Welcome to Professor Jia Wu's Homepage

Prof Jia Wu is an ARC Future Fellow (Level 3, 2026 - 2030) and Full Professor in the School of Computing at Macquarie University.

Dr Wu is the Research Director for the Centre for Applied Artificial Intelligence, Macquarie University.

Dr Wu is the Director of Higher Degree Research (HDR) in the School of Computing at Macquarie University.

Dr Wu was recognised as a National Leader, the only researcher across Australia to receive this title in the field of Databases and Information Systems, by The Australian’s Research 2025 magazine.

Dr Wu was selected as a 2024 Highly Cited Researcher (Clarivate™), placing him among the top 0.1% of researchers worldwide in Computer Science.

Dr Wu was awarded the prestigious 2025 CORE Award for Outstanding Research Contribution (known prior to 2023 as the Chris Wallace Award), granted to *ONLY ONE* academic each year from an Australian or New Zealand university or research institution.

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Associate Editor (2024 - ), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), JCR Q1, CORE A*, Impact Factor 8.9.

Associate Editor (2017- ), ACM Transactions on Knowledge Discovery from Data (TKDD), JCR Q1, Impact Factor 4.8.

Associate Editor (2018- ), Neural Networks, Elsevier, JCR Q1, CORE A, Impact Factor 6.3.

Associate Editor (2018- ), Neurocomputing, Elsevier, JCR Q1, Impact Factor 6.5.

Associate Editor (2017- ), Journal of Network and Computer Applications, Elsevier, JCR Q1, CORE A, Impact Factor 8.0.

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Dr Wu and his research team have received prestigious competitive awards and recognitions, including Microsoft Research PhD Fellowship (2022), three Vice-Chancellor’s Commendations (PhD), seven Executive Dean’s Commendations (MRes), and the recipient of the Best Paper Award (ADMA 2024), the Best Paper Runner-Up Award (ACM CIKM 2022), the Best Paper Award Honorable Mention (ACM CIKM 2022), the Best Student Paper Award (IEEE ICDM 2021), the Best Paper Award in Data Science Track (SDM 2018), the Best Student Paper Award (IJCNN 2017), and Best Paper Candidate Award (ICDM 2014). He is a Senior Member of the IEEE.

Research Interests  

  • Graph Mining
  • LLM
  • Knowledge Graphs
  • Graph Neural Networks
  • Recommended Systems
  • Social Networks
  • Time Series Analysis
  • Deep Learning
  • Graph Search
  • Multi-objective Optimisation
  • Anomaly Detection
  • Brain Graph Analysis

Address

4 Research Park Drive, Macquarie Park, NSW 2113, Australia

Email: jia.wu@mq.edu.au

  • Macquarie Univerity's data science and AI ranked in Top 50 Globally
  • Graph Neural Networks
  • LLM and Knowledge Graphs
  • Knowledge Graph Representation and Learning
  • Social Recommendation Systems
  • Graph Representation and Learning
  • Anomoly Detection - Fake News/users; spammers; fraudsters
  • Time Series Analysis - EEG/MEG
  • Graph Mining

Call for Students

I am seeking highly motivated and focused students with Backgrounds & Interests in Computer Science, Mathematics, Engineering, Busissness, Management and Bioinformatics.

 PhD scholarships are OFFERED with topics

  • Graph Mining

  • LLM

  • Knowledge Graph

  • Graph Neural Networks

  • Recommended Systems

  • Graph search

  • Deep Learning

  • Anomaly Detection

  • Time Series Analysis

  • Brain Graphs/Networks

  • Multi-objective optimisation

  • Business Data Intelligence

 Recruiting Students

  • PhD Scholarships now OPEN for 2026 commencement
    • Graph Anomaly Detection
      • Research Topics: node-level, edge-level , graph-level anomaly detection, dynamic graph anomaly detection, graph diffusion models
      • Closing Date: 2 March 2026
    • Graph Mining Theory
      • Research Topics: graph neural networks, graph explainability, dynamic graph mining, graph reinforced learning
      • Closing Date: 2 March 2026
    • LLM and Knowledge Graphs
      • Research Topics: LLM, NLP, Text Mining, Knowledge Graphs
      • Closing Date: 2 March 2026
    • How to apply: Contact me first and make an online applications

If you are interested in applying for the above scholarships, please email jia.wu@mq.edu.au

