guoping Qiu*. MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation. ISPRS Journal of Photogrammetry and Remote Sensing, 166:255-267, 2020. [Paper] [Arxiv]

  • Jun Liu, Qing Li, Rui Cao, Wenming Tang, and Guoping Qiu*. A contextual conditional random field network for monocular depth estimation. Image and Vision Computing, 98:103922, 2020. [Paper]

  • Rui Cao, Wei Tu, Cuixin Yang, Qing Li, Jun Liu, Jiasong Zhu, Qian Zhang, Qingquan Li, and Guoping Qiu*. Deep learning-based remote and social sensing data fusion for urban region function recognition. ISPRS Journal of Photogrammetry and Remote Sensing, 163:82-97, 2020. (Featured Article) [Paper]

  • Qing Li, Jiasong Zhu, Jun Liu, Rui Cao, Hao Fu, Jonathan M. Garibaldi, Qingquan Li, Bozhi Liu, and Guoping Qiu*. 3D map-guided single indoor image localization refinement. ISPRS Journal of Photogrammetry and Remote Sensing, 161:13-26, 2020. [Paper]

  • Rui Cao, Qian Zhang, Jiasong Zhu, Qing Li, Qingquan Li, Bozhi Liu, and Guoping Qiu*. Enhancing remote sensing image retrieval using a triplet deep metric learning network. International Journal of Remote Sensing, 41(2):740-751, 2020. [Paper] [Arxiv]


  • Rui Cao, Jiasong Zhu, Qing Li, Qian Zhang, Qingquan Li, Bozhi Liu, and Guoping Qiu*. Learning spatial-aware cross-view embeddings for ground-to-aerial geolocalization. The 10th International Conference on Image and Graphics (ICIG), Beijing, China, August 23-25, 2019. [Paper]

  • Jiasong Zhu, Qing Li*, Rui Cao, Ke Sun, Tao Liu, Jonathan M. Garibaldi, Qingquan Li, Bozhi Liu, and Guoping Qiu. Indoor topological localization using a visual landmark sequence. Remote Sensing, 11(1):73, 2019. [Paper]


  • Rui Cao, Jiasong Zhu, Wei Tu, Qingquan Li, Jinzhou Cao, Bozhi Liu, Qian Zhang, and Guoping Qiu*. Integrating aerial and street view images for urban land use classification. Remote Sensing, 10(10):1553, 2018. [Paper]

  • Rui Cao and Guoping Qiu*. Urban land use classification based on aerial and ground images. The 16th International Conference on Content-Based Multimedia Indexing (CBMI), La Rochelle, France, September 4-6, 2018. (Oral presentation) [Paper]

  • Wei Tu*, Rui Cao, Yang Yue, Baoding Zhou, Qiuping Li, and Qingquan Li. Spatial variations in urban public ridership derived from GPS trajectories and smart card data. Journal of Transport Geography, 69:45–57, 2018. (ESI Highly Cited Paper) [Paper]

2017 and earlier

  • Meng Zhou, Donggen Wang*, Qingquan Li, Yang Yue, Wei Tu, and Rui Cao. Impacts of weather on public transport ridership: results from mining data from different sources. Transportation Research Part C: Emerging Technologies, 75:17–29, 2017. [Paper]

  • Jinzhou Cao, Wei Tu*, Qingquan Li, and Rui Cao. Spatio-temporal analysis of aggregated human activities based on massive mobile phone tracking data. Journal of Geo-information Science, 19(4):467-474, 2017. (In Chinese with English abstract) [Paper]

  • Rui Cao, Wei Tu*, Jinzhou Cao, and Qingquan Li. Exploring the spatiotemporal variation of urban travel characteristics of public transit passengers using smart card data. The 33rd International Geographical Congress (IGC), Beijing, China, August 21-25, 2016. (Abstract, Oral presentation) [Link]

  • Rui Cao, Wei Tu*, Jinzhou Cao, and Qingquan Li. Comparison of urban human movements inferring from multi-source spatial-temporal data. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, XLI-B2: 471–76, 2016. [Paper]

  • Rui Cao, Wei Tu*, Baichong Chao, Nianxue Luo, Meng Zhou, and Qingquan Li. Identification and analysis of home and work regions in the vicinity of metro stations using smart card data. Journal of Geomatics, 41(3):74-78, 2016. (In Chinese with English abstract) [Paper]

  • Jinzhou Cao, Wei Tu*, Qingquan Li, Meng Zhou, and Rui Cao. Exploring the distribution and dynamics of functional regions using mobile phone data and social media data. The 14th International Conference on Computers in Urban Planning and Urban Management (CUPUM), MIT in Cambridge, Massachusetts USA, July 7-10, 2015. [Paper]