Wei Ju (琚玮) is currently an associate professor (副研究员) with the College of Computer Science, Sichuan University (SCU), Chengdu, China. He is also a member of DICALab (Data Intelligence and Computing Arts Lab), which is led by Prof. Jiancheng Lv. Before joining SCU, he worked as a postdoc research fellow and received his Ph.D. degree in the School of Computer Science from Peking University in June 2022, under the supervision of Prof. Ming Zhang. His current research interests lie primarily in the area of machine learning on graphs including graph representation learning and graph neural networks, and interdisciplinary applications such as bioinformatics, drug discovery, recommender systems, spatio-temporal analysis and knowledge graphs.

琚玮,四川大学计算机学院特聘副研究员。于2022年在北京大学计算机学院获博士学位,长期从事人工智能、机器学习、数据挖掘等方面的研究。研究兴趣主要集中图表示学习、推荐系统、时空数据分析以及交叉学科应用(AI4Science)等。主持国家自然科学基金青年科学基金项目和中国博士后科学基金面上项目,作为项目骨干参与多项国家重点研发计划和企业横向基金课题。近5年来共发表国际顶级学术论文40余篇,其中以第一作者/共同一作/通讯作者身份发表论文30余篇,相关研究成果发表在ICML、AAAI、IJCAI、TPAMI、TKDE、TOIS等机器学习和数据挖掘的国际顶级会议和期刊上,并荣获2022年国际顶级会议ICDM的最佳论文提名奖和2023年度ACM SIGCSE中国“优博奖”。并在多个国际顶级会议和期刊如 ICLR、ICML、NeurIPS、KDD、WWW、AAAI、IJCAI、TKDE、TOIS、TNNLS等担任程序委员会成员和审稿人。此外,长期担任由中国科协和教育部联合组织的中学生科技创新后备人才培养计划(“英才计划”)的辅导老师,指导优秀中学生进行科研探索和科技创新。

Research Interests

  • Deep Learning, Data Mining
  • Graph Representation Learning, Graph Neural Networks
  • Self-supervised/Contrastive Learning, Semi-supervised Learning on Graphs
  • Bioinformatics, Drug Discovery
  • Recommender Systems, Drug/Medicine Recommendation
  • Spatio-temporal Analysis, Traffic Prediction
  • Cross-modal Learning, Image Retrieval
  • Knowledge Graph, Knowledge Graph Reasoning

What’s New

  • 2024-7: Our paper Towards Semi-Supervised Universal Graph Classification published in TKDE 2023 has been selected as an ESI Highly Cited Paper !!
  • 2024-7: One paper has been accepted by TNNLS 2024 !!
  • 2024-6: One paper has been accepted by TPAMI 2024 !!
  • 2024-5: One paper has been accepted by TMM 2024 !!
  • 2024-5: Two papers have been accepted by ICML 2024 !!
  • 2024-5: One paper has been accepted by Pattern Recognition 2024 !!
  • 2024-4: Two papers have been accepted by IJCAI 2024 !!
  • 2024-3: One paper has been accepted by Information Fusion 2024 !!
  • 2024-2: One paper has been accepted by Neural Networks 2024 !!
  • 2024-1: One paper has been accepted by SCIS 2024 !!
  • 2023-12: One paper has been accepted by TKDE 2024 !!
  • 2023-10: One paper has been accepted by TMLR 2023 !!
  • 2023-9: Honored to be awared 2023 Outstanding Doctoral Dissertation Award of ACM SIGCSE !!
  • 2023-9: One paper has been accepted by TOMM 2023 !!
  • 2023-9: One paper has been accepted by TKDD 2023 !!
  • 2023-9: One paper has been accepted by TNNLS 2023 !!
  • 2023-8: One paper has been accepted by TBD 2023 !!
  • 2023-8: One paper has been accepted by TOIS 2023 !!
  • 2023-8: Project supported by the Young Scientists Fund of the National Natural Science Foundation of China !!
  • 2023-8: One paper has been accepted by TMLR 2023 !!
  • 2023-7: Two papers have been accepted by ACMMM 2023 !!
  • 2023-7: Honored to be appointed as an Editorial Board Member of Applied Research !!
  • 2023-6: Honored to be appointed as an Academic Editor of PLOS ONE !!
  • 2023-6: Project supported by the China Postdoctoral Science Foundation !!
  • 2023-5: One paper has been accepted by TKDE 2023 !!
  • 2023-4: One paper has been accepted by ICML 2023 !!
  • 2023-3: One paper has been accepted by Neural Networks 2023 !!
  • 2023-2: One paper has been accepted by ICASSP 2023 !!
  • 2023-2: One paper has been accepted by ICDE 2023 !!
  • 2022-11: 🏆 We win the Best Paper Finalist in ICDM 2022 !!
  • 2022-11: One paper has been accepted by AAAI 2023 !!
  • 2022-11: One paper has been accepted by Neural Networks 2023 !!
  • 2022-10: One paper has been accepted by WSDM 2023 !!
  • 2022-9: One paper has been accepted by ICONIP 2022 !!
  • 2022-9: One paper has been accepted by ICDM 2022 !!
  • 2022-6: One paper has been accepted by ACMMM 2022 !!
  • 2022-5: One paper has been accepted by TNNLS 2022 !!
  • 2022-4: One paper has been accepted by IJCAI 2022 !!
  • 2022-3: One paper has been accepted by Neural Networks 2022 !!
  • 2021-12: One paper has been accepted by AAAI 2022 !!
  • 2021-10: One paper has been accepted by WSDM 2022 !!
  • 2021-10: One paper has been accepted by ICONIP 2021 !!
  • 2021-9: One paper has been accepted by ICTAI 2021 !!
  • 2021-8: One paper has been accepted by ICDE 2022 !!

