Welcome to A/Prof Jia Wu's Homepage

Jia Wu is an Associate Professor (Professor in North America) in the School of Computing at Macquarie University.

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

A/Prof Wu is the Research Director for the Centre for Applied Artificial Intelligence, Macquarie University.

A/Prof Wu is an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

A/Prof Wu is an Associate Editor for the ACM Transactions on Knowledge Discovery from Data (TKDD).

A/Prof Wu and his research team are the recipient of Best Paper Runner-Up Award (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, School of Computing, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, Australia

Email: jia.wu@mq.edu.au

Visitor Globe

  • 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

  • International Research Scholarships now OPEN for 2024 commencement
    • Awards will only be available to applicants who, at the time of application
      • are a citizen of a country other than Australia or New Zealand, and not an Australian permanent resident
      • Closing Date: 31 July 2024
      • How to apply: Contact me first and make an online applications
  • Road to Research scholarships now OPEN for 2024 commencement
    • The Road to Research Scholarship is for onshore international applicants in Australia
      • are not an Australian or New Zealand citizen, or an Australian permanent resident
      • are onshore in Australia
      • Closing Date: 31 July 2024
      • How to apply: Contact me first and make an online applications
  • Project-based PhD Scholarships now OPEN for 2024 commencement
    • Graph Mining Theory
      • Research Topics: graph neural networks, graph representations, graph search, dynamic graph mining, multi-objective optimisation, deep reinforced learning
      • Closing Date: 31 July 2024
    • LLM and Knowledge Graphs
      • Research Topics: LLM, NLP, Text Mining, Knowledge Graphs
      • Closing Date: 31 July 2024
    • Graph Mining for Social Event Detection
      • Theoretical Research Topics: graph neural networks, graph representations, dynamic graph mining, deep reinforced learning
      • Applied Research Topics: event detection, NLP
      • Closing Date: 31 July 2024
    • Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective
      • Theoretical Research Topics: graph neural networks, time series, deep reinforced learning
      • Applied Research Topics: EEG/MEG data analysis, fMRI/DTI/MRI data analysis
      • Closing Date: 31 July 2024
    • 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

Congratulations to Xuexiong Luo for his JOURNAL paper accepted by IEEE TNNLS

Congratulations to Xuexiong Luo for his DEMO paper accepted by WSDM 2024

Congratulations to Yongshen Yu for his FULL paper accepted by IEEE BigData 2023

Congratulations to Malik Khizar Hayat for his FULL paper accepted by ICDM 2023

Congratulations to Xiaoxiao Ma for his FULL paper accepted by KDD 2023

Congratulations to Bilal Khan for his JOURNAL paper accepted by ACM TORS

Congratulations to Bingbing Xie for his JOURNAL paper accepted by IEEE TCE

Congratulations to Lingfeng Zhong for his SURVEY paper accepted by ACM CSUR

Congratulations to Xing Su for her paper accepted by WSDM 2023

Congratulations to Zhenyu Yang for his paper accepted by WSDM 2023

DEMO Chair for the 2024 ACM Intl. Conf. on Web Search and Data Mining (WSDM)

Area Chair for the 2023 ACM Intl. Conf. on Know. Discovery and Data Mining (KDD)

Senior PC for the 2023 International World Wide Web Conference (WWW)

Senior PC for the 2024 Pacific-Asia Conf. on Know. Discovery and Data Mining (PAKDD)

