I am an Assistant Professor at Nanjing University (QS 90), China, and a DAAD AInet Fellow, Germany.
I previously worked as a Research Fellow at Nanyang Technological University, Singapore, and as a researcher at Leibniz University Hannover and the L3S Research Center, Germany.
I received my Ph.D. from Swinburne University of Technology, Australia, and my bachelor's degree from Wuhan University, China.
My research focuses on databases and graph databases, with a current interest in the intersection of database systems and large language models (LLMs).
My work has appeared in leading database conferences, including SIGMOD and ICDE, and other major venues.
I am currently looking for motivated PhD, master's, and undergraduate students who are passionate about research. If you are interested in working with me, please feel free to get in touch.
2025.11 - present. Assistant Professor Nanjing University, China
2023.08 - 2025.11 Research Fellow Nanyang Technological University, Singapore
2022.09 - 2023.08 Senior Researcher L3S Research Center, Leibniz University Hannover, Germany
Research Projects
National Natural Science Foundation of China (NSFC), Young Scientists Fund (Category C), PI.
Natural Science Foundation of Jiangsu Province, Youth Fund, PI.
State Key Laboratory for Novel Software Technology, Overseas Open Research Projects, PI.
Ministry of Education (MOE), Singapore, Academic Research Fund (AcRF) Tier 1, Co-PI.
Ministry of Education, China, Pilot Project for Disciplinary Breakthroughs, Core team member.
Selected Publications
ICDE 2025 (CORE A*, CCF A) Xiaofan Li, Rui Zhou, Lu Chen, and Chengfei Liu. 2025. Clique Comparator: A Fundamental Operator for Finding a Concise Clique Summary. In 2025 IEEE International Conference on Data Engineering (ICDE). IEEE.
ICDE 2024 (CORE A*, CCF A) Xiaofan Li, Gao Cong, and Rui Zhou. 2024. Quantum Algorithms for the Maximum K-Plex Problem. In 2024 IEEE International Conference on Data Engineering (ICDE). IEEE, 2435-2448.
WWW 2024 (CORE A*, CCF A)
Wei Zhang, Xiaofan Li, and Wolfgang Nejdl. 2024. Adversarial Mask Explainer for Graph Neural Networks. In 2024 ACM The Web Conference (WWW). ACM, 861-869.
SIGMOD 2022 (CORE A*, CCF A) Xiaofan Li, Rui Zhou, Lu Chen, Chengfei Liu, Qiang He, and Yun Yang. 2022. One Set to Cover All Maximal Cliques Approximately. In 2022 ACM Special Interest Group on Management of Data (SIGMOD). ACM, 2006-2019.
ICDE 2021 (CORE A*, CCF A) Xiaofan Li, Rui Zhou, Lu Chen, Yong Zhang, Chengfei Liu, Qiang He, and Yun Yang. 2021. Finding a Summary for All Maximal Cliques. In 2021 IEEE International Conference on Data Engineering (ICDE). IEEE, 1344-1355.
Teaching
“I couldn’t do it. I couldn’t reduce it to the freshman level. That means we don’t really understand it.”