Luzhi Wang

Luzhi Wang

Hi👋, I’m Luzhi Wang. Now I am an associate professor at Dalian Maritime University. I received my Ph.D. from the Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, under the supervision of Prof. Di Jin. I also supervised by Prof. Shirui Pan (Griffith University) at the TrustAGI Lab. During my Ph.D., I had the opportunity to be a visiting scholar at the NExT++ Research Centre, National University of Singapore, where I was supervised by Prof. Tat-Seng Chua and worked with Prof. Wenjie Wang.

đź“– Educations

  • 2020.09 - 2025.01, Ph.D. Tianjin University (TJU), Tianjin, China.
  • 2023.01 - 2024.01, Visiting Ph.D. Student, National University of Singapore (NUS), Singapore.
  • 2017.09 - 2020.06, M.E. Northeast Normal University (NENU), ChangChun, China.
  • 2013.09 - 2017.06, B.E. Northeast Normal University (NENU), ChangChun, China.

🔥 Recent Publications

  • “Hi-GMAE: Hierarchical Graph Masked Autoencoders”. Chuang Liu, Zelin Yao, Xueqi Ma, Mukun Chen, Luzhi Wang, Jia Wu and Wenbin Hu. WWW 2026.
  • “A Graph Foundation Model for Unified Anomaly Detection”. Renda Han, Xiaobao Wang, Luzhi Wang, Wenxin Zhang, Guangzhen Yao, Hongxiang Liang. WWW 2026.
  • “Cross-Type Semantic Alignment for Multi-Type Anomaly Detection in Heterogeneous Graphs”. Di Jin, Xiao Huang, Xiaobao Wang, Fengyu Yan, Luzhi Wang, Hongxiang Liang. WWW 2026.
  • “From Subtle to Significant: Prompt-Driven Self-Improving Optimization in Test-Time Graph OOD Detection”. Luzhi Wang, Xuanshuo Fu, He Zhang, Chuang Liu, Xiaobao Wang, Hongbo Liu. AAAI 2026, Oral, 4.48%.
  • “Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph classification”. Xiaobao Wang, Ruoxiao Sun, Yujun Zhang, Bingdao Feng, Dongxiao He, Luzhi Wang, Di Jin. NeurIPS 2025.
  • “GOODAT: Towards Test-time Graph Out-of-Distribution Detection”. Luzhi Wang, Dongxiao He, He Zhang, Yixin Liu, Wenjie Wang, Shirui Pan*, Di Jin, Tat-seng Chua. AAAI 2024, Oral, 1.77%.
  • “Contrastive Graph Similarity Networks”. Luzhi Wang, Yizhen Zheng, Di Jin, Fuyi Li, Yongliang Qiao, Shirui Pan*. Tweb 2024.
  • “A Survey on Fairness-aware Recommender System”. Di Jin (Supervisor), Luzhi Wang, He Zhang, Yizhen Zheng, Weiping Ding, Feng Xia, Shirui Pan*. Information Fusion 2023, IF: 18.60.
  • “Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation”. Di Jin (Supervisor), Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan. WWW 2023, Oral.
  • “CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning”. Di Jin (Supervisor), Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan*. IJCAI 2022, Long Oral, 3.75%.

đź’¬ Service Experiences

  • Session Chairs: AAAI-26.
  • Program Committee Members: ICML, ICLR, KDD, NeurIPS, AAAI, IJCAI, MM, WWW and etc.
  • Journal Reviewers: TIP, TNNLS, TWEB, TCSVT, TBigData, Pattern Recognition, Neural Networks, Information Science, KAIS, and etc.

đź’» Intern Experiences

  • Research Intern, Xinrenxinshi Recommendation Lab.
  • Research Intern, Search and Recommendation Technology Department, Meituan Recommendation Lab.

🎖 Certifications and Awards

  • National Scholarship Award.
  • Outstanding Student Scholarship Award.