Welcome to Jia Wu's Homepage

  • Macquarie Univerity's Computer Science ranked in Top 162 Globally
  • Graph Neural Networks
  • 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

  • Social Networks and Graph Mining

  • Graph Neural Networks

  • Social Recommended Systems

  • Time Series Analysis

  • Deep Learning

  • Anomaly Detection

  • Brain Networks (EEG/MEG, MRI/fMRI)

  • Business Data Intelligence

 Recruiting Students

If you are interested in joining my team, please email (jia.wu@mq.edu.au) me.

Congratulations to Donghua Liu on her paper accepted by IEEE TKDE Journal (IF: 4.935)

Congratulations to Chenglong Dai on his paper accepted by IEEE TKDE Journal (IF: 4.935)

Congratulations to Zhenchang Xia on his paper accepted by IEEE TII Journal (IF: 9.112)

Tutorial Chair for the 2021 IEEE International Conference on Big Data (BigData-2021)

Area Chair for the 2021 IEEE International Conference on Data Mining (ICDM-2021)

Area Chair for the 2021 ACM International Conference on Multimedia (MM-2021)

Congratulations to Xixun Lin on his paper accepted by WWW 2021, Acceptance Rate 12.6%

Conferences
  1. 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]
  2. 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]
  3. 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]
  4. Pinghua Xu, Wenbin Hu, Jia Wu, and Weiwei Liu, Opinion Maximization in Social Trust Networks, the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), Yoko, Japan, 2020. [ code]
  5. 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 2020), Yoko, Japan, 2020. [ code]
  6. 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 2020), New York, USA, 2020.[ dataset]
  7. 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 2020),New York, USA.
  8. 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]
  9. 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]
  10. 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 (ACM KDD), USA, 2020.
  11. 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]
  12. 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 (IEEE ICDM), Sorrento, Italy, 2020. [ code]
  13. 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 (IEEE ICDM), Sorrento, Italy, 2020.
  14. 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 2019) , Macao, China, 2019
  15. 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 2019) , Macao, China, 2019.
  16. 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 2019) , Macao, China, 2019. [ code]
  17. 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]
  18. 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 (ACM KDD) , USA, 2019. [ code]
  19. 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 (IEEE ICDM), Beijing, China, 2019. [ code]
  20. 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 (IEEE ICDM), Beijing, China, 2019. [ code]
  21. 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 (IEEE ICDM), Beijing, China, 2019. [ code]
  22. 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 (IEEE ICDM), Beijing, China, 2019
  23. 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.
  24. 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]
  25. 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'18), Stockholm, Sweden, Jul 13-19, 2018.
  26. 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'18), Stockholm, Sweden, Jul 13-19, 2018.
  27. 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'18), Stockholm, Sweden, Jul 13-19, 2018.
  28. 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'18), Stockholm, Sweden, Jul 13-19, 2018.
  29. 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'18), New Orleans, Louisiana, USA, Feb 2-7, 2018.
  30. 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'18), New Orleans, Louisiana, USA, Feb 2-7, 2018. [ code]
  31. 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'18), Singapore, November 17-20, 2018. [ code]
  32. 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 '18), San Diego, California, USA, May 3-5, 2018. (Best Paper Award in Applied Data Science Track)
  33. 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.
  34. 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'17), San Francisco, USA, Feb 4-9, 2017.
  35. 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'16), Phoenix, Arizona, USA, Feb 12-17, 2016.
  36. 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]
  37. 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'17), Alaska, USA, May 14-19, 2017. [ code] (Best Stduent Paper Award)
  38. 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 '16) , Helsinki, Finland, May 16-20, 2016. [ code]
  39. 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'16), New York, USA, Jul 9-15, 2016.
  40. 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'16), New York, USA, Jul 9-15, 2016. [ code]
  41. Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu and Xingquan Zhu, Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness, Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, USA, Jul 9-15, 2016.
  42. 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'16), Barcelona, Spain, December 12-15, 2016.
  43. 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 '16) , Indianapolis, Indiana, USA, Oct 24-28, 2016.
  44. 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 '16) , Indianapolis, Indiana, USA, Oct 24-28, 2016.
  45. 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.
  46. 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'14), Shenzhen, China, Dec 14-17, 2014. (Best Paper Candidate)
  47. 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 '14) , Shanghai, China, Nov 3-7, 2014.
  48. 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.
  49. 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 '14), Philadelphia, Pennsylvania, USA, Apr 24-26, 2014.
  50. 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 '13), Dallas, Texas, USA, Dec 7-10, 2013.
Journals
  1. 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, To appear in 2021. [ code]
  2. 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, To appear in 2021. [ dataset]
  3. 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.
  4. 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, In-press, To appear in 2021. [ dataset]
  5. 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]
  6. 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.
  7. 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.
  8. 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]
  9. 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.
  10. 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)
  11. 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)
  12. Huan Wang, Jia Wu, Wenbin Hu, and Xindong Wu, Detecting and Assessing Anomalous Evolutionary Behaviors of Nodes in Evolving Social Networks, ACM Transactions on Knowledge Discovery from Data, DOI: 10.1145/3299886, 13(1):1-24, 2019. ( Highly Cited Paper)
  13. 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.
  14. Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, and Xingquan Zhu, A Novel Consistent Random Forest Framework: Bernoulli Random Forests, IEEE Transactions on Neural Networks and Learning Systems, 29(8):3510-3523, 2018
  15. 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
  16. 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)
  17. 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.
  18. 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)
  19. 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.
  20. 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.
  21. 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)
  22. 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.
  23. 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.
Associate Editors Tutorial Chair
  • BigData-2021: The IEEE International Conference on Big Data, Orlando, FL, USA, December 15-18, 2021
Area Chair
  • 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
  • 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
  • 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
PhD Students  

 

Naime Kermany

PhD. Stud.

Data Science

 

Fanzhen Liu

PhD. Stud.

Artificial Intelligence

 

Ge Zhang

PhD. Stud.

Artificial Intelligence

 

Qi Wang

PhD. Stud.

Data Science

 

Xiaoxiao Ma

PhD. Stud.

Data Science

 

Malik Hayat

PhD. Stud.

Data Science

 

Bilal Khan

PhD. Stud.

Data Science

 

Xing Su

PhD. Stud.

Data Science

 

Yang Guo

PhD. Stud.

Machine Learning

 

Qianli Xing

PhD. Stud.

Machine Learning

 

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
  • The Macquarie University Enterprise Partnerships Scheme, 04.2019-04.2020.
  • Macquarie University Research Seeding Grant, 01.2019-12.2020.
  • Data Science and Machine Learning (COMP8220).
  • Research Frontiers in Computing (COMP7900).
  • Data Science (COMP2200/COMP6200).
  • Artificial Intelligence (COMP3160).