 Selected Publications
CompleteList: DBLP or Google
Conferences
  1. Nian Rong, Fei Xiong, Shirui Pan, Guixun Luo, Jia Wu, Liang Wang, Domain-Level Disentanglement Framework Based on Information Enhancement for Cross-Domain Cold-Start Recommendation, Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI), USA, 2025.
  2. Zitai Qiu, Congbo Ma, Jia Wu, Jian Yang, Text is All You Need: LLM-enhanced Incremental Social Event Detection, Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), Austria, 2025. [ code]
  3. Congbo Ma, Yuxia Wang, Jia Wu, Jian Yang, Jing Du, Zitai Qiu, Qing Li, Hu Wang, Preslav Nakov: Explicit and Implicit Data Augmentation for Social Event Detection, Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), Austria, 2025. [ code]
  4. Xixun Lin, Yanan Cao, Nan Sun, Lixin Zou, Chuan Zhou, Peng Zhang, Shuai Zhang, Ge Zhang, Jia Wu, Conformal graph-level out-of-distribution detection with adaptive data augmentation, Proceedings of the 34th ACM on Web Conference (WWW), Australia, 2025.
  5. Congbo Ma, Zitai Qiu, Hu Wang, Jing Du, Shan Xue, Jia Wu, Jian Yang, Enhanced Social Event Detection through Dynamically Weighted Meta-Paths Modeling, Proceedings of the 34th ACM on Web Conference (WWW), Australia, 2025.
  6. Qihua Lyu, Xin Cao, Yongsheng Yu, Shan Xue, Jian Yang, Jia Wu, Amin Beheshti, A Multiagent-based Framework on RoboCup Simulation System for Enhancing Rescue Operation during Dynamic Disaster Environments, Proceedings of the 34th ACM on Web Conference (WWW), Australia, 2025.
  7. Malik Khizar Hayat, Shan Xue, Jia Wu, Bilal Khan, Jian Yang, Self-supervised Time-aware Heterogeneous Hypergraph Learning for Dynamic Graph-level Classification, Proceedings of the 18th ACM International Conference on Web Search and Data Mining (WSDM), Germany, 2025. [ code]
  8. Kun Li, Yida Xiong, Hongzhi Zhang, Xiantao Cai, Jia Wu, Bo Du, Wenbin Hu, Graph-Structured Small Molecule Drug Discovery Through Deep Learning: Progress, Challenges, and Opportunities, Proceedings of the IEEE International Conference on Web Services (ICWS), Finland, 2025.
  9. Jiameng Chen, Xiantao Cai, Jia Wu, Wenbin Hu, Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding, Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI), Canada, 2025.
  10. Yiming Wang, Hao Peng, Senzhang Wang, Haohua Du, Chunyang Liu, Jia Wu, Guanlin Wu, STAMImputer: Spatio-Temporal Attention MoE for Traffic Data Imputation, Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI), Canada, 2025.
  11. Minhui Xie, Hao Peng, Pu Li, Guangjie Zeng, Shuhai Wang, Jia Wu, Peng Li, Philip S. Yu, Hierarchical Superpixel Segmentation via Structural Information Theory, Proceedings of the 25th SIAM International Conference on Data Mining (SDM), USA, 2025.
  12. Kai Zhu, Jing Li, Jia Wu, Yue He, Jun Chang, Guohao Li, Shuyi Zhang, Adaptive User Dynamic Interest Guidance for Generative Sequential Recommendation, Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Italy, 2025. [ data]
  13. Xiaoxiao Ma, Yuchen Zhang, Kaize Ding, Jian Yang, Jia Wu, Hao Fan, On Fake News Detection with LLM Enhanced Semantics Mining, Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), USA, 2024. [ data]
  14. Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu, Graph Anomaly Detection with Few Labels: A Data-Centric Approach, Proceedings of the 30th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD), Spain, 2024. [ data]
  15. Kun Li, Weiwei Liu, Yong Luo, Xiantao Cai, Jia Wu, Wenbin Hu, Zero-shot Learning for Preclinical Drug Screening, Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), Korea, 2024. [ code]
  16. Kun Li, Xiuwen Gong, Jia Wu, Wenbin Hu, Contrastive Learning Drug Response Models from Natural Language Supervision, Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), Korea, 2024. [ code]
  17. Chuang Liu, Yuyao Wang, Yibing Zhan, Xueqi Ma, Dapeng Tao, Jia Wu, Wenbin Hu, Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders, Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), Korea, 2024. [ code]
  18. Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Quan Z. Sheng, David McAlpine, Paul F. Sowman, Alexis Giral, Philip S. Yu, Graph Neural Networks for Brain Graph Learning: A Survey, Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), Korea, 2024. [ data]
  19. Yuchen Zhang, Xiaoxiao Ma, Jia Wu, Jian Yang, Hao Fan, Heterogeneous Subgraph Transformer for Fake News Detection, Proceedings of the 34th ACM on Web Conference (WWW), Singapore, 2024. [ data]
  20. Zitai Qiu, Congbo Ma, Jia Wu, Jian Yang, An Efficient Automatic Meta-Path Selection for Social Event Detection via Hyperbolic Space, Proceedings of the 34th ACM on Web Conference (WWW), Singapore, 2024. [ code]
  21. Xing Su, Jian Yang, Jia Wu, Zitai Qiu, Debunking Fake News in Online Social Networks Without Text Analysis, Proceedings of the 24th IEEE International Conference on Data Mining (ICDM), UAE, 2024. [ code]
  22. Guangwei Dong, Xuexiong Luo, Jing Du, Jia Wu, Shan Xue, Jian Yang, Amin Beheshti, Counterfactual Brain Graph Augmentation Guided Bi-Level Contrastive Learning for Disorder Analysis, Proceedings of the 24th IEEE International Conference on Data Mining (ICDM), UAE, 2024. [ data]
  23. Venus Haghighi, Behnaz Soltani, Nasrin Shabani, Jia Wu, Yang Zhang, Lina Yao, Quan Z. Sheng, Jian Yang, TROPICAL: Transformer-Based Hypergraph Learning for Camouflaged Fraudster Detection, Proceedings of the 24th IEEE International Conference on Data Mining (ICDM), UAE, 2024.
  24. Xuexiong Luo, Guangwei Dong, Jia Wu, Amin Beheshti, Jian Yang, Shan Xue, An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis, Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM), México, 2024. [ code]
  25. Nasrin Shabani, Amin Beheshti, Jia Wu, Maryam Khanian Najafabadi, Jin Foo, Alireza Jolfaei, GraphSUM: Scalable Graph Summarization for Efficient Question Answering, Proceedings of the 27th International Conference on Extending Database Technology (EDBT), Italy, 2024.
  26. Fariba Lotfi, Amin Beheshti, Mansour Jamzad, Hamid Beigy, Jia Wu, Philip S. Yu, The Open Story Model (OSM): Transforming Big Data into Interactive Narratives, Proceedings of the IEEE International Conference on Web Services (ICWS), China, 2024.
  27. Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng, Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping, Proceedings of the 29th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD), USA, 2023. [ code]
  28. Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su, Minimum Entropy Principle Guided Graph Neural Networks, Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM), Singapore, 2023. [ code]
  29. Xing Su, Jian Yang, Jia Wu, Yuchen Zhang, Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social Networks, Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM), Singapore, 2023. [ code]
  30. Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu, Unbiased and Efficient Self-Supervised Incremental Contrastive Learning, Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM), Singapore, 2023. [ code]
  31. Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li, Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification, Proceedings of the 32nd International World Wide Web Conference (WWW), USA, 2023. [ code]
  32. Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu, SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization, Proceedings of the 32nd International World Wide Web Conference (WWW), USA, 2023. [ code]
  33. Chuang Liu, Yibing Zhan, Jia Wu, Chang Li, Bo Du, Wenbin Hu, Tongliang Liu, Dacheng Tao, Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities, the 32nd International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2023.
  34. Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu, KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks, Proceedings of the 32nd International World Wide Web Conference (WWW), USA, 2023. [ data]
  35. Zepeng Wang, Xiaochuan Shi, Chao Ma, Libing Wu, Jia Wu, CCPO: Conservatively Constrained Policy Optimization Using State Augmentation, the 26th European Conference on Artificial Intelligence (ECAI), Poland, 2023. [ code]
  36. Li Zheng, Zhao Li, Jun Gao, Zhenpeng Li, Jia Wu, Chuan Zhou, Domain Adaptation for Anomaly Detection on Heterogeneous Graphs in E-Commerce, the 45th European Conference on Information Retrieval (ECIR), Ireland, 2023.
  37. Tong Liu, Jing Li, Jia Wu, Lefei Zhang, Shanshan Zhao, Jun Chang, Jun Wan, Cross-Domain Facial Expression Recognition via Disentangling Identity Representation, the 32nd International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2023.
  38. Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal, DAGAD: Data Augmentation for Graph Anomaly Detection, Proceedings of the 22nd IEEE International Conference on Data Mining (ICDM), USA, 2022. [ code]
