Wei Ju (琚玮) is currently a postdoc research fellow in Computer Science at Peking University. Prior to that, he received his Ph.D. degree in 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.

I’m on job market now! If you are interested in me, contact me via juwei@pku.edu.cn

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

2024-5: 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

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
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
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
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

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

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
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
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
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
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
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
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
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
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
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
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
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
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
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, 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 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)
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)
Signal Processing (SP)
BMC Bioinformatics
PLOS ONE
Multimedia Systems

Conference:

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