Assistant Professor
Xiongnan Jin, PhD, Assistant Professor, Shenzhen University.
He received his PhD from Yonsei University and his Bachelor's degree from Zhejiang University.
Email: xiongnanjin@szu.edu.cn
Research Capabilities and Achievements
Xiongnan Jin received his PhD from Yonsei University (ranked 76th in the QS World University Rankings) in 2019 and his Bachelor's degree from Zhejiang University in 2012. From January 2020, he conducted postdoctoral research at NIST (National Institute of Standards and Technology), and joined the Zhejiang Lab as a Senior Researcher in November 2021. He joined the National Engineering Laboratory for Big Data at Shenzhen University as an Assistant Professor in July 2024. His research interests mainly include artificial intelligence technologies such as knowledge graphs, large-scale models, data mining, and semantic computing. He has been granted 4 foreign invention patents, more than 10 domestic invention patents, and 3 domestic and international software copyrights. He has published over 20 papers in top international journals and conferences such as IEEE TKDE, AAAI, CIKM, and KAIS, which have been cited over 600 times, with an h-index of 11. He serves as a member of the CIPS Language and Knowledge Computing Special Committee and a reviewer for conferences and journals such as KDD, WSDM, KBS, and Information Fusion. Some of the research results are as follows:
1. Xiongnan Jin, Zhilin Wang, Jinpeng Chen, Liu Yang, Byungkook Oh, seung-won hwang, Jianqiang Li. HLMEA: Unsupervised Entity Alignment based on Hybrid Language Models. Proc. of AAAI, 2025. (Accepted, CCF-A conference)
2. Xiongnan Jin, Sangjin Shin, Eunju Jo, Kyong-Ho Lee. Collective keyword query on a spatial knowledge base. IEEE Transactions on Knowledge and Data Engineering, 31(11), 2051-2062, 2018. (CCF-A journal, IF=8.9)
3. Xiongnan Jin, Yooyoung Lee, Jonathan Fiscus, Haiying Guan, Amy N Yates, Andrew Delgado, Daniel F Zhou. MFC-Prov: Media forensics challenge image provenance evaluation and data analysis on large-scale datasets. Neurocomputing, 470, 76-88, 2022. (CAS Q2 journal, IF=6.0)
4. Xiongnan Jin, Sungkwang Eom, Sangjin Shin, Kyong-Ho Lee, Chaoqun Hong. DORIC: discovering topological relations based on spatial link composition. Knowledge and Information Systems (KAIS), 63(10), 2645-2669, 2021. (CCF-B journal, IF=2.7)
5. Xiongnan Jin, Byungkook Oh, Sanghak Lee, Dongho Lee, Kyong-Ho Lee, Liang Chen. Learning region similarity over spatial knowledge graphs with hierarchical types and semantic relations. Proc. of ACM Int'l Conf. on Information and Knowledge Management (CIKM), pp. 669-678, 2019. (CCF-B conference)
Project Status
Leaded 1 national-level project and 1 provincial-level project. Participated in more than 10 domestic and international research projects, including those funded by DARPA (USA), NIST (NIST), NRF (Korea), the National Natural Science Foundation of China (NSFC), and the Ministry of Science and Technology of China.
Projects led include:
1. National Natural Science Foundation of China (NSFC) Youth Project: Research on Few-Sample Graph Fusion Based on Hybrid Spatial Knowledge Representation (Principal Investigator, 62306287, 300,000 RMB, January 2024 - December 2026);
2. Zhejiang Provincial Natural Science Foundation Exploration Project: Research on Representation Learning and Pre-training Models for Knowledge Extraction from Structured Big Data (Principal Investigator, LY23F020012, 100,000 RMB, January 2023 - December 2025).