  39. Qianren Mao, Yiming Wang, Chenghong Yang, Linfeng Du, Hao Peng, Jia Wu, Jianxin Li, Zheng Wang, HiGIL: Hierarchical Graph Inference Learning for Fact Checking, Proceedings of the 22nd IEEE International Conference on Data Mining (ICDM), USA, 2022. [ code]
  40. Yuecen Wei, Xingcheng Fu, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li, Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation, Proceedings of the 22nd IEEE International Conference on Data Mining (ICDM), USA, 2022. [ code]
  41. Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng, Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification, the 31st International Joint Conference on Artificial Intelligence (IJCAI), Austria, 2022.
  42. Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He, From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection, Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), USA, 2022. [ code]
  43. Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu, Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees, Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), USA, 2022. [ code]
  44. Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal, Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection, Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), USA, 2022. [ code]
  45. Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, Shan Xue, ComGA: Community-Aware Attributed Graph Anomaly Detection, Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM), Tempe, Arizona, 2022. [ code]
  46. Naime Ranjbar Kermany, Jian Yang, Jia Wu, Luiz Pizzato, Fair-SRS: A Fair Session-based Recommendation System, Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM), USA, 2022. [ code]
  47. Fengzhao Shi, Yanan Cao, Yanmin Shang, Yuchen Zhou, Chuan Zhou, Jia Wu, H2-FDetector: A GNN-based Fraud Detector with Homophilic and Heterophilic Connections, Proceedings of the 31st International World Wide Web Conference (WWW), Lyon, France, 2022. [ code]
  48. Pinghua Xu, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, Wenbin Hu, Dual-branch Density Ratio Estimation for Signed Network Embedding, Proceedings of the 31st International World Wide Web Conference (WWW), Lyon, France, 2022. [ code]
  49. Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng, Curvature Graph Generative Adversarial Networks, Proceedings of the 31st International World Wide Web Conference (WWW), Lyon, France, 2022. [ code]
  50. Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S Yu, Graph Structure Learning with Variational Information Bottleneck, Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), Virtual, 2022. [ code]
  51. Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, Quan Z Sheng, FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance, Proceedings of the 21st IEEE International Conference on Data Mining (ICDM), Auckland, New Zealand, 2021. [ code] (Best Student Paper Award)
  52. Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, and Bin Wang, Task-adaptive Neural Process for User Cold-Start Recommendation, Proceedings of the 30th International World Wide Web Conference (WWW), Ljubljana, Slovenia, 2021. [ code]
  53. Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, and Philip S. Yu, Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs, Proceedings of the 30th International World Wide Web Conference (WWW), Ljubljana, Slovenia, 2021. [ code] ( Most Influential WWW Papers ranked 7th in 2021)
  54. Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Phillip S. Yu, and Lifang He, SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism, Proceedings of the 30th International World Wide Web Conference (WWW), Ljubljana, Slovenia, 2021. [ code] ( Most Influential WWW Papers ranked 4th in 2021)
  55. Pinghua Xu, Wenbin Hu, Jia Wu, and Weiwei Liu, Opinion Maximization in Social Trust Networks, the 29th International Joint Conference on Artificial Intelligence (IJCAI), Yoko, Japan, 2020. [ code]
  56. Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, and Philip S. Yu, Deep Learning for Community Detection: Progress, Challenges and Opportunities, Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), Yoko, Japan, 2020. [ code]( Most Influential IJCAI Papers ranked 1st in 2020)
  57. Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, and Li Guo, A Knowledge-Aware Attentional Reasoning Network for Recommendation, Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI ), New York, USA, 2020.[ dataset]
  58. Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, and Xiaohua Jia, Temporal Network Embedding with High-Order Nonlinear Information, Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI),New York, USA.
  59. Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, and Jilong Wang, Graph Stochastic Neural Networks for Semi-supervised Learning, Proceedings of the 34th Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, 2020. [ code]
  60. Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, and Bin Wang, Graph Geometry Interaction Learning, Proceedings of the 34th Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, 2020. [ code]
  61. Yipeng Zhang, Bo Du, Lefei Zhang, and Jia Wu, Parallel DNN Inference Framework Leveraging a Compact RISC-V ISA-based Multi-core System, Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), USA, 2020.
  62. Xuexiong Luo, Jia Wu, Chuan Zhou, Xiankun Zhang, and Yuan Wang, Deep Semantic Network Representation, Proceedings of the 20th IEEE Intl. Conference on Data Mining (IEEE ICDM), Sorrento, Italy, 2020. [ code]
  63. Xixun Lin, Chuan Zhou, Hong Yang, Jia Wu, Haibo Wang, Yanan Cao, and Bin Wang, Exploratory Adversarial Attacks on Graph Neural Networks, Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), Sorrento, Italy, 2020. [ code]
  64. Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Chuan Zhou, and Qianli Xing, AtNE-Trust: Attributed Trust Network Embedding for Trust Prediction in Online Social Networks, Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), Sorrento, Italy, 2020.
  65. Zhenyu Qiu, Wenbin Hu, Jia Wu, ZhongZheng Tang, and Xiaohua Jia, Noise-Resilient Similarity Preserving Network Embedding for Social Networks, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI) , Macao, China, 2019
  66. Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, and Li Guo, Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI) , Macao, China, 2019.
  67. Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei Li, Jianlong Tan, and Li Guo, Deep Active Learning for Anchor User Prediction, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI) , Macao, China, 2019. [ code]
  68. Peiyao Li, Weiliang Zhao, Jian Yang, and Jia Wu, CoTrRank: Trust Evaluation of Users and Tweets, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019) , Macao, China, 2019. [ demo video]
  69. Pinghua Xu, Wenbin Hu, Jia Wu, and Bo Du, Link Prediction with Signed Latent Factors in Signed Social Networks, Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , USA, 2019. [ code]
  70. Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Wenbin Hu, and Qianli Xing, DeepTrust: A Deep User Model of Homophily Effect for Trust Prediction, Proceedings of the 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 2019. [ code]
  71. Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, and Jian Yang, Social Trust Network Embedding, Proceedings of the 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 2019. [ code]
  72. Xixun Lin, Hong Yang, Jia Wu, Chuan Zhou, and Bin Wang, Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding, Proceedings of the 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 2019. [ code]
  73. Xindong Wu, Jia Wu, Xiaoyi Fu, Jiachen Li, Peng Zhou, and Xu Jiang, Automatic Knowledge Graph Construction: A Report on the 2019 ICDM/ICBK Contest, Proceedings of the 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 2019
  74. Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang, and Mei Wang, GroExpert: A Novel Group-Aware Experts Identification Approach in Crowdsourcing, Proceedings of the 20th International Conference on Web Information Systems Engineering (WISE), China, 2019.
  75. Naime Ranjbar Kermany, Weiliang Zhao, Jian Yang, and Jia Wu, ReInCre: Enhancing Collaborative Filtering Recommendations by Incorporating User Rating Credibility, Proceedings of the 20th International Conference on Web Information Systems Engineering (WISE), DEMO , China, 2019. [ demo video, code]
  76. Sihan Ma, Lefei Zhang, Wenbin Hu, Yipeng Zhang, Jia Wu, and Xuelong Li, Self-Representative Manifold Concept Factorization with Adaptive Neighbors for Clustering, Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 13-19, 2018.