 Selected Publications
CompleteList: DBLP or Google
Conferences
  1. 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]
  2. 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]
  3. 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]
  4. 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]
  5. 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]
  6. 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]
  7. 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.
  8. 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]
  9. 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]
  10. 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.
  11. 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.
  12. 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]
  13. 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]
  14. 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]
  15. 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.
  16. 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]
  17. 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]
  18. 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]
  19. 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]
  20. 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]
  21. 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]
  22. 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]
  23. 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]
  24. 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]
  25. 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)
  26. 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]
  27. 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)
  28. 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)
  29. 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]
  30. 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)
  31. 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]
  32. 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.
  33. 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]
  34. 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]
  35. 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.
  36. 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]
  37. 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]
  38. 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.
  39. 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
  40. 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.
  41. 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]
  42. 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]
  43. 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]
  44. 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]
  45. 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]
  46. 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]
  47. 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
  48. 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.
  49. 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]
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. 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]
  56. 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]
  57. 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)
  58. 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.
  59. 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.
  60. 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.
  61. 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]
  62. 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)
  63. 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]
  64. 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.
  65. 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]
  66. 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.
  67. 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.
  68. 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.
  69. 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.
  70. 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)
  71. 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.
  72. 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.
  73. 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.
  74. 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. 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, In-press, 2024.
  2. Zehao Wang, Jin Fan, Huifeng Wu, Danfeng Sun, Jia Wu, Representing Multi-View Time-Series Graph Structures for Multivariate Long-Term Time-Series Forecasting, IEEE Transactions on Artificial Intelligence, 10.1109/TAI.2023.3326796, In-press, 2024. [ data]
  3. 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, doi.org/10.1145/3631115, In-press, 2024. [ data]
  4. 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, 10.1109/TKDE.2023.3304839, In-press, 2024. [ data]
  5. Bilal Khan, Jia Wu, Jian Yang, Xiaoxiao Ma, Heterogeneous Hypergraph Neural Network for Social Recommendation using Attention Network, ACM Transactions on Recommender Systems, doi.org/10.1145/3613964, In-press, 2024.
  6. 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, 10.1109/TCE.2023.3324661, In-press, 2024. [ code]
  7. 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
  8. 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, 10.1109/TKDE.2021.3118815, 35(12): 12012-12038, 2023. [ code]
  9. 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]
  10. 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]
  11. 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 Comput. Surv. 56(2): 50:1-50:37 (2024)
  12. 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.
  13. 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
  14. 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]
  15. 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.
  16. 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]
  17. 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.
  18. 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]
  19. 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]
  20. 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.
  21. 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]
  22. 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]
  23. 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, DOI: 10.1109/TNNLS.2021.3107948, 10(5): 2832-2842, 2023. [ dataset]
  24. 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, DOI: 10.1109/TNNLS.2021.3091681, 34(1): 186-200, 2023.
  25. 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. [ dataset]
  26. 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.
  27. 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]
  28. 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, 10.1109/TNNLS.2021.3137396, In-press, 2022. [ code]
  29. 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, 10.1109/TNSE.2022.3177307, 9(5): 3762-3774, 2022. [ code]
  30. 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]
  31. Chenyan Zhang, Jing Li, Jia Wu, Donghua Liu, Jun Chang, Rong Gao, Deep Recommendation with Adversarial Training, IEEE Transactions on Emerging Topics in Computing, 10.1109/TETC.2022.3141422, 10(4): 1966-1978, 2022. [ dataset]
  32. 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]
  33. 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, DOI: 10.1109/TKDE.2020.3010949, 34(5):2076-2090, 2022. [ code]
  34. 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)
  35. 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, DOI: 10.1109/TII.2021.3077865, 18(2):1165-1174, 2022.
  36. 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, DOI: 10.1109/TKDE.2021.3125148, In-press, 2022. [ code]
  37. 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, DOI: 10.1109/TKDE.2021.3108513, In-press, 2021.
  38. 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.
  39. 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, DOI: 10.1109/TKDE.2021.3104155, In-press, 2021.
  40. 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, DOI: 10.1109/TII.2020.3006199, 17(6):4188-4196, 2021.
