About Me

My name is Kai Sun. I am a postdoctoral associate in the Department of Geography at the University of Buffalo (UB), advised by Dr. Yingjie Hu. My current major research interest is in geospatial artificial intelligence (GeoAI), with a special focus on understanding and extracting location descriptions from disaster related social media messages. CV can be downlaoded here.

Interests
  • Geospatial artificial intelligence
  • Disaster management
  • Natural language processing
Education
  • Ph.D. in GIScience, 2021

    Institute of Geographic Sciences and Natural Resources Research, CAS

  • M.S. in GIScience, 2017

    Institute of Geographic Sciences and Natural Resources Research, CAS

  • B.E. in Remote sensing, 2014

    Wuhan University

Publications

22. Sun, K., Hu, Y., Gaurish L., & Zhou, R. Z. Spatial cross-validation for GeoAI, In: S. Gao,     Y. Hu, and W. Li (Eds), Handbook of Geospatial Artificial Intelligence, Taylor & Francis     Group.
21. Zhu, Y., Sun, K.*, Wang, S., Zhou, C., Lu, F., Lv, H., Qiu, Q., Wang, X.,, & Qi, Y. An     Adaptive Representation Model for Geoscience Knowledge Graphs Considering     Complex Spatiotemporal Features and Relationships. Science China Earth Sciences,     2023.
20. Li, W., Sun, K.*, Zhu, Y., Ding, F., Hu, L., Dai, X., Song, J., Yang, J., Qian, L., & Wang, S.     (2023). GeoTPE: A Neural Network Model for Geographical Topic Phrases Extraction     from Literature Based on BERT Enhanced with Relative Position Embedding. Expert     Systems with Applications, 121077.
19. Sun, K., Hu, Y., Ma, Y., Zhou, R. Z., & Zhu, Y. (2023). Conflating point of interest (POI)     data: A systematic review of matching methods. Computers, Environment and Urban     Systems, 103, 101977.
18. Dai, X., Zhu, Y., Sun, K.*, Zou, Q., Zhao, S., Li, W., Hu, L., & Wang, S. (2023). Examining     the Spatially Varying Relationships between Landslide Susceptibility and Conditioning     Factors Using a Geographical Random Forest Approach: A Case Study in Liangshan,     China. Remote Sensing, 15(6), 1513.
17. Zhou, T., Zhu, Y., Sun, K.*, Chen, J., Wang, S., Zhu, H., & Wang, X. (2022). Variance     Analysis in China’s Coal Mine Accident Studies Based on Data Mining. International     Journal of Environmental Research and Public Health, 19(24), 16582.
16. Wang, S., Yan, X., Zhu, Y., Song, J., Sun, K., Li, W., Hu, L., Qi, Y., & Xu, H. (2022). New     Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method     Based on Remote Sensing Images. Remote Sensing, 14(19), 4725.
15. Wang, S., Zhu, Y., Qi, Y., Hou, Z., Sun, K., Li, W., Hu, L., Yang, J., & Lv, H. (2022). A     unified framework of temporal information expression in geosciences knowledge     system. Geoscience Frontiers, 101465.
14. Wang, S., Zhu, Y., Qian, L., Song, J., Yuan, W., Sun, K., Li, W., & Cheng, Q. (2022). A     novel rapid web investigation method for ecological agriculture patterns in China.     Science of The Total Environment, 156653.
13. Jiang, D., Ma, T., Hao, M., Ding, F., Sun, K., Wang, Q., Kang, T., Wang, D., Zhao, S., Li,     M., Xie, X., Fan, P., Meng, Z., Zhang, S., Qian, Y., Edwards, J., Chen, S., & Li, Y. (2022).     Quantifying risk factors and potential geographic extent of African swine fever     across the world. PloS one, 17(4), e0267128.
12. Qiu, Q., Xie, Z., Wang, S., Zhu, Y., Lv, H., & Sun, K. (2022). ChineseTR: A weakly     supervised toponym recognition architecture based on automatic training data     generator and deep neural network. Transactions in GIS, 26(3), 1256-1279.
11. Zhu, Y., Sun, K.*, Hu, X., Lv, H., Wang, X., Yang, J., Wang, S., Li, W., Song, J., Su, N., &     Mu, X. (2022). Research and practice on the framework for the construction, sharing,     and application of large-scale geoscience knowledge graphs. Journal of Geo-
    information Science
. (in Chinese)
10. Sun, K., Hu, Y., Song, J., & Zhu, Y. (2021). Aligning geographic entities from historical     maps for building knowledge graphs. International Journal of Geographical     Information Science, 35(10), 2078-2107.
9. Li, W., Sun, K., Zhu, Y., Song, J., Yang, J., Qian, L., & Wang, S. (2021). Analyzing the     research evolution in response to COVID-19. ISPRS International Journal of Geo-
    Information
, 10(4), 237-260.
8. Sun, K., Zhu, Y., Pan, P., Hou, Z., Wang, D., Li, W., & Song, J. (2019). Geospatial data     ontology: the semantic foundation of geospatial data integration and sharing. Big     Earth Data, 3(3), 269-296.
7. Sun, K., Zhu, Y., & Song, J. (2019). Progress and challenges on entity alignment of     geographic knowledge bases. ISPRS International Journal of Geo-Information, 8(2),     77-101.
6. Yang, J., Zhu, Y., Song, J., Lu, F., Sun, K., & Li, W. (2018). A Precise Description     Approach on the Result of Automatic Data Matching for Geo-spatial Model. Journal     of Geo-information Science, 20(6), 744-752. (in Chinese)
5. Zhu, Y., Zhu, A. X., Song, J., Yang, J., Feng, M., Sun, K., Zhang J., Hou Z., & Zhao, H.     (2017). Multidimensional and quantitative interlinking approach for linked geospatial     data. International Journal of Digital Earth, 10(9), 923-943.
4. Zhu, Y., Zhu, A. X., Feng, M., Song, J., Zhao, H., Yang, J., Zhang Q., Sun K., Zhang J., &     Yao, L. (2017). A similarity-based automatic data recommendation approach for     geographic models. International Journal of Geographical Information Science,     31(7), 1403-1424.
3. Li, W., Zhu, Y., Song, J., Sun, K., & Yang, J. (2017). Geospatial Data Provenance     Ontology and Its Application in Data Linking. Journal of Geo-information Science,     19(10), 1261-1269. (in Chinese)
2. Sun, K., Zhu, Y., Pan, P., Luo, K., Wang, D., & Hou, Z. (2016). Research on Morphology     Ontology and Its Application in Geospatial Data Discovery. Journal of Geo-
    information Science
, 18(8), 1011-1021. (in Chinese)
1. Sun, K., Zhu, Y., Pan, P., Luo, K., Wang, D., & Hou, Z. (2015). Morphology-ontology of     geospatial data and its application in data discovery. In 2015 23rd International     Conference on Geoinformatics, 1-6.