  77. Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu, and Yue Hu, Recommendation with multi-source heterogeneous information, Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 13-19, 2018.
  78. Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Mehmet A Orgun, and Jia Wu, A Deep Framework for Cross-Domain and Cross-System Recommendations, Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 13-19, 2018.
  79. Li Gao, Hong Yang, Chuan Zhou, Jia Wu, Shirui Pan, and Yue Hu, Active Discriminative Network Representation Learning, Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 13-19, 2018.
  80. Liangchen Song, Bo Du, Lefei Zhang, Liangpei Zhang, Jia Wu, and Xuelong Li, Nonlocal Patch Based t-SVD for Image Inpainting: Algorithm and Error Analysis, Proceedings of the 32st AAAI Conference on Artificial Intelligence (AAAI), New Orleans, Louisiana, USA, Feb 2-7, 2018.
  81. ChunYi Liu, Chuan Zhou, Jia Wu, Yue Hu, and Li Guo, Social Recommendation with an Essential Preference Space, Proceedings of the 32st AAAI Conference on Artificial Intelligence (AAAI), New Orleans, Louisiana, USA, Feb 2-7, 2018. [ code]
  82. Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, and Jilong Wang, Deep Structure Learning for Fraud Detection, Proceedings of the 18th IEEE International Conference on Data Mining (ICDM), Singapore, November 17-20, 2018. [ code]
  83. Chenglong Dai, Jia Wu, Dechang Pi, and Lin Cui, Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification, Proceedings of the 2018 SIAM International Conference on Data Mining (SDM), San Diego, California, USA, May 3-5, 2018. (Best Paper Award in Applied Data Science Track)
  84. Min Fu, Chi-Man Wong, Hai Zhu, Yanjun Huang, Yuanping Li, Xi Zheng, Jia Wu, Jian Yang, and Chi-Man Vong, DAliM: Machine Learning Based Intelligent Lucky Money Determination for Large-Scale E-Commerce Businesses, Proceedings of the 16th International Conference on Service-Oriented Computing (ICSOC), Hangzhou, China, November 12-15, 2018.
  85. Li Gao, Jia Wu, Chuan Zhou, and Yue Hu, Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation, Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, USA, Feb 4-9, 2017.
  86. Chuan Zhou, WeiXue Lu, Peng Zhang, Jia Wu, Yue Hu, and Li Guo, On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks, Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'), Phoenix, Arizona, USA, Feb 12-17, 2016.
  87. Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, and Yang Wang, Tri-Party Deep Network Representation, Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, USA, Jul 9-15, 2016. [ code]
  88. Chun-Yi Liu, Chuan Zhou, Jia Wu, Hongtao Xie, Yue Hu, and Li Guo, CPMF: A Collective Pairwise Matrix Factorization Model for Upcoming Event Recommendation, Proceedings of the 30th IEEE International Joint Conference on Neural Networks (IJCNN), Alaska, USA, May 14-19, 2017. [ code] (Best Stduent Paper Award)
  89. Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Joint structure feature exploration and regularization for multi-task graph classification, Proceedings of the 32nd IEEE International Conference on Data Engineering (ICDE) , Helsinki, Finland, May 16-20, 2016. [ code]
  90. Li Gao, Jia Wu, Hong Yang, Zhi Qiao, Chuan Zhou, and Yue Hu, Semi-data-driven network coarsening, Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, USA, Jul 9-15, 2016.
  91. Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian, and Chengqi Zhang, Unsupervised Feature Learning from Time Series, Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, USA, Jul 9-15, 2016. [ code]
  92. Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, and Chengqi Zhang, Inferring Latent Network from Cascade Data for Dynamic Social Recommendation, Proceedings of the 16th IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 12-15, 2016.
  93. Li Gao, Jia Wu, Zhi Qiao, Chuan Zhou, Hong Yang, and Yue Hu, Collaborative Social Group Influence for Event Recommendation, Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM) , Indianapolis, Indiana, USA, Oct 24-28, 2016.
  94. Qinzhe Zhang, Jia Wu, Hong Yang, Weixue Lu, Guodong Long, and Chengqi Zhang, Global and Local Influence-based Social Recommendation, Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM) , Indianapolis, Indiana, USA, Oct 24-28, 2016.
  95. Yongshan Zhang, Jia Wu, Chuan Zhou, Peng Zhang, and Zhihua Cai, Multiple-instance Learning with Evolutionary Instance Selection, Proceedings of the 21st International Conference on Database Systems for Advanced Applications (DASFAA) , , Dallas, Texas, USA, 2016.
  96. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Chengqi Zhang, Multi-Graph-View Learning for Graph Classification, Proceedings of the IEEE 14th International Conference on Data Mining (ICDM), Shenzhen, China, Dec 14-17, 2014. (Best Paper Candidate)
  97. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, and Chengqi Zhang, Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning, Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) , Shanghai, China, Nov 3-7, 2014.
  98. Jia Wu, Xingquan Zhu, Chengqi Zhang, and Zhihua Cai, Multi-Instance Learning from Positive and Unlabeled Bags, Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Tainan, Taiwan, May 13-16, 2014.
  99. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Multi-Graph Learning with Positive and Unlabeled Bags, Proceedings of the 2014 SIAM International Conference on Data Mining (SDM), Philadelphia, Pennsylvania, USA, Apr 24-26, 2014.
  100. Jia Wu, Xingquan Zhu, Chengqi Zhang, and Zhihua Cai, Multi-Instance Multi-Graph Dual Embedding Learning, Proceedings of the 13th IEEE International Conference on Data Mining (ICDM), Dallas, Texas, USA, Dec 7-10, 2013.
Journals
  1. Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Hao Peng, Pietro Liò, Learning from Graph-Graph Relationship: A New Perspective On Graph-level Anomaly Detection, IEEE Transactions on Knowledge and Data Engineering, TKDE.2025.3618929, In-press, 2025.
  2. Xixun Lin, Qing Yu, Yanan Cao, Lixin Zou, Chuan Zhou,Jia Wu, Chenliang Li, Peng Zhang, Shirui Pan, Generative Causality-driven Network for Graph Multi-task Learnin, IEEE Transactions on Pattern Analysis and Machine Intelligenc, TPAMI.2025.3610096, In-press, 2025.
  3. Bilal Khan, Jia Wu, Jian Yang, Shan Xue, Malik Khizar Hayat, Dynamic Hypergraph for Cross-Domain Session-Based Social Recommendations, IEEE Transactions on Computational Social Systems, TCSS.2025.3575596, In-press, 2025.
  4. Jie Cao, Jiawei Miao, Haicheng Tao, Youquan Wang, Jia Wu, Zidong Wang, Generative Models for Time Series Anomaly Detection: A Survey, IEEE Transactions on Artificial Intelligence , TAI.2025.3614213, In-press, 2025.
  5. Zheng Gao, Danfeng Sun, Jianyong Zhao, Huifeng Wu, Jia Wu, Cost-Minimized Data Edge Access Model for Digital Twin Using Cloud-Edge Collaboration, IEEE Transactions on Network and Service Management, TNSM.2025.3621548, In-press, 2025.
  6. Shichen Luo, Xuexiong Luo, Jing Du, Jia Wu, Jian Yang, Community-Structure Enhanced Brain Graph Mining, IEEE Transactions on Artificial Intelligence , TAI.2025.3598793, In-press, 2025.
  7. Zhenchang Xia, Guanqun Zheng, Shengwu Xiong, Junyin Wang, Jianqun Cui, Yanan Chang, Chenghu Du, Jia Wu, RDNet: Rotate-Groundtruth Augmentation and Decoupled Attention HEAD for 3D Object Detection, IEEE Transactions on Big Data, TBDATA.2025.3624947, In-press, 2025.
  8. Xuexiong Luo, Jia Wu, Jian Yang, Hongyang Chen, Zhao Li, Hao Peng, Chuan Zhou, Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration, IEEE Transactions on Neural Networks and Learning Systems, 36(2): 3559-3572, 2025. [ code]
  9. Bilal Khan, Jia Wu, Jian Yang, Malik Khizar Hayat, Shan Xue, A Unified Hypergraph Framework for Inter and Intra-Session Dynamics in Session-Based Social Recommendations, IEEE Transactions on Big Data, 11(6): 2987-3002, 2025.
  10. Yuzhe Chen, Jie Cao, Youquan Wang, Jia Wu, Huanhuan Chen, Guandong Xu, Causal variational inference for deconfounded multi-behavior recommendation, ACM Transactions on Information Systems, 43(6): 1-26, 2025.
  11. Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò, State of the Art and Potentialities of Graph-level Learning, ACM Computing Surveys, 57(2): 28:1-28:40, 2025. [ data]
  12. Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester, A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions, ACM Computing Surveys, 57(3): 69:1-69:38, 2025. [ data]
  13. Zitai Qiu, Jia Wu, Jian Yang, Xing Su, Charu C. Aggarwal, Heterogeneous Social Event Detection via Hyperbolic Graph Representations, IEEE Transactions on Big Data, 11(1): 115-129, 2025. [ code]