  41. 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.
  42. 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.
  43. 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.
  44. 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, DOI:10.1109/TMM.2020.2966887, 22(11):2844-2857, 2020. [ dataset]
  45. 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.
  46. 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, DOI: 10.1109/TSMC.2017.2777889, 50(5):1663-1678, 2020.
  47. 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]
  48. 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.
  49. 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 , DOI: org/10.1145/3340268, 10(5):1-23, 2019.
  50. 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)
  51. 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, DOI: 10.1109/TKDE.2018.2836440, 30(2):201-213, 2019. ( Highly Cited Paper)
  52. 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 , DOI: doi.org/10.1145/3299886, 13(1):1-24, 2019.
  53. 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.
  54. 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
  55. 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)
  56. 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.
  57. 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)
  58. 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.
  59. 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.
  60. 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)
  61. 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.
  62. 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 Demo & Poster Chair
  • WSDM-2024: The 17th ACM Intl. Conf. on Web Search and Data Mining, Mexico, Mar 4-8, 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, Nov 28 - Dec 1, 2022
Tutorial Chair
  • BigData-2021: The IEEE International Conference on Big Data, Orlando, FL, USA, December 15-18, 2021
Area Chair
  • 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, Nov 28 - Dec 1, 2022
  • MM-2021: The 29th ACM International Conference on Multimedia, Chengdu, China, October 20-24, 2021
  • ICDM-2021: The 21th IEEE Intl. Conf. on Data Mining, Auckland, New Zealand, Nov 7-10, 2021
  • ICDM-2020: The 20th IEEE International Conference on Data Mining, Sorrento, Italy, November 17-20, 2020
Publicity Chair
  • ACSW-2019: The 42nd Australasian Computer Science Week, Sydney, Australia, January 29 - February 1, 2019
Contest Chair
  • ICDM-2019: The 19th International Conference on Data Mining, Beijing, China, November 8-11, 2019
Program Committee Co-Chair
  • ATIS-2018: International Conference on Applications and Techniques in Information Security, Nanning, China, November 9-11, 2018
Web Chair
  • ICBK-2018: The IEEE Conference on Big Search, Singapore, November 17-18, 2018
Senior Program Committee
  • WSDM-2024: The 17th ACM Intl. Conf. on Web Search and Data Mining, Mexico, Mar 4-8, 2024
  • WSDM-2023: The 16th ACM Intl. Conf. on Web Search and Data Mining, Singapore, Feb 27 - Mar 3, 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, May 25-18, 2023
  • KDD-2022: The 28th ACM SIGKDD Intl. Conf. on Knowl. Discov Data Min., USA, August 14-18, 2022
  • WWW-2022: The 31st International World Wide Web Conference, Lyon, France, April 25-29, 2022
  • WSDM-2022: The 15th ACM Intl. Conf. on Web Search and Data Mining, AZ, USA, Feb 21-25, 2022
  • PAKDD-2022: The 26th Pacific-Asia Conf. on Knowl. Discov Data Min.,China, May 16-19, 2022
  • CIKM-2021: The 30th ACM Intl. Conf. Inf. Knowl. Manag., Gold Coast, Australia, Nov 1-5, 2021, Full Paper  
  • CIKM-2021: The 30th ACM Intl. Conf. Inf. Knowl. Manag., Gold Coast, Australia, 2021, Short Paper  
  • IJCAI-2021: The 30th Intl. Joint Conf. on Artificial Intelligence, Montreal, Canada, August 21-26, 2021  
  • PAKDD-2021: The 25th Pacific-Asia Conf. on Knowl. Discov Data Min., Delhi, India, May 11-14, 2021
  • IJCAI-2020: The 29th International Joint Conference on Artificial Intelligence, Yokohama, Japan, July 11-17 2020
  • PAKDD-2020: The 24th Pacific-Asia Conference on Knowl. Discov Data Min., Singapore, May 11-14, 2020
  • IJCAI-2019: The 28th International Joint Conference on Artificial Intelligence, Macau, China, August 10-16, 2019 
  • PAKDD-2019: The 23rd Pacific-Asia Conf. on Knowl. Discov Data Min., Macau, China, April 14-17, 2019
  • IJCAI-2018: The 27th Intl. Joint Conference on Artificial Intelligence, Stockholm, Sweden, July 13-19, 2018
  • SDM-2018: The 18th SIAM International Conference on Data Mining, San Diego, USA, May 3-5, 2018
  • PAKDD-2018: The 22nd Pacific-Asia Conf. on Knowl. Discov Data Min., Melbourne, Australia, June 3-6, 2018
  • IJCAI-2017: The 26th Intl. Joint Conference on Artificial Intelligence, Melbourne, Australia, August 19-25, 2017
Program Committee
  • AAAI-2023: The 37th AAAI Conference on Artificial Intelligence,DC, USA, Feb 7-14, 2023
  • AAAI-2022: The 36th AAAI Conference on Artificial Intelligence, Vancouver, Canada, Feb 2 - Mar 1, 2022
  • IJCAI-2022: The 31st Intl. Joint Conf. on Artificial Intelligence, Vienna, Austria, July 23-29, 2022
  • KDD-2021: The 27th ACM SIGKDD Intl. Conf. on Knowl. Discov Data Min., Singapore, August 14-18, 2021
  • AAAI-2021: The 35th AAAI Conference on Artificial Intelligence, February 2-9, 2021
  • WWW-2021: The 30th International World Wide Web Conference, Ljubljana, Slovenia, April 19-23, 2021
  • ICDM-2020: The 20th IEEE International Conference on Data Mining, Sorrento, Italy, November 17-20, 2020
  • KDD-2020: The 26th ACM SIGKDDIntl. Conf. on Knowl. Discov Data Min., San Diego, USA, August 22-27, 2020
  • KDD-2019: The 25th ACM SIGKDD Intl. Conf. on Knowl. Discov Data Min., Anchorage, USA, August 3-7, 2019
  • AAAI-2019: The 33rd AAAI Conference on Artificial Intelligence, Honolulu, USA, January 27-February 1, 2019
  • ICDM-2019: The 19th IEEE International Conference on Data Mining, New York, USA, July 17-21, 2019
  • CIKM-2019: The 28th ACM Intl. Conf. Inf. Knowl. Manag., Beijing, China, November 3-7, 2019
  • KDD-2018: The 24th ACM SIGKDD Intl. Conf. on Knowl. Discov Data Min., London, UK, August 14-19, 2018
  • AAAI-2018: The 32nd AAAI Conference on Artificial Intelligence, New Orleans, USA, February 2-7, 2018
  • ICCS-2018: The 18th International Conference on Computational Science, Wuxi, China, June 11-13, 2018
  • ICDM-2018: The 18th IEEE International Conference on Data Mining, Singapore, November 17-20, 2018
  • CIKM-2018: The 27th ACM Intl. Conf. Inf. Knowl. Manag., Turin, Italy, October 22-26, 2018
  • AAAI-2017: The 31st AAAI Conference on Artificial Intelligence, San Francisco, USA, February 4-10, 2017
  • SDM-2017: The 17th SIAM International Conference on Data Mining, Houston, Texas, USA April 27-29, 2017
  • ICDM-2017: The 17th IEEE International Conference on Data Mining, New Orleans, USA, November 18-21, 2017
  • CIKM-2017: The 26th ACM Intl. Conf. Inf. Knowl. Manag., Singapore, November 6-10, 2017
  • ICCS-2017: The 17th International Conference on Computational Science, Trieste, Italy, July 3-6, 2017
  • PAKDD-2017: The 21st Pacific-Asia Conference on Knowl. Discov Data Min., Jeju, Korea, May 23-26, 2017
  • IJCNN-2017: The 31st IEEE Intl. Joint Conference on Neural Networks, Anchorage, USA, May 14-19, 2017
  • AAAI-2016: The 30th AAAI Conference on Artificial Intelligence, Phoenix, Arizona, USA, February 12–17, 2016
  • SDM-2016: The 16th SIAM International Conference on Data Mining, Florida, USA, May 5-7, 2016
  • DASFAA-2016: The 21st Intl. Conf. Database Syst. Adv. Appl., Dallas, USA, April 16-19, 2016
  • IJCNN-2016: The 30th IEEE Intl. Joint Conf. on Neural Networks, Vancouver, Canada, July 24-29, 2016
  • PAKDD-2016: The 20th Pacific-Asia Conf. Knowl. Discov Data Min., Auckland, New Zealand, April 19-22, 2016
  • PAKDD-2015: The 19th Pacific-Asia Conf. Knowl. Discov Data Min., Ho Chi Minh City, Vietnam, May 19-22, 2015
  • ICTAI-2014: The 26th IEEE Intl. Conf. on Tools with AI, Limassol, Cyprus, November 10-12, 2014
 Team Members
PhD Students  