Survey

  1. A Survey of Data-Efficient Graph Learning [Paper]
    Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, and Ming Zhang
    International Joint Conference on Artificial Intelligence
    IJCAI 2024, CCF-A

  2. A Comprehensive Survey on Deep Graph Representation Learning [Paper]
    Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, and Ming Zhang
    Neural Networks 2024, CCF-B, JCR Q1, IF=7.8

  3. Towards Graph Contrastive Learning: A Survey and Beyond [Paper]
    Wei Ju, Yifan Wang, Yifang Qin, Zhengyang Mao, Zhiping Xiao, Junyu Luo, Junwei Yang, Yiyang Gu, Dongjie Wang, Qingqing Long, Siyu Yi, Xiao Luo, and Ming Zhang

  4. A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges [Paper]
    Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S Yu, and Ming Zhang

  5. A Survey on Graph Neural Networks in Intelligent Transportation Systems [Paper]
    Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, and Ming Zhang

Preprints

  1. PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering [Paper]
    Yifang Qin, Wei Ju, Xiao Luo, Yiyang Gu, Zhiping Xiao, and Ming Zhang

  2. Fimo: A challenge formal dataset for automated theorem proving [Paper]
    Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, and Qun Liu

  3. Poisoning scientific knowledge using large language models [Paper]
    Junwei Yang, Hanwen Xu, Srbuhi Mirzoyan, Tong Chen, Zixuan Liu, Wei Ju, Luchen Liu, Ming Zhang, and Sheng Wang

  4. Graph ODE with Factorized Prototypes for Modeling Complicated Interacting Dynamics [Paper]
    Xiao Luo, Yiyang Gu, Huiyu Jiang, Jinsheng Huang, Wei Ju, Ming Zhang, and Yizhou Sun

  5. Learning from the Future: Improve Long-term Mesh-based Simulation with Foresight [Paper]
    Xiao Luo, Junyu Luo, Huiyu Jiang, Wei Ju, Carl Yang, Ming Zhang, and Yizhou Sun

  6. When does maml work the best? an empirical study on model-agnostic meta-learning in nlp applications [Paper]
    Zequn Liu, Ruiyi Zhang, Yiping Song, Wei Ju, and Ming Zhang

Selected Publications [See All]

(* Equal Contribution)

  1. Hypergraph-enhanced Dual Semi-supervised Graph Classification [Paper]
    Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, and Ming Zhang
    International Conference on Machine Learning
    ICML 2024, CCF-A

  2. GLCC: A General Framework for Graph-level Clustering [Paper]
    Wei Ju*, Yiyang Gu*, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, and Ming Zhang
    AAAI Conference on Artificial Intelligence
    AAAI 2023, CCF-A, Oral Representation

  3. TGNN: A Joint Semi-supervised Framework for Graph-level Classification [Paper]
    Wei Ju*, Xiao Luo*, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, and Ming Zhang
    International Joint Conference on Artificial Intelligence
    IJCAI 2022, CCF-A

  4. A Survey of Data-Efficient Graph Learning [Paper]
    Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, and Ming Zhang
    International Joint Conference on Artificial Intelligence
    IJCAI 2024, CCF-A

  5. GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling [Paper]
    Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, and Ming Zhang
    SCIENCE CHINA Information Sciences
    SCIS 2024, CCF-A, JCR Q1, IF=8.8

