Welcome to my Homepage!

I am a Postdoctoral Fellow at the Hong Kong University of Science and Technology (HKUST), working in the Department of Civil and Environmental Engineering. I received my Ph.D. in Computer Science from Xidian University in 2025. My research focuses on semi-supervised learning and graph neural networks, with publications in top-tier venues including NeurIPS, SIGKDD, AAAI, ICDE, WWW, and IEEE TKDE. I also serve as a reviewer for leading academic journals and conferences, and as Session Chair for WWW 2026 and AAAI 2026.

News

2026.08 👨‍🏫👨‍🏫 I will be joining the School of Computer Science at Northwestern University (China) as a Professor!
2026.01 🎉🎉 Three papers accepted at WWW 2026 (3 Oral) as Oral presentation!
2025.12 🎉🎉 One paper accepted at AAAI 2026 (Oral) as Oral presentation!
2025.09 🎉🎉 One paper accepted at NeurIPS 2025!
2025.07 🎉🎉 Two paper accepted at SIGKDD 2025!
2025.06 🎓🎓 Successfully defended my Ph.D. thesis at Xidian University!
2025.02 🎉🎉 Two paper accepted at ICDE 2025!
2024.12 🎉🎉 One paper accepted at AAAI 2025!
2024.08 🏆🏆 Received ACM SIGKDD Student Travel Award!
2024.07 🏆🏆 Received the National Scholarship for Postgraduates!
2024.05 🎉🎉 One paper accepted at SIGKDD 2024!
2024.02 🎉🎉 One paper accepted at TKDE 2024!
2023.12 🎉🎉 One paper accepted at AAAI 2024!

Experience

Hong Kong University of Science and Technology
2025.09 - Present
Postdoctoral Fellow at Department of Civil and Environmental Engineering
Supervisor: Prof. Hong K. Lo.

Xidian University
2022.03 - 2025.06
Ph.D. in Computer Science, advised by Prof. Ziyu Guan
School of Computer Science and Technology.

Hong Kong University of Science and Technology
2025.04 - 2025.06
Visiting Student at Department of Civil and Environmental Engineering
Supervisor: Prof. Hong K. Lo.

JD EXPLORE ACADEMY
2021.01 - 2021.12
Algorithm Engineer Intern
Supervisor: Prof. Dacheng Tao.

Xidian University
2019.09 - 2021.12
M.S. in Computer Science, advised by Prof. Wei Zhao
School of Computer Science and Technology.

Anhui Polytechnic University
2015.09 - 2019.07
B.S. in Internet of Things
School of Computer and Information.

Publications

(* equal contribution · † corresponding author · first author)

MessageShift: Fine-Grained Data Augmentation for Graph Neural Networks
Weigang Lu, Zheng Liang*, Yaming Yang, Ziyu Zheng, Meng Yan, Beilei Ling, Ziyu Guan, Wei Zhao.
A fine-grained data augmentation framework for GNNs that shifts message passing patterns to enhance node representations under limited labels.
WWW 2026 Oral [Paper]

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang, Yujie Sun, Zheng Liang, Yibing Zhan, Dapeng Tao.
A progressive knowledge distillation framework that transfers GNN knowledge to MLPs for efficient deployment without sacrificing performance.
AAAI 2026 Oral [arXiv]

AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang, Yibing Zhan, Yiheng Lu, Dapeng Tao.
An adaptive graph mixup strategy that generates synthetic training samples for improved semi-supervised node classification.
AAAI 2025 [Paper]

AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang.
An AdaBoost-inspired approach for distilling GNN knowledge into MLPs, achieving efficient inference while preserving performance.
SIGKDD 2024 [Paper]

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks
Weigang Lu, Yibing Zhan, Binbin Lin†, Ziyu Guan†, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, Dacheng Tao.
A novel architecture that mitigates performance degradation in deep GCNs by selectively skipping node updates.
IEEE TKDE 2024 [Paper]