  14. Tianpeng Liu, Jing Li, Amin Beheshti, Jia Wu, Jun Chang, Beihang Song, Lezhi Lian, HEART: Historically Information Embedding and Subspace Re-Weighting Transformer-Based Tracking, IEEE Transactions on Big Data, 11(2): 566-577, 2025.
  15. Junjie Hu, Danfeng Sun, Jin Fan, Junwei Dong, Baiping Chen, Huifeng Wu, Jia Wu, Extendable Multi-Device Collaborative Pipeline Parallel Inference in the Edge-Cloud Scenari, IEEE Transactions on Consumer Electronics, 71(2): 4065-4075, 2025.
  16. Bingbing Xie, Xiaoxiao Ma, Shan Xue, Amin Beheshti, Jian Yang, Hao Fan, Jia Wu, Multiknowledge and LLM-Inspired Heterogeneous Graph Neural Network for Fake News Detection, IEEE Transactions on Computational Social Systems, 12(2): 682-694, 2025.
  17. Jin Fan, Zheyu Wang, Zehao Wang, Jiajun Yang, Huifeng Wu, Jia Wu, Enhancing GCN Robustness Against Structural Attacks via Adaptive Spectrum Filtering, EEE Transactions on Information Forensics and Security, 20: 10668-10682, 2025.
  18. Xiulin Zheng, Pei-Pei Li, Zan Zhang, Jia Wu, Xindong Wu, A Relation-Constraint Link Prediction Model for Dynamic Knowledge Graphs with Entity Drift, ACM Transactions on Knowledge Discovery from Data, 19(5): 1-38, 2025.
  19. Guangjie Zeng, Hao Peng, Angsheng Li, Jia Wu, Chunyang Liu, Philip S. Yu, Scalable Semi-Supervised Clustering via Structural Entropy With Different Constraints, IEEE Transactions on Knowledge and Data Engineering, 37(1): 478-492, 2025. [ data]
  20. Xiaoxiao Ma, Fanzhen Liu, Jia Wu, Jian Yang, Shan Xue, Quan Z. Sheng, Rethinking Unsupervised Graph Anomaly Detection With Deep Learning: Residuals and Objectives, IEEE Transactions on Knowledge and Data Engineering, 37(2): 881-895, 2025. [ data]
  21. Qingqing Yi, Jingjing Tang, Xiangyu Zhao, Yujian Zeng, Zengchun Song, Jia Wu, An Adaptive Entire-Space Multi-Scenario Multi-Task Transfer Learning Model for Recommendations, IEEE Transactions on Knowledge and Data Engineering, 37(4): 1585-1598, 2025.
  22. Wenya Hu, Jia Wu, Quan Qian, GAFExplainer: Global View Explanation of Graph Neural Networks Through Attribute Augmentation and Fusion Embedding, IEEE Transactions on Knowledge and Data Engineering, 37(5): 2569-2583, 2025. [ code]
  23. Syed Shafat Ali, Ajay Rastogi, Tarique Anwar, Syed Afzal Murtaza Rizvi, Jian Yang, Jia Wu, Quan Z. Sheng, Generalized Local Prominence for Source Detection in Real-World Rumor Networks. IEEE Transactions on Knowledge and Data Engineering, 37(8): 4620-4634, 2025. [ data]
  24. Tong Liu, Jing Li, Jia Wu, Bo Du, Yibing Zhan, Dapeng Tao, Jun Wan, Facial Expression Recognition With Heatmap Neighbor Contrastive Learning. IEEE Transactions on Multimedia, 27: 4795-4807, 2025.
  25. Xusheng Zhao, Qiong Dai, Xu Bai, Jia Wu, Hao Peng, Huailiang Peng, Zhengtao Yu, Philip S. Yu, Reinforced GNNs for Multiple Instance Learning. IEEE Transactions on Neural Networks and Learning Systems, 36(4): 6693-6707, 2025. [ code]
  26. Wenya Hu, Jia Wu, Quan Qian, CiRLExplainer: Causality-Inspired Explainer for Graph Neural Networks via Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems, 36(6): 9970-9984, 2025.
  27. Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang, Enhancing Graph Neural Networks for Out-of-Distribution Graph Detection. IEEE Transactions on Neural Networks and Learning Systems, 36(10): 19255-19269, 2025.
  28. Da Ding, Youquan Wang, Haicheng Tao, Jia Wu, Jie Cao, A Dual-Discriminator Generative Adversarial Network for Anomaly Detection. IEEE Transactions on Neural Networks and Learning Systems, 36(10): 19285-19296, 2025.
  29. Bingbing Xie, Xiaoxiao Ma, Shan Xue, Jian Yang, Jia Wu, Hao Fan, Contrastive Multi-Knowledge Graph Learning for Fake News Detection, IEEE Transactions on Network Science and Engineering, 12(5): 3948-3961, 2025. [ code]
  30. Bilal Khan, Jia Wu, Jian Yang, Xiaoxiao Ma, Heterogeneous Hypergraph Neural Network for Social Recommendation using Attention Network. ACM Transactions on Recommender Systems, 3(3): 30:1-30:22, 2025.
  31. Zehao Wang, Jin Fan, Huifeng Wu, Danfeng Sun, Jia Wu, Representing Multiview Time-Series Graph Structures for Multivariate Long-Term Time-Series Forecasting, IEEE Transactions on Artificial Intelligence, 5(6): 2651-2662, 2024. [ data]
  32. Nasrin Shabani, Jia Wu, Amin Beheshti, Quan Z. Sheng, Jin Foo, Venus Haghighi, Ambreen Hanif, Maryam Shahabikargar, A Comprehensive Survey on Graph Summarization With Graph Neural Networks. IEEE Transactions on Artificial Intelligence, 5(8): 3780-3800, 2024.
  33. Yufei Liu, Jia Wu, Jie Cao, SBP-GCA: Social Behavior Prediction via Graph Contrastive Learning With Attention. IEEE Transactions on Artificial Intelligence, 5(9): 4708-4722, 2024. [ data]
  34. Malik Khizar Hayat, Shan Xue, Jia Wu, Jian Yang, Heterogeneous Hypergraph Embedding for Node Classification in Dynamic Networks. IEEE Transactions on Artificial Intelligence, 5(11): 5465-5477, 2024.
  35. Xiang Huang, Hao Peng, Dongcheng Zou, Zhiwei Liu, Jianxin Li, Kay Liu, Jia Wu, Jianlin Su, Philip S. Yu, CoSENT: Consistent Sentence Embedding via Similarity Ranking. IEEE Transactions on Audio, Speech and Language Processing, 32: 2800-2813, 2024. [ code]
  36. Xuelian Ni, Fei Xiong, Shirui Pan, Jia Wu, Liang Wang, and Hongshu Chen, Community preserving social recommendation with Cyclic Transfer Learning, ACM Transactions on Information Systems, 42(3): 67:1-67:36, 2024. [ data]
  37. Xixun Lin, Chuan Zhou, Jia Wu, Lixin Zou, Shirui Pan, Yanan Cao, Bin Wang, Shuaiqiang Wang, Dawei Yin, Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation, IEEE Transactions on Knowledge and Data Engineering, 36(4): 1815-1828, 2024. [ data]
  38. Bingbing Xie, Xiaoxiao Ma, Jia Wu, Jian Yang, Hao Fan, Knowledge Graph Enhanced Heterogeneous Graph Neural Network for Fake News Detection, IEEE Transactions on Consumer Electronics, 70(1): 2826-2837, 2024. [ code]
  39. Nasrin Shabani, Amin Beheshti, Alireza Jolfaei, Jia Wu, Venus Haghighi, Maryam Khanian Najafabadi, Jin Foo, Attention-Based Graph Summarization for Large-Scale Information Retrieval. IEEE Transactions on Consumer Electronics, 70(3): 6224-6235, 2024.
  40. Beihang Song, Jing Li, Jia Wu, Jun Chang, Jun Wan, Direction Prediction Redefinition: Transfer Angle to Scale in Oriented Object Detection, IEEE Transactions on Circuits and Systems for Video Technology, 34(12): 12894-12906, 2024.
  41. Tianpeng Liu, Jing Li, Jia Wu, Lefei Zhang, Jun Chang, Jun Wan, Lezhi Lian, Tracking With Saliency Region Transformer. IEEE Transactions on Image Processing, 33: 285-296, 2024.
  42. Jiaqian Ren, Hao Peng, Lei Jiang, Zhifeng Hao, Jia Wu, Shengxiang Gao, Zhengtao Yu, Qiang Yang, Toward Cross-Lingual Social Event Detection with Hybrid Knowledge Distillation, ACM Transactions on Knowledge Discovery from Data, 18(9): 229:1-229:36, 2024.
  43. Yuyao Wang, Jie Cao, Youquan Wang, Jia Wu, Yangyang Liu, Position Matters: Play a Sequential Game to Detect Significant Communities. IEEE Transactions on Knowledge and Data Engineering, 36(7): 3402-3416, 2024.
  44. Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Zhao Li, Jilong Wang, Philip S. Yu, Graph Structure Reshaping Against Adversarial Attacks on Graph Neural Networks, IEEE Transactions on Knowledge and Data Engineering, 36(11): 6344-6357,2024. [ code]
  45. Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu, Uncertainty-Guided Boundary Learning for Imbalanced Social Event Detection. IEEE Transactions on Knowledge and Data Engineering, 36(6): 2701-2715, 2024.
  46. Hao Ke, Dong Chen, Qiwei Yao, Yixin Tang, Jia Wu, Jessica Monaghan, Paul Sowman, David McAlpine, Deep factor learning for accurate brain neuroimaging data analysis on discrimination for structural MRI and functional MRI, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(4): 582-595, 2024.
  47. Xin Zhang, Zengmao Wang, Bo Du, Jia Wu, Xiao Zhang, Erli Meng, Deep Session Heterogeneity-Aware Network for Click Through Rate Prediction, IEEE Transactions on Knowledge and Data Engineering, 36(12): 7927-7939,2024.
  48. Xuexiong Luo, Sheng Zhang, Jia Wu, Hongyang Chen, Hao Peng, Chuan Zhou, Zhao Li, Shan Xue, Jian Yang, ReiPool: Reinforced Pooling Graph Neural Networks for Graph-Level Representation Learning. IEEE Transactions on Knowledge and Data Engineering, 36(12): 9109-9122, 2024. [ code]
  49. Zhenchang Xia, Nan Dong, Jia Wu, Chuanguo Ma, Multivariate Knowledge Tracking Based on Graph Neural Network in ASSISTments. IEEE Transactions on Learning Technologies, 17: 32-43, 2024.
  50. Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z Sheng, S Yu Philip, A Comprehensive Survey on Community Detection with Deep Learning, IEEE Transactions on Neural Networks and Learning Systems, 35(4): 4682-4702, 2024. [ code]