  6. COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting [Paper]
    Wei Ju*, Yusheng Zhao*, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, and Ming Zhang
    Information Fusion 2024, JCR Q1, IF=18.6

  7. Kernel-based Substructure Exploration for Next POI Recommendation [Paper][Code]
    Wei Ju*, Yifang Qin*, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, and Ming Zhang
    IEEE International Conference on Data Mining
    ICDM 2022, CCF-B, 🏆 Best Paper Finalist

  8. KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification [Paper]
    Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, and Ming Zhang
    ACM International Conference on Web Search and Data Mining
    WSDM 2022, CCF-B

  9. Focus on Informative Graphs! Semi-supervised Active Learning for Graph-level Classification [Paper]
    Wei Ju, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Siyu Yi, Zhiping Xiao, Xiao Luo, Yanjie Fu, and Ming Zhang
    Pattern Recognition 2024, CCF-B, JCR Q1, IF=8.0

  10. A Comprehensive Survey on Deep Graph Representation Learning [Paper]
    Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, and Ming Zhang
    Neural Networks 2024, CCF-B, JCR Q1, IF=7.8

  11. Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs [Paper]
    Wei Ju*, Zequn Liu*, Yifang Qin, Bin Feng, Chen Wang, Zhihui Guo, Xiao Luo, and Ming Zhang
    Neural Networks 2023, CCF-B, JCR Q1, IF=7.8

  12. Unsupervised Graph-level Representation Learning with Hierarchical Contrasts [Paper]
    Wei Ju*, Yiyang Gu*, Xiao Luo, Yifan Wang, Haochen Yuan, Huasong Zhong, and Ming Zhang
    Neural Networks 2023, CCF-B, JCR Q1, IF=7.8

  13. GHNN: Graph Harmonic Neural Networks for Semi-supervised Graph-level Classification [Paper]
    Wei Ju*, Xiao Luo*, Zequ Ma, Junwei Yang, Minghua Deng, and Ming Zhang
    Neural Networks 2022, CCF-B, JCR Q1, IF=9.657

  14. Zero-shot Node Classification with Graph Contrastive Embedding Network [Paper]
    Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, and Ming Zhang
    Transactions on Machine Learning Research
    TMLR 2023

Funds and Projects

  • Young Scientists Fund of the National Natural Science Foundation of China, Principal Investigator
  • China Postdoctoral Science Foundation Funded Project, Principal Investigator

Honors and Awards

  • Sep. 2023: Outstanding Doctoral Dissertation Award (The Only Winner in ACM SIGCSE Chapter), ACM SIGCSE
  • Nov. 2022: 🏆 Best Paper Finalist, ICDM
  • Dec. 2021: Award for Scientific Research, Peking University
  • Dec. 2020: Huawei Scholarship, Huawei Technologies Co., Ltd.
  • Dec. 2020: Merit student, Peking University
  • May. 2018: Top 1 of the men’s team in table tennis competition for college students, Beijing
  • Jan. 2017: Outstanding Student, Sichuan University
  • Jan. 2017: The First Price Scholarship, Sichuan University
  • May. 2014: Top 1 of men’s singles in table tennis competition for college students, Sichuan Province

Program Committee Member and Reviewer

Journal:

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Multimedia (TMM)
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
  • IEEE Transactions on Intelligent Vehicles (TIV)
  • IEEE Transactions on Cognitive and Developmental Systems (TCDS)
  • ACM Transactions on Information Systems (TOIS)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • ACM Transactions on Intelligent Systems and Technology (TIST)
  • Transactions on Machine Learning Research (TMLR)
  • Information Fusion (IF)
  • Pattern Recognition (PR)
  • Neural Networks (NN)
  • Knowledge and Information Systems (KAIS)
  • Knowledge-Based Systems (KBS)
  • Neurocomputing (NC)
  • Neural Computing and Applications (NCAA)
  • Artificial Intelligence Review (AIR)
  • Signal Processing (SP)
  • BMC Bioinformatics
  • PLOS ONE
  • Multimedia Systems

Conference:

  • 2025: KDD, AAAI
  • 2024: ICLR, ICML, NeurIPS, KDD, WWW, CVPR, ECCV, ACL, AAAI, IJCAI, ACMMM, WSDM, CIKM, SDM, ICASSP, AISTATS, DASFAA, BMVC, PAKDD, ACML, LoG, CAI
  • 2023: NeurIPS, KDD, AAAI, IJCAI, SIGIR, ACMMM, CIKM, ICDM, BMVC, LoG, ISKE
  • 2022: ECCV, IJCNN, ICONIP