Dr. Guanfeng Liu (PhD)
Senior Lecturer (Associate Professor in North America)
Course Director for Stream "Data Science"
 Deputy Director of Master by Research
 IEEE Senior Member
School of Computing
Macquarie University
Sydney, Australia, 2109

Office: BD Building, Level 3
Email: guanfeng.liu [at] mq.edu.au
Tel: +61-2-9850-9542
Fax: +61-2-9850-9551

Dr. Guanfeng Liu is a Senior Lecturer in School of Computing , Macquarie University, Sydney, Australia. Guanfeng got his PhD in computer science from Macquarie University in 2013. His research interests include graph database, trust management, and social network mining.


Research Interests and Projects

MRes and PhD Scholarships
I am seeking highly motivated and focused students with Backgrounds & Interests in Computer Science, Mathematics, and Engineering.

Honors and Awards
Research Supervision

Complete Students Current Students Visitors

Research Grants

Selected Publications

International Journal Papers
  1. X. Liu, Y. Hao, L. Zhao, G. Liu, V. Sheng and P. Zhao, LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning, ACM Transactions on Knowledge Discovery from Data (ACM TKDD),Vol. 18, Issue 7, pp. 1-24, 2024.
  2. C. Chen, J. Cui, G. Liu, J. Wu and L. Wang, Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications, International Journal of Machine Learning and Cybernetics, Volume 15, pp. 3513-3532, 2024.
  3. C. Long, H. Yuan, J. Fang, X. Xian, G. Liu, V. Sheng and P. Zhao, Learning Global and Multi-granularity Local Representation with MLP for Sequential Recommendation, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), Vol 18, Issue 4, pp. 1-15, 2024.
  4. H. Du, H. Yuan, P. Zhao, D. Wang, V. Sheng, Y. Liu, G. Liu and L. Zhao, Feature-aware Contrastive Learning with Bidirectional Transformers for Sequential Recommendation, IEEE Transactions on Knowledge and Data Engineering (TKDE), (accepted in 2023).
  5. C. Wu, H. Yuan, P. Zhao, J. Qu, V. Sheng and G. Liu, Dual-Supervised Contrastive Learning for Bundle Recommendation, IEEE Transactions on Computational Social Systems (TCSS), Vol. 11, Issue 3, pp. 3955-3965, 2024.
  6. Y. Hao, P. Zhao, X. Xian, G. Liu, L. Zhao, Y. Liu, V. Sheng and X. Zhou, Learnable Model Augmentation Contrastive Learning for Sequential Recommendation, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 36, Issue 8, pp. 3963-3976, 2024.
  7. L. Sun, M. Liu, G. Liu, X. Chen and X. Yu, FD-TGCN: Fast and Dynamic Temporal Graph Convolution Network for Traffic Flow Prediction, Information Fusion, Volume 106, June 2024
  8. Y. Hao, T. Zhang, P. Zhao, Y. Liu, V. Sheng, J. Xu, G. Liu and X. Zhou, Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential Recommendation, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 35, Issue 10, pp. 10112-10124, 2023.
  9. P. Ding, Y. Wang, G. Liu and X. Zhou, Few-Shot Semantic Relation Prediction across Heterogeneous Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 35, Issue, 10, 2023.
  10. F. Wang, G. Li, Y. Wang, W. Rafique, M. Khosravi, G. Liu, Y. Liu and L. Qi, Privacy-aware Traffic Flow Prediction based on Multi-party Sensor Data with Zero Trust in Smart City, ACM Transactions on Internet Technology (TOIT) Vol. 23, Issue 3, pp. 1-19, 2023.
  11. P. Zhao, Y. Fang, G. Liu, Y. Liu, V. S. Sheng, L. Zhao and X. Zhou, A Quaternion-Based Graph Convolution Network for Recommendation, World Wide Web Journal 26, 2835-2854, 2023.
  12. J. Lu, X. Zhan, G. Liu, X. Zhan and X. Deng, BSTC: A Fake Review Detection Model Based on a Pre-Trained Language Model and Convolutional Neural Network, Electronics,Vol. 12, No. 10, May 2023.