WWW 2026 MessageShift: Fine-Grained Data Augmentation for Graph Neural Networks
Weigang Lu, Zheng Liang*, Yaming Yang, Ziyu Zheng, Meng Yan, Beilei Ling, Ziyu Guan, Wei Zhao. Oral. [Paper]
WWW 2026 Aligning Multiple Knowledge Graphs in A Single Pass
Yaming Yang, Zhe Wang, Ziyu Guan†, Wei Zhao, Weigang Lu, Xinyan Huang, Jiangtao Cui, Xiaofei He. Oral. [Paper]
WWW 2026 Beyond Single-Granularity Prompts: A Multi-Scale Chain-of-Thought Prompt Learning for Graph
Ziyu Zheng, Yaming Yang, Ziyu Guan, Wei Zhao†, Xinyan Huang, Weigang Lu. Oral. [Paper]
AAAI 2026 ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang, Yujie Sun, Zheng Liang, Yibing Zhan, Dapeng Tao. Oral. [arXiv]
ICDE 2025 SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks (Extended Abstract)
Weigang Lu, Yibing Zhan, Binbin Lin†, Ziyu Guan†, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, Dacheng Tao. [Paper]
AAAI 2025 AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang, Yibing Zhan, Yiheng Lu, Dapeng Tao. [Paper]
NeurIPS 2025 Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
Yaming Yang, Ziyu Zheng, Weigang Lu, Zhe Wang, Xinyan Huang, Wei Zhao, Ziyu Guan. [Paper]
SIGKDD 2025 Enhancing Homophily-Heterophily Separation: Relation-Aware Learning in Heterogeneous Graphs
Ziyu Zheng, Yaming Yang, Ziyu Guan, Wei Zhao†, Weigang Lu. [Paper]
SIGKDD 2025 Discrepancy-Aware Graph Mask Auto-Encoder
Ziyu Zheng, Yaming Yang, Ziyu Guan, Wei Zhao, Weigang Lu. [Paper]
SIGKDD 2024 AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang. [Paper]
IEEE TKDE 2024 SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks
Weigang Lu, Yibing Zhan, Binbin Lin†, Ziyu Guan†, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, Dacheng Tao. [Paper]
AAAI 2024 NodeMixup: Tackling Under-Reaching for Graph Neural Networks
Weigang Lu, Ziyu Guan, Wei Zhao†, Yaming Yang, Long Jin. [Paper]
NeurIPS 2022 Self-supervised Heterogeneous Graph Pre-training based on Structural Clustering
Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao†, Cai Xu, Weigang Lu, Jianbin Huang. Spotlight. [Paper]
Neurocomputing 2025 Pseudo Contrastive Learning for Graph-based Semi-supervised Learning
Weigang Lu, Ziyu Guan†, Wei Zhao, Yaming Yang, Yuanhai Lv, Lining Xing, Baosheng Yu, Dacheng Tao. [Paper]
Pattern Recognition 2025 Does Noise in the Knowledge Graph Really Harm Recommendations?
Meng Yan, Cai Xu, Ziyu Guan†, Wei Zhao, Xujing Wang, Beilei Ling, Weigang Lu†. [Paper]
Neurocomputing 2025 G-NodeMixup: Enhancing Graph Neural Networks Reachability under Extremely Limited Labels
Ziyu Guan, Beilei Ling, Weigang Lu†, Meng Yan, Yaming Yang, Wei Zhao, Yibing Zhan, Yiheng Lu, Dapeng Tao. [Paper]
DASFAA 2026 Collaborative Pattern Mining in Activity Graphs
Beilei Ling, Ziyu Guan, Wei Zhao, Yiheng Lu, Meng Yan, Cai Xu, Weigang Lu, Beizeng Ling. [Paper]
IEEE TKDE 2023 Graph Substructure Assembling Network with Soft Sequence and Context Attention
Yaming Yang, Ziyu Guan†, Wei Zhao, Weigang Lu, Bo Zong. [Paper]

Awards

🏆 2025, AAAI Student Travel Award
🏆 2024, National Scholarship for Postgraduates
🏆 2024, China Scholarship Council (CSC) Scholarship
🏆 2024, ACM SIGKDD Student Travel Award
🏆 2024, Outstanding Doctoral Dissertation Funding Program (Xidian University)
🏆 2024, Second-class Ph.D. Scholarship (Xidian University)
🏆 2024, Outstanding Graduate Student Scholarship (Xidian University)
🏆 2021/2022, Annual Academic Conference Outstanding Paper Award (Xidian University)

Services

Session Chair:

WWW 2026, Session Chair
AAAI 2026, Session Co-chair

Journal Reviewer:

IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Information Processing and Management (IP&M)
Neurocomputing
ACM Transactions on Knowledge Discovery from Data (TKDD)
Neural Networks
Scientific Reports

Conference Reviewer:

NeurIPS 2026
ACM SIGKDD 2024, 2025, 2026, 2027
AAAI 2026, 2027
WebConf 2026
WSDM 2027
ICDM 2024

Weigang Lu 陆维港