 

Naime Kermany

PhD. Stud.

Machine Learning

 

Fanzhen Liu

PhD. Stud.

Machine Learning

 

Ge Zhang

PhD. Stud.

Machine Learning

 

Yuchen Zhang

PhD. Stud.

Data Science

 

Xiaoxiao Ma

PhD. Stud.

Machine Learning

 

Malik Hayat

PhD. Stud.

Data Science

 

Bilal Khan

PhD. Stud.

Data Science

 

Xing Su

PhD. Stud.

Data Science

 

Xuexiong Luo

PhD. Stud.

Data Science

 

Bingbing Xie

PhD. Stud.

Machine Learning

 

Zhuozhu Liu

PhD. Stud.

Machine Learning

 

Lingfeng Zhong

PhD. Stud.

Machine Learning

 

 

Master of Research Students  

 

Zhenyu Yang

MRes Y2. Stud.

Machine Learning

 

Zitai Qiu

MRes Y2. Stud.

Machine Learning

 

Yongsheng Yu

MRes Y2. Stud.

Machine Learning

 

Shichen Luo

MRes Y2. Stud.

Data Science

 

Alumni  
  • Master of Research, Xiaoxiao Ma, Macquarie University, Australia
  • Master of Research, Naime Ranjbar Kermany, Macquarie University, Australia
  • Master of Research, Fanzhen Liu, Macquarie University, Australia
  • PhD, Zizhu Zhang, Macquarie University, Australia
  • PhD, Qi Wang, Macquarie University, Australia
  • PhD, Yang Guo, Macquarie University, Australia
  • PhD, Qianli Xing, Macquarie University, Australia
  • PhD, Samira Ghodratnama, Macquarie University, Australia
 Grants
  • The Macquarie University Enterprise Partnerships Scheme, 04.2019-04.2020.
  • Macquarie University Research Seeding Grant, 01.2019-12.2020.
 Teaching
  • Data Science and Machine Learning (COMP8220).
  • Research Frontiers in Computing (COMP7900).
  • Data Science (COMP2200/COMP6200).
  • Artificial Intelligence (COMP3160).
 Award and Membership