  13. P. Ding, G. Liu, Y. Wang, K. Zheng and X. Zhou, MCTS: Adaptive Monte Carlo Tree Search for Temporal Path Discovery, IEEE Transactions on Knowledge and Data Engineering (TKDE),Vol. 15, pp. 2243-2257, March 2023.
  14. G. Sun, G. Liu, Y. Wang, M. A Orgun, Q. Z. Sheng and X. Zhou, Partition-Aware Graph Pattern based Node Matching with Updates, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 35, Issue 2, pp. 1922-1937, February 2023.
  15. F. Zhu, Y. Wang, J. Zhou, C. Chen, L. Li and G. Liu, A Unified Framework for Cross-Domain and Cross-System Recommendations, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 35, Issue 2, pp. 1171-1184, February 2023.
  16. Y. Hao, J. Ma, P. Zhao, G. Liu X. Xian, L. Zhao and V.S. Sheng, Multi-dimensional Graph Neural Network for Sequential Recommendation, Pattern Recognition, Vol. 139, July 2023.
  17. M. Liu, G. Liu and L. Sun, Spatial-Temporal Dependence and Similarity Aware Traffic Flow Forecasting, Information Sciences, Vol. 625, pp. 81-96, May 2023.
  18. T. Yu, G. Liu, A. Liu, Z. Li and L. Zhao, LIFOSS: A Learned Index Scheme for Streaming Scenarios, World Wide Web Journal, Vol. 26, Issue 1, January 2023.
  19. Y. Li, Y. Hao, P. Zhao, G. Liu, Y. Liu, V. S. Sheng and X. Zhou, Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation, ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 17, Issue 6, April 2023
  20. G. Liu, L. Li, G. Liu and X. Wu, Social Group Query Based on Multi-Fuzzy-Constrained Strong Simulation, ACM Transactions on Knowledge Discovery from Data (TKDD) Vol. 16, Issue 3, pp. 1-27, 2022.
  21. B. Zheng, L. Ming, Q. Hu, Z. Lv, G. Liu and X. Zhou, Supply-Demand-aware Deep Reinforcement Learning for Dynamic Fleet Management, ACM Transactions on Intelligent Systems and Technology (TIST) Vol. 13, Issue 3, pp. 1-19, 2022.
  22. X. Chen, Y. Zhao, G. Liu, R. Sun and X. Zhou, Efficient Similarity-aware Influence Maximization in Geo-social Network, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 34, Issue 10, pp. 4767-4780, 2022.
  23. Y. Zhou, J. Liu, H. Wang, J. Wang, G. Liu, D. Wu, C. Li and and S. Yu, USST: A Two-Phase Privacy-Preserving Framework for Personalized Recommendation with Semi-Distributed Training, Information Sciences, Vol. 606, pp. 688-701, August 2022.
  24. A. Liu, Y. Zhang, X. Zhang, G. Liu, Y. Zhang, Z. Li, L. Zhao, Q. Li and X. Zhou, Representation Learning With Multi-Level Attention for Activity Trajectory Similarity Computation, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 34, Issue 5, pp. 2387-2400, 2022.
  25. G. Sun, G. Liu, Y. Wang, M. A. Orgun, Q. Z. Sheng and X.Zhou, Incremental Graph Pattern based Node Matching with Multiple Updates, IEEE Transactions on Knowledge and Data Engineering (TKDE) Vol. 33, Issue 4, pp. 1585-1600, 2021.
  26. Y. Zhang, G. Liu, A. Liu, Y. Zhang, Z. Li, X. Zhang and Q. Li, Personalized Geographical Influence Modeling for POI Recommendation, IEEE Intelligent Systems, Vol.35, Issue 5, 2020.
  27. G. Liu, Y. Wang, Z. Li, B. Zheng and K. Zheng, Strong Social Graph Based Trust-Oriented Graph Pattern Matching with Multiple Constraints, IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), pp.675-685, June 2020.
  28. K. Zheng, Y. Zhao, D. Lian, B. Zheng, G. Liu, X. Zhou, Reference-Based Framework for Spatio-Temporal Trajectory Compression and Query Processing, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 32, Issue 11, pp. 2227-2240, 2020.
  29. G. Li, Q. Chen, B. Zheng, N. Hung, P. Zhoun and G. Liu, Time-Aspect-Sentiment Recommendation Models Based on Novel Similarity Measure Methods, ACM Transactions on Web (TWEB), Vol. 14, Issue 2, pp. 1-26, 2020.
