Welcome! My name is Wenwen Xia, I’m currently a Lecture at Soochow University. I obtained my Ph.D. degree at Shanghai Jiao Tong University (SJTU), Bachelor’s degree at Wuhan University, and was a a visiting Ph.D. student at Singapore Management Univeristy (SMU) where I worked with Prof. Yuchen Li. Previously, I spent one year at Microsoft Research Asia (Shanghai) as a research intern. I was a senior machine learning engineer at Ant Group until Dec. 2024.

I work on graph-related learning methods (e.g., graph neural neworks), graph algorithms, large language models, and so on.

Research Interests

Advancing Graph Machine Learning: My first part of research interests focus on graph machine learning, especially graph neural networks (GNNs), e.g., message-passing or Transformer based graph models, with a particular emphasis on graph foundation models. I aim to push the boundaries of GNNs in terms of performance, generalizability, and efficiency, addressing challenges that limit their boarder adaptability across diverse and real-world applications.

Integrating Large Language Models with Graphs: My second part of research interests relates to the synergy between large language models (LLMs) and graph data, striving to equip LLMs with a deep understanding and manipulation of graph structures. This integration also seeks to enhance LLMs’ capabilities in planning, reasoning, and tool utilization, enabling more intelligent and context-aware AI systems.

News

🔥 [2025.01] 2025年课题组有研究生名额，欢迎感兴趣的同学与我邮件联系！

🆕 [2024.11] I’m move to Soochow University, Suzhou, China, as a Lecture (Assistant Professor) from Dec. 2024.

🆕 [2024.05] Our paper “Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning” was accepted by The Web conference 2024, which was held in Singapore.

Publications

• Jun hu*, Wenwen Xia*, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, Jun Zhou. “Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning”. WWW, 2024
• Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li. “Explaining Temporal Graph Models through an Explorer-Navigator Framework”. ICLR, 2023
• Wenwen Xia, Yuchen Li, and Shenghong Li. “On the substructure countability of graph neural networks”. IEEE Transactions on Knowledge and Data Engineering, 2022
• Wenwen Xia, Yuchen Li, Wentian Guo, and Shenghong Li. “Efficient navigation for constrained shortest path with adaptive expansion control”. ICDM, 2022
• Wenwen Xia, Yuchen Li, and Shenghong Li. “Graph neural point process for temporal interaction prediction”. IEEE Transactions on Knowledge and Data Engineering, 2022
• Wenwen Xia, Yuchen Li, Jun Wu, and Shenghong Li. “Deepis: Susceptibility estimation on social networks”. WSDM, 2021
• Wenwen Xia, Yuchen Li, Jianwei Tian, and Shenghong Li. “Forecasting interaction order on temporal graphs”. KDD, 2021
• Wenwen Xia, Fangqi Li, and Shenghong Li. “Gaussian process bandits for online influence maximization”. ICDM Workshop, 2020
• Wenwen Xia, Chong Di, Haonan Guo, Shenghong Li, “Reinforcement learning based stochastic shortest path finding in wireless sensor networks”, IEEE Access, 2019
• Fangqi Li, Chong Di, Wenwen Xia, “On the Submodularity of Diffusion Models: Equivalent Conditions and Applications”

Experiences

• 2023.09-Present, Machine learning engineer, Ant Group
• 2022.03-2023.02, Research Intern, Microsoft Research Asia
• 2021.01-2022.02, Visiting Ph.D. student, SMU

Miscellaneous

If you have any questions about my research work or aim to collaborate with me, feel free to drop an email to me [xiawenwen49 AT gmail DOT com].