  51. Qian Li, Jianxin Li, Jiawei Sheng, Shiyao Cui, Jia Wu, Yiming Hei, Hao Peng, Shu Guo, Lihong Wang, Amin Beheshti, Philip S. Yu, A Survey on Deep Learning Event Extraction: Approaches and Applications. IEEE Transactions on Neural Networks and Learning Systems, 35(5): 6301-6321, 2024.
  52. Danfeng Sun, Junjie Hu, Huifeng Wu, Jia Wu, Jian Yang, Quan Z. Sheng, Schahram Dustdar, A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT. ACM Computing Surveys, 56(2): 50:1-50:37, 2024.
  53. Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z Sheng, Hui Xiong, Leman Akoglu, A Comprehensive Survey on Graph Anomaly Detection with Deep Learning, IEEE Transactions on Knowledge and Data Engineering, 35(12): 12012-12038, 2023. [ code]
  54. Jianxin Li, Qingyun Sun, Hao Peng, Beining Yang, Jia Wu, Philip S. Yu, Adaptive Subgraph Neural Network With Reinforced Critical Structure Mining, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(7): 8063-8080, 2023. [ code]
  55. Tarique Anwar, Surya Nepal, Cécile Paris, Jian Yang, Jia Wu, Quan Z. Sheng, Tracking the Evolution of Clusters in Social Media Streams, IEEE Transactions on Big Data, 9(2): 701-715, 2023. [ data]
  56. Pengbo Li, Hang Yu, Xiangfeng Luo, Jia Wu, LGM-GNN: A Local and Global Aware Memory-Based Graph Neural Network for Fraud Detection, IEEE Transactions on Big Data, 9(4): 1116-1127, 2023.
  57. Zhenyu Qiu, Jia Wu, Wenbin Hu, Bo Du, Guocai Yuan, Philip S. Yu, Temporal Link Prediction with Motifs for Social Networks, IEEE Transactions on Knowledge and Data Engineering, 35(3): 3145-3158, 2023.
  58. Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu, Signed Network Representation by Preserving Multi-order Signed Proximity, IEEE Transactions on Knowledge and Data Engineering, 35(3): 3087-3100, 2023. [ code]
  59. Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, Xindong Wu, A Comprehensive Survey on Automatic Knowledge Graph Construction, ACM Computing Surveys, 56(4): 62:1-62:94, 2023
  60. Lei Chen, Jie Cao, Haicheng Tao, Jia Wu, Trip Reinforcement Recommendation with Graph-based Representation Learning, ACM Transactions on Knowledge Discovery from Data, 17(4): 57:1-57:2, 2023. [ data]
  61. Tong Liu, Jing Li, Jia Wu, Bo Du, Jun Chang, Yi Liu, Facial Expression Recognition on the High Aggregation Subgraphs, IEEE Transactions on Image Processing, 32: 3732-3745, 2023.
  62. Chenglong Dai, Jia Wu, Jessica J. M. Monaghan, Guanghui Li, Hao Peng, Stefanie I. Becker, David McAlpine, Semi-Supervised EEG Clustering With Multiple Constraints, IEEE Transactions on Knowledge and Data Engineering, 35(11): 11301-11315, 2023. [ code]
  63. Yuyao Wang, Jie Cao, Zhan Bu, Jia Wu, Youquan Wang, Dual Structural Consistency Preserving Community Detection on Social Networks. IEEE Transactions on Knowledge and Data Engineering, 35(11): 11301-11315, 2023.
  64. Qian Li, Shu Guo, Jia Wu, Jianxin Li, Jiawei Sheng, Hao Peng, Lihong Wang, Event Extraction by Associating Event Types and Argument Roles, IEEE Transactions on Big Data, 9(6): 1549-1560, 2023.
  65. Guanghui Li, Jiahua Shen, Chenglong Dai, Jia Wu, Stefanie I. Becker, ShVEEGc: EEG Clustering With Improved Cosine Similarity-Transformed Shapley Value, IEEE Transactions on Emerging Topics in Computational Intelligence, 7(1): 222-236, 2023. [ data]
  66. Lei Chen, Jie Cao, Weichao Liang, Jia Wu, Qiaolin Ye, Keywords-enhanced Deep Reinforcement Learning Model for Travel Recommendation, ACM Transactions on Web, 17(1): 5:1-5:21, 2023. [ data]
  67. Tianpeng Liu, Jing Li, Jia Wu, Jun Chang, Beihang Song, Bowen Yao, Tracking With Mutual Attention Network, IEEE Transactions on Multimedia, 25: 5330-5343, 2023.
  68. Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip Yu, Weixiong Zhang, A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning, IEEE Transactions on Knowledge and Data Engineering, 35(2): 1149-1170, 2023.
  69. Xusheng Zhao, Qiong Dai, Jia Wu, Hao Peng, Mingsheng Liu, Xu Bai, Jianlong Tan, Senzhang Wang, Philip S. Yu, Multi-view Tensor Graph Neural Networks Through Reinforced Aggregation, IEEE Transactions on Knowledge and Data Engineering, 10.1109/TKDE.2022.3142179,35(4): 4077-4091, 2023. [ code]
  70. Xiaosai Huang, Jing Li, Jia Wu, Jun Chang, Donghua Liu, Transfer Learning With Document-Level Data Augmentation for Aspect-Level Sentiment Classification, IEEE Transactions on Big Data, 9(6): 1643-1657, 2023. [ data]
  71. Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Shan Xue, Qianli Xing, Philip S. Yu, C-DeepTrust: A Context-Aware Deep Trust Prediction Model in Online Social Networks, IEEE Transactions on Neural Networks and Learning Systems, 10(5): 2832-2842, 2023. [ data]
  72. Sanmin Liu, Shan Xue, Jia Wu, Chuan Zhou, Jian Yang, Zhao Li, Jie Cao, Online Active Learning for Drifting Data Streams, IEEE Transactions on Neural Networks and Learning Systems, 34(1): 186-200, 2023.
  73. Weichao Liang, Jie Cao, Lei Chen, Youquan Wang, Jia Wu, Amin Beheshti, Jiangnan Tang, Crime Prediction With Missing Data Via Spatiotemporal Regularized Tensor Decomposition IEEE Transactions on Big Data, 9(5): 1392-1407, 2023. [ data]
  74. Beihang Song, Jing Li, Jia Wu, Bo Du, Jun Chang, Jun Wan, Tianpeng Liu, SRDF: Single-Stage Rotate Object Detector via Dense Prediction and False Positive Suppression, IEEE Transactions on Geoscience and Remote Sensing, 61: 1-16, 2023.
  75. Danfeng Sun, Jianyong Zhao, Baiping Chen, Huifeng Wu, Jia Wu, Cross-Level Dependability Assessment With a Distributed Split Mechanism for Wireless Communication Systems, IEEE Transactions on Network Science and Engineering, 10(5): 2832-2842, 2023.
  76. Ge Zhang, Zhao Li, Jiaming Huang, Jia Wu, Chuan Zhou, Jian Yang, Jianliang Gao, eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks, ACM Transactions on Information Systems, doi.org/10.1145/3474379, 47:1-29, 2022. [ code]
  77. Xiaoxiao Ma, Shan Xue, Jia Wu, Jian Yang, Cecile Paris, Surya Nepal, Quan Z. Sheng, Deep Multi-Attributed-View Graph Representation Learning, IEEE Transactions on Network Science and Engineering, 9(5): 3762-3774, 2022. [ code]
  78. Qian Li, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Lihong Wang, S Yu Philip, Zheng Wang, Reinforcement Learning-Based Dialogue Guided Event Extraction to Exploit Argument Relations, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 10.1109/TASLP.2021.3138670, 30:520-533, 2022. [ code]
  79. Chenyan Zhang, Jing Li, Jia Wu, Donghua Liu, Jun Chang, Rong Gao, Deep Recommendation with Adversarial Training, IEEE Transactions on Emerging Topics in Computing, 10(4): 1966-1978, 2022. [ dataset]
  80. Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui, Blake Johnson, and Stefanie I. Becker, Electroencephalogram Signal Clustering with Convex Cooperative Games, IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2021.3060742, 34(12): 5755-5769, 2022. [ dataset]
  81. Donghua Liu, Jia Wu, Jing Li, Bo Du, Jun Chang, and Xuefei Li, Adaptive Hierarchical Attention-Enhanced Gated Network Integrating Reviews for Item Recommendation, IEEE Transactions on Knowledge and Data Engineering, 34(5):2076-2090, 2022. [ code]
  82. Chenglong Dai, Jia Wu, Dechang Pi, Stefanie I Becker, Lin Cui, Qin Zhang, and Blake Johnson, Brain EEG Time Series Clustering Using Maximum Weight Clique, IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2020.2974776, 52(1):357-371, 2022. [ dataset]( Highly Cited Paper)
  83. Danfeng Sun, Shan Xue, Huifeng Wu, Jia Wu, A Data Stream Cleaning System Using Edge Intelligence for Smart City Industrial Environments, IEEE Transactions on Industrial Informatics, 18(2):1165-1174, 2022.
  84. Zhongze Chen, Jing Li, Jia Wu, Jun Chang, Yafu Xiao, Xiaoting Wang, Drift-proof Tracking with Deep Reinforcement Learning, IEEE Transactions on Multimedia, DOI: 10.1109/TMM.2021.3056896, 24:609-624, 2022.
  85. Zhenchang Xia, Shan Xue, Jia Wu, Yanjiao Chen, Junjie Chen, and Libing Wu, Deep Reinforcement Learning for Smart City Communication Networks, IEEE Transactions on Industrial Informatics, 17(6):4188-4196, 2021.
  86. Danfeng Sun, Jia Wu, Jian Yang, Huifeng Wu, Intelligent Data Collaboration in Heterogeneous-device IoT Platforms, ACM Transactions on Sensor Networks, DOI: doi.org/10.1145/3427912, 17(3):1-17, 2021.
  87. Zhenchang Xia, Jia Wu, Libing Wu, Yanjiao Chen, Jian Yang, Philip S Yu, A Comprehensive Survey of the Key Technologies and Challenges Surrounding Vehicular Ad Hoc Networks, ACM Transactions on Intelligent Systems and Technology, DOI: doi.org/10.1145/3451984, 12(4):1-30, 2021.
  88. Chenglong Dai, Dechang Pi, Stefanie I Becker, Jia Wu, Lin Cui, Blake Johnson, CenEEGs: Valid EEG Selection for Classification, ACM Transactions on Knowledge Discovery from Data, DOI:doi.org/10.1145/3371153, 14(2):1-25, 2020.