  30. A. Zhao, G. Liu, B. Zheng, Y. Zhao and K. Zheng, Temporal Paths Discovery with Multiple Constraints in Attributed Dynamic Graphs, World Wide Web Journal 23:313–336, 2020.
  31. Z. Yang, B. Zheng, G. Li, N. Hung, G. Liu and K. Zheng, Searching Activity Trajectories by Exemplar, ACM Transactions on Data Science (TDS) Vol. 1, Issue 3, pp. 1-19, 2020.
  32. G. Liu, Q. Shi, K. Zheng, A. Liu, Z. Li and X. Zhou, An Efficient Method for Top-K Graph Based Node Matching, World Wide Web Journal 22(3): 945-966, May 2019.
  33. G. Liu, K. Zheng, A. Liu, Z. Li, Y. Wang and X. Zhou, MCS-GPM: Multi-Constrained Simulation Based Graph Pattern Matching in Contextual Social Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE) 30(6), June, 2018.
  34. G. Liu, Y. Liu, K. Zheng, Z. Li, A. Liu, Y. Wang and X. Zhou, Context-Aware Trust Network Extraction in Large-Scale Trust-Oriented Social Networks, World Wide Web Journal21(3): 713-738, May, 2018.
  35. Y. Zhao, G. Liu, K. Zheng, A. Liu, Z. Li and X. Zhou, A Context-Aware Approach for Trustworthy Worker Selection in Social Crowd, World Wide Web Journal 20(6): 1211-1235, 2017.
  36. G. Liu, F. Zhu, K. Zheng, A. Liu, Z. Li, L. Zhao and X. Zhou, TOSI: A Trust-Oriented Social Influence Evaluation Method in Contextual Social Networks, Neurocomputing Vol 201, 130-140, 2016.
  37. Y. Wang, L. Li and G. Liu, Social Context-Aware Trust Inference for Trust Enhancement in Social Network based Recommendations on Service Providers, World Wide Web Journal Vol.18, Issue 1, 2015.
  38. G. Liu, Y. Wang, M. A. Orgun and E. P. Lim, Finding the Optimal Social Trust Path for the Selection of Trustworthy Service Providers in Complex Social Networks, IEEE Transactions on Services Computing (TSC), Volume 6, Issue 2, 2013.
  39. Y. Hao, G. Liu and N. Wen, An Enhanced Load Balancing Mechanism Based on Deadline Control on GridSim, Future Generation Computer Systems, Vol.28, No.4, April, 2012.
International Conference Papers
  1. Y. Hao, F. Zhuang, D. Wang, G. Liu, V. Sheng and P. Zhao, A General Strategy Graph Collaborative Filtering for Recommendation Unlearning, CIKM2024.
  2. H. Xue, Q. Ma, G. Liu, J. Qu, Y. Liu and A. Liu, CLR2G: Cross modal Contrastive Learning on Radiology Report Generation, CIKM2024.
  3. Y. Liu, G. Liu, Q. Ma, Z. Li, S. Wen, L. Zhao and A. Liu KMCT: k-Means Clustering of Trajectories Efficiently in Location-Based Services, CIKM2024.
  4. H. Li, W. Wei, G. Liu, J. Liu, F. Jiang and J. Du, Intent Distribution based Bipartite Graph Representation Learning, SIGIR2024.
  5. L. Zhang, C. Li, Y. Lei, Z. Sun and G. Liu, An Empirical Analysis on Multi-turn Conversational Recommender Systems, SIGIR2024.
  6. H. Li, Z. Cheng, X. Yu, J. Liu, G. Liu and J. Du, Behavior Pattern Mining-based Multi-Behavior Recommendation, SIGIR2024.
  7. R. Xu, G. Liu, Y. Wang, X. Zhang, K. Zheng and X. Zhou, Adaptive Hypergraph Network for Trust Prediction, ICDE 2024.
  8. Y. Hao, P. Zhao, J. Qu, L. Zhao, G. Liu, F. Zhuang, V. Sheng and X. Zhou, Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering, ICDE 2024.
  9. Y. Hao, P. Zhao, J. Fang, J. Qu, G. Liu, F. Zhuang, V. Sheng and X. Zhou, Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation, ICDE 2024.
  10. X. Qin, H. Yuan, P. Zhao, G. Liu, F. Zhuang and V. Sheng, Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation, WSDM 2024.
  11. P. Ding, Y. Wang and G. Liu, Cross-heterogeneity Graph Few-shot Learning, CIKM 2023.
  12. H. Yuan, P. Zhao, X. Xian, G. Liu, Y. Liu, V. S. Sheng and L. Zhao, Sequential Recommendation with Probabilistic Logical Reasoning, IJCAI 2023.
  13. H. Du, H. Yuan, P. Zhao, F. Zhuang, G. Liu, L. Zhao, Y. Liu and V. S. Sheng, Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation, SIGIR 2023.
