Ph.D. Student at Xidian University

Zhe Wang

王 哲

Researching knowledge graphs, entity alignment, and graph representation learning — pushing the boundaries of how machines understand and connect structured knowledge.

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Who I Am

A researcher passionate about unlocking the power of structured knowledge through graph learning.

I am a Ph.D. student at the School of Computer Science and Technology, Xidian University, advised by Prof. Ziyu Guan.

My research focuses on knowledge graph representation learning, entity alignment, graph neural networks, and self-supervised learning. I aim to develop scalable and principled methods that enable machines to better understand, align, and reason over complex structured data.

I have published in top-tier venues including NeurIPS, WWW, ICDE, TKDE, and CIKM, with a strong track record in CCF-A conferences and journals.

Quick Info

Degree Ph.D. (硕博连读)
Advisor Prof. Ziyu Guan
Institution Xidian University
Email zwang_01@stu.xidian.edu.cn
GitHub github.com/wzCSDN
7
Publications
4
CCF-A Papers
2
NSFC Projects
Top 5%
WSDM Challenge

Research Interests

Bridging structured knowledge with deep learning to build more intelligent systems.

🔗 Knowledge Graphs & Entity Alignment
🧠 Graph Neural Networks
🎯 Self-Supervised Learning
🌐 Heterogeneous Information Networks
📊 Recommender Systems
📈 Time Series Forecasting

Selected Papers

Recent work in knowledge graphs, graph learning, and recommendation.

NeurIPS 2022 · Spotlight (5.8%)
Self-supervised Heterogeneous Graph Pre-training based on Structural Clustering
Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao*, Cai Xu, Weigang Lu, Jianbin Huang
Proposed SHGP — a self-supervised pre-training approach that requires no positive/negative sample generation. Achieved 98.41% node classification accuracy on MAG dataset. Widely reported by AI media outlets.
WWW 2026 · CCF-A
Aligning Multiple Knowledge Graphs in A Single Pass
Yaming Yang, Zhe Wang, Ziyu Guan*, Wei Zhao, Weigang Lu, Xinyan Huang, Jiangtao Cui, Xiaofei He
First work to study and solve multi-KG (>2) alignment in a single pass. Proposed MultiEA framework with three alignment strategies and high-order similarity inference enhancement. Built two new benchmark datasets.
IEEE TKDE 2025 · CCF-A Journal
Unsupervised Entity Alignment Based on Personalized Discriminative Rooted Tree
Yaming Yang, Zhe Wang, Ziyu Guan, Wei Zhao*, Xinyan Huang, Xiaofei He
Proposed UNEA with parametric tree neighborhood sampling and tree attention aggregation for personalized embeddings. Outperformed many supervised EA baselines in unsupervised settings.
ICDE 2025 · CCF-A
A Translation-based Heterogeneous Graph Neural Network for Multiple Knowledge Graphs Alignment
Yaming Yang, Zhuofeng Luo, Zhe Wang, Weigang Lu, Yiheng Lu, Ziyu Guan*, Wei Zhao, Yuanhai Lv
Proposed KG2HIN that transforms KGs into HINs, combining HGNN aggregation with translation-based KG embedding. Improved M-Hits@1 from 10.25% to 73.05% on DBP-4 with fewer parameters.
NeurIPS 2025 · CCF-A
Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
Yaming Yang, Ziyu Zheng, Weigang Lu, Zhe Wang, Xinyan Huang, Wei Zhao, Ziyu Guan*
Introduced hyper-meta-path concept for heterogeneous hypergraphs. Designed HHNN with attention to learn importance of hyper-meta-paths, improving both performance and interpretability.
CIKM 2025 · CCF-B
Audience-Aware and Self-Adaptive Multi-Interest Modeling for Sharing Rate Prediction in Affiliate Marketing
Zhe Wang, Yaming Yang, Ziyu Guan*, Rui Wang, Yujian Cao, Bin Tong*, Wei Zhao, Hongbo Deng*
Multi-interest modeling for B-end promoter sharing rate prediction. Proposed dynamic routing with interest capsules and dual-channel attention for audience preference integration.
CIKM 2025 · CCF-B
Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing
Zhe Wang, Yaming Yang, Bin Tong, Rui Wang, Ziyu Guan, Wei Zhao*, Hongbo Deng*
Designed propagation scale metric for promoter indirect contributions. Two-stage solution with descendant graph convolution encoding and hypergraph convolution.

Academic Journey

From e-commerce to graph intelligence.

2023.09 — Present
Ph.D. in Computer Science and Technology
Xidian University · Advisor: Prof. Ziyu Guan
2020.09 — 2023.06
M.Eng. in Computer Technology
Xidian University
2016.09 — 2020.06
B.Eng. in E-Commerce
Hefei University of Technology