  89. Yongshan Zhang, Jia Wu, Zhihua Cai, and Philip S. Yu, Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation, IEEE Transactions on Multimedia, 22(11):2844-2857, 2020. [ dataset]
  90. Haishuai Wang, Jia Wu, Xingquan Zhu, Yixin Chen, and Chengqi Zhang, Time-Variant Graph Classification, IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2018.2830792, 50(8):2883-2896, 2020.
  91. Lin Cui, Jia Wu, Dechang Pi, Peng Zhang, and Paul Kennedy, Dual Implicit Mining-Based Latent Friend Recommendation, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(5):1663-1678, 2020.
  92. Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, and Chengqi Zhang, Salient Subsequence Learning for Time Series Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(9):2193-2207, 2019. [ dataset]
  93. Haishuai Wang, Jia Wu, Peng Zhang, and Yixin Chen, Learning Shapelet Patterns from Network-based Time Series Data, IEEE Transactions on Industrial Informatics, 15(7):3864-3876, 2019.
  94. Yongshan Zhang, Jia Wu, Chuan Zhou, Zhihua Cai, Jian Yang, Philip S Yu, Multi-View Fusion with Extreme Learning Machine for Clustering, ACM Transactions on Intelligent Systems and Technology, 10(5):1-23, 2019.
  95. Jiayi Ma, Jia Wu, Ji Zhao, Junjun Jiang, Huabing Zhou, and Quan Z. Sheng, Nonrigid Point Set Registration With Robust Transformation Learning Under Manifold Regularization, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2018.2872528, 30(12):3584-3597, 2019. ( Highly Cited Paper)
  96. Liangxiao Jiang, Lungan Zhang, Chaoqun Li, and Jia Wu, A Correlation-based Feature Weighting Filter for Naive Bayes, IEEE Transactions on Knowledge and Data Engineering, 30(2):201-213, 2019. ( Highly Cited Paper)
  97. Huan Wang, Jia Wu, Wenbin Hu, Xindong Wu, Detecting and Assessing Anomalous Evolutionary Behaviors of Nodes in Evolving Social Networks, ACM Transactions on Knowledge Discovery from Data, 13(1):1-24, 2019.
  98. Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Xindong Wu, Multi-Instance Learning with Discriminative Bag Mapping, IEEE Transactions on Knowledge and Data Engineering, 30(6):1065-1080, 2018.
  99. Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Multiple Structure-View Learning for Graph Classification, IEEE Transactions on Neural Networks and Learning Systems, 29(7):3236-3251, 2017
  100. Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Xindong Wu, Positive and Unlabeled Multi-Graph Learning, IEEE Transactions on Cybernetics, 47(4):818-829, 2017. ( Highly Cited Paper)
  101. Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, and Chengqi Zhang, Task Sensitive Feature Exploration and Learning for Multitask Graph Classification, IEEE Transactions on Cybernetics, 47(3):744-758, 2017.
  102. Bo Du, Wei Xiong, Jia Wu, Lefei Zhang, and Dacheng Tao, Stacked convolutional denoising auto-encoders for feature representation, IEEE Transactions on Cybernetics, 47(4): 1017-1027, 2017. ( Highly Cited Paper)
  103. Ting Guo, Jia Wu, Xingquan Zhu, and Chengqi Zhang. Combining Structured Node Content and Topology Information for Networked Graph Clustering, ACM Transactions on Knowledge Discovery from Data, 11(3): 1-29, 2017.
  104. Shirui Pan, Jia Wu, and Xingquan Zhu, CogBoost: Boosting for Fast Cost-sensitive Graph Boosting Algorithm, IEEE Transactions on Knowledge and Data Engineering, 27(11): 2933-2946, 2015.
  105. Jia Wu, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Boosting for Multi-Graph Classification, IEEE Transactions on Cybernetics, 45(3): 430-443, 2015. ( Highly Cited Paper)
  106. Shirui Pan, Jia Wu, Xingquan Zhu, and Chengqi Zhang, Graph Ensemble Boosting for Imbalanced and Noisy Graph Stream Classification, IEEE Transactions on Cybernetics, 45(5): 940-954, 2015.
  107. Jia Wu, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Bag Constrained Structure Pattern Mining for Multi-Graph Classification, IEEE Transactions on Knowledge and Data Engineering, 26(10):2382-2396, 2014.
 Selected Professional Services
Associate Editors Research Track Chair
  • WWW-2026: The 35th International World Wide Web Conference, Dubai, United Arab Emirates, 2026
Survey Track Chair
  • IJCAI-2025: The 34th International Joint Conference on Artificial Intelligence, Canada, 2025
Demo Chair
  • WWW-2025: The 34th International World Wide Web Conference, Sydney, Australia, 2025
  • WSDM-2024: The 17th ACM Intl. Conf. on Web Search and Data Mining, Mexico, 2024
Symposium Chair
  • ICWS-2025: IEEE International Conference on Web Services, Finland, 2025
  • ICWS-2024: IEEE International Conference on Web Services, China, 2024
Encore Track Chair
  • ADC-2025: The 35th Australian Database Conference, Sydneyt, Australia, 2025
Proceeding Chair
  • ADMA-2024: The 20th International Conference Advanced Data Mining and Applications, Sydney, Australi, 2024
Shepherding Chair
  • ADC-2024: The 34th Australian Database Conference, Gold Coast, Australia, 2024
IEEE Computational Intelligence Society ECR Mentoring Program Co-chair
  • IEEE CIS:Student and Early Career Mentoring Program, Padua, Italy, 2022
Applied Track Chair
  • ICDM-2022: The 22nd IEEE International Conference on Data Mining, Orlando, FL, USA, 2022
Tutorial Chair
  • BigData-2021: The IEEE International Conference on Big Data, Orlando, FL, USA, 2021
Area Chair
  • NeurIPS-25: The 39th Annual Conference on Neural Information Processing Systems, CA, USA, 2025
  • IJCAI-25: The 34th International Joint Conference on Artificial Intelligence, Montreal, Canada, 2025
  • ICDM-24: The 24th IEEE International Conference on Data Mining, Orlando, Abu Dhabi, UAE, 2024
  • KDD-2023: The 29th ACM SIGKDD Intl. Conf. on Know. Discovery and Data Mining, CA, USA, 2023
  • ICDM-2022: The 22nd IEEE International Conference on Data Mining, Orlando, FL, USA, 2022
  • MM-2021: The 29th ACM International Conference on Multimedia, Chengdu, China, 2021
  • ICDM-2021: The 21th IEEE Intl. Conf. on Data Mining, Auckland, New Zealand, 2021
  • ICDM-2020: The 20th IEEE International Conference on Data Mining, Sorrento, Italy, 2020
Publicity Chair
  • ACSW-2019: The 42nd Australasian Computer Science Week, Sydney, Australia,, 2019
Contest Chair
  • ICDM-2019: The 19th International Conference on Data Mining, Beijing, China, 2019
Program Committee Co-Chair
  • ATIS-2018: International Conference on Applications and Techniques in Information Security, Nanning, China, 2018
Web Chair
  • ICBK-2018: The IEEE Conference on Big Search, Singapore, 2018
Senior Program Committee
  • CIKM-2025: The 34th ACM Intl. Conf. Information and Knowledge Management, Full Paper Track, Korea, 2025
  • WSDM-2025: The 18th ACM Intl. Conf. on Web Search and Data Mining, Germany, 2025       
  • CIKM -2024: The 33rd ACM Intl. Conf. Information and Knowledge Management, Full Paper Track, USA, 2024
  • WSDM-2024: The 17th ACM Intl. Conf. on Web Search and Data Mining, Mexico, 2024
  • WSDM-2023: The 16th ACM Intl. Conf. on Web Search and Data Mining, Singapore, 2023
  • WWW-2023: The 32nd International World Wide Web Conference, USA, 2023
  • CIKM-2023: The 32nd ACM Intl. Conf. Inf. Knowl. Manag., UK, Full Paper, 2023
  • CIKM-2023: The 32nd ACM Intl. Conf. Inf. Knowl. Manag., UK, Short Paper, 2023
  • PAKDD-2023: The 27th Pacific-Asia Conf. on Knowl. Discov Data Min., Japan, 2023
  • KDD-2022: The 28th ACM SIGKDD Intl. Conf. on Knowl. Discov Data Min., USA, 2022
  • WWW-2022: The 31st International World Wide Web Conference, Lyon, France, 2022
  • WSDM-2022: The 15th ACM Intl. Conf. on Web Search and Data Mining, AZ, USA, 2022
  • PAKDD-2022: The 26th Pacific-Asia Conf. on Knowl. Discov Data Min.,China, 2022
  • CIKM-2021: The 30th ACM Intl. Conf. Inf. Knowl. Manag., Gold Coast, Australia, Full Paper, 2021 
  • CIKM-2021: The 30th ACM Intl. Conf. Inf. Knowl. Manag., Gold Coast, Australia, Short Paper, 2021 
  • IJCAI-2021: The 30th Intl. Joint Conf. on Artificial Intelligence, Montreal, Canada, 2021  
  • PAKDD-2021: The 25th Pacific-Asia Conf. on Knowl. Discov Data Min., Delhi, India, 2021
  • IJCAI-2020: The 29th International Joint Conference on Artificial Intelligence, Yokohama, Japan, 2020
  • PAKDD-2020: The 24th Pacific-Asia Conference on Knowl. Discov Data Min., Singapore, 2020
  • IJCAI-2019: The 28th International Joint Conference on Artificial Intelligence, Macau, China, 2019 
  • PAKDD-2019: The 23rd Pacific-Asia Conf. on Knowl. Discov Data Min., Macau, China, 2019
  • IJCAI-2018: The 27th Intl. Joint Conference on Artificial Intelligence, Stockholm, Sweden, 2018
  • SDM-2018: The 18th SIAM International Conference on Data Mining, San Diego, USA, 2018
  • PAKDD-2018: The 22nd Pacific-Asia Conf. on Knowl. Discov Data Min., Melbourne, Australia, 2018
  • IJCAI-2017: The 26th Intl. Joint Conference on Artificial Intelligence, Melbourne, Australia, 2017
 Selected Grants

