My name is Kai Sun. I am a postdoctoral associate in the Department of Geography at the University at 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.
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
21. Sun, K., Zhou, R. Z., Kim, J., and Hu, Y. (2024). PyGRF: An improved Python Geographical Random Forest model and case studies in public health and natural disasters. Transactions in GIS. In press.
20. Li, W., Sun, K.*, Wang, S., Zhu, Y., Dai, X., & Hu, L. (2024). DePNR: A DeBERTa-based deep learning model with complete position embedding for place name recognition from geographical literature. Transactions in GIS. In press.
19. Sun, K., Hu, Y., Gaurish L., & Zhou, R. Z. (2023). Spatial cross-validation for GeoAI, In: S. Gao, Y. Hu, and W. Li (Eds), Handbook of Geospatial Artificial Intelligence, Taylor & Francis Group.
18. Zhu, Y., Sun, K.*, Wang, S., Zhou, C., Lu, F., Lv, H., Qiu, Q., Wang, X.,, & Qi, Y. (2023). An Adaptive Representation Model for Geoscience Knowledge Graphs Considering Complex Spatiotemporal Features and Relationships. Science China Earth Sciences, 66(11), 2563-2578.
17. 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.
16. 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.
15. 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.
14. 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.
13. 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.
12. 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, 25(6), 1215-1227. (in Chinese)
11. Zhu, Y., Sun, K.*, Li, W., Wang, S., Song, J., Cheng, Q., Yang, J., Mu, X., Geng, W., Dai, X. (2021). Comparative Analysis and Enlightenment of Geoscience Knowledge Graphs: A Perspective of Construction Methods and Contents. Geological Journal of China Universities, 29(3): 382-394. (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.
1. GEO 514: GIS and Machine Learning (Spring 2024, at University at Buffalo)
8. Oral presentation (2024): PyGRF: An improved Python Geographical Random Forest model and case studies in public health and natural disasters, 2024 Esri User Conference: Innovations in GI Science, July 15-19, 2024, San Diego, California, USA.
7. Poster presentation (2024): GALLOC: A GeoAnnotator for Labeling LOCation descriptions from disaster-related text messages, 2024 CaGIS + UCGIS Symposium, June 3-6, 2024, Columbus, Ohio, USA.
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.
Peer Reviewer for Academic Journals
5. ICA Scholarship, By International Cartographic Association (ICA), 2024
4. Excellent Graduate, by Institute of Geographic Sciences and Natural Resources Research, 2021
3. Doctoral Fellowship, by Institute of Geographic Sciences and Natural Resources Research, 2018, 2019
2. Joint Ph.D. Student Scholarship, by China Scholarship Council, 2018
1. Undergraduate Fellowship, by Wuhan University, 2011, 2012