Chuang Liu

Chuang Liu

PhD candidate

About me

刘闯，博士，大连海事大学人工智能学院副教授。本科毕业于武汉大学物理科学与技术学院，博士毕业于武汉大学计算机学院。

Chuang Liu, Ph.D., is an Associate Professor at the School of Artificial Intelligence, Dalian Maritime University. He received his B.S. in Physics from Wuhan University and his Ph.D. in Computer Science, also from Wuhan University.

欢迎报考本组硕士，同时也诚邀本科实习生加入。 有意向的同学请将个人简历发送至我的邮箱 (chuangliu@whu.edu.cn/ 2015301020059lc@gmail.com)

Research Interests

  • Graph Representation Learning: Graph Neural Networks, Graph Transformer
  • Pre-training on Graphs: Graph Masked Autoencoder, Graph Contrastive Learning
  • Graph Efficient Learning: Pruning, Graph Knowledge Distillation
  • Application: Drug Discovery, Drug Generation, Traffic Flow Prediction

Preprints

  1. Dual-perspective Cross Contrastive Learning in Graph Transformers [Paper]
    Zelin Yao, Chuang Liu, Xueqi Ma, Mukun Chen, Jia Wu, Xiantao Cai, Bo Du, Wenbin Hu

  2. Hi-GMAE: Hierarchical Graph Masked Autoencoders [Paper]
    Chuang Liu, Zelin Yao, Yibing Zhan, Xueqi Ma, Dapeng Tao, Jia Wu, Wenbin Hu, Shirui Pan, Bo Du

  3. Local-Global Graph Masked Autoencoders for Graph-level Representation Learning [Paper]
    Chuang Liu, Chen Cao, Zelin Yao, Yibing Zhan, Xueqi Ma, Dapeng Tao, Jia Wu, Wenbin Hu

  4. Exploring High-Order Message-Passing in Graph Transformers [Paper]
    Xueqi Ma, Xingjun Ma, Chuang Liu, Sarah Monazam Erfani, James Bailey

  5. Leveraging Tissue-level Representations and Labels for Whole Slide Images Classification [Paper]
    Xueqi Ma, Xingjun Ma, Chuang Liu, Sarah Monazam Erfani, James Bailey

Selected Publications [See All]

(* Equal Contribution # Corresponding Author)

  1. Graph Explicit Pooling Utilizing Discarded Nodes [Paper]
    Chuang Liu, Wenhang Yu, Kuang Gao, Xueqi Ma, Yibing Zhan, Jia Wu, Bo Du, Wenbin Hu
    Neural Networks 2024, CCF-B, JCR Q1, IF=7.8

  2. Debiased Graph Clustering with Dual Contrastive Learning [Paper]
    Kuang Gao, Mukun Chen, Chuang Liu, Zhenyu Qiu, Xiahu, Jia, Wenbin Hu
    IEEE International Conference on Web Services
    IEEE ICWS 2024, CCF-B

  3. Exploring sparsity in graph transformers [Paper]
    Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu, Bo Du
    Neural Networks 2024, CCF-B, JCR Q1, IF=7.8

  4. Towards a better negative sampling strategy for dynamic graphs [Paper]
    Kuang Gao, Chuang Liu, Jia Wu, Bo Du, Wenbin Hu
    Neural Networks 2024, CCF-B, JCR Q1, IF=7.8

  5. Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders [Paper]
    Chuang Liu, Yuyao Wang, Yibing Zhan, Xueqi Ma, Dapeng Tao, Jia Wu, Wenbin Hu
    International Joint Conference on Artificial Intelligence
    IJCAI 2024, CCF-A

  6. Gradformer: Graph Transformer with Exponential Decay [Paper]
    Chuang Liu, Zelin Yao, Yibing Zhan, Xueqi Ma, Shirui Pan, Wenbin Hu
    International Joint Conference on Artificial Intelligence
    IJCAI 2024, CCF-A

  7. On exploring node-feature and graph-structure diversities for node drop graph pooling [Paper]
    Chuang Liu, Yibing Zhan, Baosheng Yu, Liu Liu, Bo Du, Wenbin Hu, Tongliang Liu
    Neural Networks 2023, CCF-B, JCR Q1, IF=7.8

  8. Gapformer: Graph transformer with graph pooling for node classification [Paper]
    Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu
    International Joint Conference on Artificial Intelligence
    IJCAI 2023, CCF-A

  9. Graph pooling for graph neural networks: Progress, challenges, and opportunities [Paper]
    Chuang Liu, Yibing Zhan, Jia Wu, Chang Li, Bo Du, Wenbin Hu, Tongliang Liu, Dacheng Tao
    International Joint Conference on Artificial Intelligence
    IJCAI 2023, CCF-A

  10. Comprehensive graph gradual pruning for sparse training in graph neural networks [Paper]
    Chuang Liu, Xueqi Ma, Yibing Zhan, Liang Ding, Dapeng Tao, Bo Du, Wenbin Hu, Danilo P Mandic
    IEEE Transactions on Neural Networks and Learning Systems
    IEEE TNNLS 2023, CCF-B, JCR Q1, IF=10.2

  11. Vega-MT: The JD explore academy machine translation system for WMT22 [Paper]
    Changtong Zan, Keqin Peng, Liang Ding, Baopu Qiu, Boan Liu, Shwai He, Qingyu Lu, Zheng Zhang, Chuang Liu, Weifeng Liu, Yibing Zhan, Dacheng Tao
    Proceedings of the Seventh Conference on Machine Translation
    WMT 2022, CCF-A

  12. Masked graph auto-encoder constrained graph pooling [Paper]
    Chuang Liu, Yibing Zhan, Xueqi Ma, Dapeng Tao, Bo Du, Wenbin Hu
    Joint European Conference on Machine Learning and Knowledge Discovery in Databases
    ECML-PKDD 2022, CCF-B

  13. Enhancing graph neural networks by a high-quality aggregation of beneficial information [Paper]
    Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu
    Neural Networks 2021, CCF-B, JCR Q1, IF=7.8

  14. Range and dose verification in proton therapy using proton-induced positron emitters and recurrent neural networks [Paper]
    Chuang Liu, Zhongxing Li, Wenbin Hu, Lei Xing, Hao Peng
    Physics in Medicine & Biology 2021, JCR Q2, IF=2.8

Honors and Awards

  • 2023: First-class academic scholarship, Wuhan University
  • 2023: Special Scholarship (DiDi), Wuhan University
  • 2019: Excellent graduate, Wuhan University

Program Committee Member and Reviewer

Journal:

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • Pattern Recognition
  • Neural Networks
  • Information Sciences
  • Expert Systems With Applications
  • Knowledge-Based Systems
  • Engineering Applications of Artificial Intelligence
  • Neurocomputing
  • Pattern Recognition Letters

Conference:

  • KDD, IJCAI, ACMMM, IEEE ICWS