    I have secured $13+ million in research funding from both national research councils and industry as a Chief Investigator.

    My research achievement extends well beyond academia, significantly influencing industries. As the Research Director for the Applied AI Centre, my work has garnered widespread recognition, fostering extensive collaborations with leading companies such as AWS, Fujitsu, CSIRO, Domain, Locii Innovations Pty Ltd, Prospa Pty Ltd, and Yirigaa Pty Ltd, among others.

  • Jia Wu, ARC Future Fellowship (FT) 2025, "Next-Generation Graph-Level Mining for High-Complexity Data Environments", $1,173,569, 2026-2030.
  • Jia Wu, Jian Yang, Michael Sheng, ARC Discovery Project (DP) 2026, "Generative Graph Modelling for Anomaly Detection", $566,045, 2026-2029.
  • Jia Wu, Zitai Qiu, Digital Finance CRC, 2025, "Graph-based and AI-enhanced Detection of Misinformation in Social Media for Trustworthy Digital Finance", $15,000, 2025-2026
  • Jia Wu, Amin Beheshti, MQ Linkage Project (MQLP) 2024, "Mitigating Generative AI Deepfake Threats in Identity and Access Management Systems", $800,000, 2024-2028
  • Amin Beheshti, Jia Wu, et al, MQ Linkage Project (MQLP) 2024, "Next-Gen Banking: Towards Customized and Personalized Banking Solutions through Generative AI Technologies", $1,760,000, 2024-2030
  • Jia Wu, Zhenyu Yang, Digital Finance CRC, 2024, "Graph-Based Anomaly Detection for Financial Fraud Identification: Techniques and Applications", $15,000, 2024-2025
  • Jia Wu, Jian Yang, ARC Discovery Project (DP) 2023, "New Graph Mining Technologies to Enable Timely Exploration of Social Events", $380,610, 2023-2025.
  • Jia Wu, Jian Yang, Michael Sheng, Amin Beheshti, David McAlpine, Paul Sowman, ARC Linkage Project (LP) 2021, "Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective", $501,667, 2023-2026.
  • Jia Wu, ARC Discovery Early Career Researcher Award (DECRA) 2020, "Early Prediction in Large-scale Time-variant Information Networks", $427,068, 2020-2023
  • Jia Wu, Ge Zhang, Microsoft Research 2022, "Graph-level Anomaly Detection", $135,999, 2023-2025
 Teaching
  • Machine Learning (COMP8220).
  • Mining Unstructured Data (COMP8230)
  • Artificial Intelligence for Text and Vision (COMP3420/COMP6420)
  • Research Frontiers in Computing (COMP7900).
  • Data Science (COMP2200/COMP6200).
  • Big Data (COMP3210)
  • Research Frontiers in Computing (COMP7900)
  • Artificial Intelligence (COMP3160).
 Award and Honors