Presentations

6. Oral presentation (2023): GALLOC: A GeoAnnotator for Labeling LOCation descriptions     from disaster-related text messages, the 4th Spatial Data Science Symposium,     September 5-6, 2023, online.
5. Oral presentation (2023): GALLOC: A GeoAnnotator for Labeling LOCation descriptions     from disaster-related text messages, International Symposium on Location-Based Big     Data and GeoAI, August 12, 2023, online.
4. Oral presentation (2022): Geospatial data ontology: the semantic foundation of     geospatial data integration and sharing, International Training Workshop on     Resource & Environment Scientific Data Sharing and Disaster Risk Reduction     Knowledge Service along the Belt and Road, November 20-24, 2022, online.
3. Oral presentation (2022): Aligning geographic entities from historical maps based on     spatial mapping transformation, the 5th International Conference on Big Earth Data,     November 12-13, 2022, online.
2. Oral presentation (2021): Geospatial data ontology: the semantic foundation of     geospatial data integration and sharing, the 19th International Conference on Spatial     Data Handling and Geographic Intelligence, August 13-14, 2021, online.
1. Oral presentation (2015): Morphology-Ontology of Geospatial Data and its     Application in Data Discovery, the 23rd International Conference on Geoinformatics,     June 19-21, 2015, Wuhan, China.

Awards

4. Excellent Graduate, by Institute of Geographic Sciences and Natural Resources     Research, CAS, 2021
3. Doctor Fellowship, by Institute of Geographic Sciences and Natural Resources     Research, CAS, 2018, 2019
2. Joint Ph.D. Student Scholarship, by China Scholarship Council, 2018
1. Undergraduate Fellowship, by Wuhan University, 2011, 2012