  14. X. Qin, H. Yuan, P. Zhao, J. Fang, F. Zhuang, G. Liu, Y. Liu and V. S. Sheng, Meta-optimized Contrastive Learning for Sequential Recommendation, SIGIR 2023.
  15. X. Du, H. Yuan, P. Zhao, J. Qu, F. Zhuang, G. Liu, Y. Liu and V. S. Sheng, Frequency Enhanced Hybrid Attention Network for Sequential Recommendation, SIGIR 2023.
  16. X. Du, H. Yuan, P. Zhao, J. Fang, G. Liu, Y. Liu, V. S. Sheng and X. Zhou, Contrastive Enhanced Slide Filter Mixer for Sequential Recommendation, ICDE 2023 (research track).
  17. F. Zhu, M. Zhong, X. Yang, L. Li, L. Yu, T. Zhang, J. Zhou, C. Chen, F. Wu, G. Liu and Y. Wang, DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation, ICDE 2023 (industry track).
  18. A. Anwar, I. Younis, G. Liu, A. Beheshti and X. Zhang, A Cricket-based Selection Hyper-heuristic for Many-objective Optimization Problems, ADMA 2022.
  19. R. Xu, G. Liu, X. Hua, S. Ye, X. Zhang and J. Lu, Attention-aware Multi-hop Trust Inference in Online Social Networks, DSAA 2022.
  20. X. Xu, A. Liu, G. Liu, J. Xu and L. Zhao, Acceptance-aware Multi-Platform Cooperative Matching in Spatial Crowdsourcing, ICSOC 2022.
  21. X. Xu, An Liu, G. Liu, Z. Li and L. Zhao, Drive Less but Finish More: Food Delivery based on Multi-Level Workers in Spatial Crowdsourcing, CIKM 2022.
  22. H. Du, H. Shi, P. Zhao, D. Wang, V. S. Sheng, Y. Liu, G. Liu and L. Zhao, Contrastive Learning with Bidirectional Transformers for Sequential Recommendation, CIKM 2022.
  23. M. Huang, P. Zhao, X. Xian, J. Qu, G. Liu, Y. Liu, and V. S. Sheng, Help from Meta-Path: Node and Meta-Path Contrastive Learning for Recommender Systems, IJCNN 2022.
  24. Y. Fang, P. Zhao, X. Xian, J. Fang, G. Liu, Y. Liu and V. S. Sheng, Quaternion-Based Graph Contrastive Learning for Recommendation, IJCNN 2022.
  25. C. Niu, A. Liu, G. Liu, J. Xu and L. Zhao, Representation Learning Based Query Decomposition for Batch Shortest Path Processing in Road Networks, ICSOC 2021.
  26. F. Zhu, Y. Wang, C. Chen, J. Zhou, L. Li and G. Liu, Cross-Domain Recommendation: Challenges, Progress, and Prospects, IJCAI 2021.
  27. G. Sun, G. Liu, Y. Wang and X. Zhou, Updates-Aware Graph Pattern based Node Matching, ICDE 2020.
  28. Y. Zhang, A. Liu, G. Liu, Z. Li and Q. Li, Deep Representation Learning of Activity Trajectory Similarity Computation, ICWS 2019.
  29. H. Wang, G. Liu, Y. Zhao, B. Zheng, P. Zhao and K. Zheng, A Dynamic Multi-faceted Fine-grained Preference Model for Recommendation, ICDM 2019.
  30. P. Ding, G. Liu, P. Zhao, A. Liu, Z. Li and K. Zheng, Reinforcement Learning Based Monte Carlo Tree Search for Temporal Path Discovery, ICDM 2019.
  31. H. Wang, G. Liu, A. Liu, Z. Li and K. Zheng, DMRAN:A Hierarchical Fine-Grained Attention-Based Network for Recommendation, IJCAI 2019.
  32. J. Xia, Y. Zhao, G. Liu, J. Xu, M. Zhang and K. Zheng, Profit-driven Task Assignment in Spatial Crowdsourcing, IJCAI 2019.
  33. T. Zhang, P. Zhao, Y. Liu, V. S. Sheng, J. Xu, D. Wang, G. Liu and X. Zhou, Feature-level Deeper Self-Attention Network for Sequential Recommendation, IJCAI 2019.
  34. Y. Zhao, J. Xia, G. Liu, H. Su, D. Lian, S. Shang and K. Zheng, Preference-aware Task Assignment in Spatial Crowdsourcing, AAAI 2019.
  35. G. Sun, G. Liu, Y. Wang, M. A Orgun, and X. Zhou, Incremental Graph Pattern Based Node Matching, ICDE 2018.
  36. F. Zhu, Y. Wang, C. Chen, G. Liu, M. A. Orgun, and J. Wu, A Deep Framework for Cross-Domain and Cross-System Recommendations, IJCAI 2018.
  37. J. Shi, G. Liu, Z. Li, A. Liu and K. Zheng, A Multi-Constrained Temporal Path Query System, ER 2018.
  38. Q. Shi, G. Liu, Z. Li, A. Liu, K. Zheng, L. Zhao and X. Zhou, Pattern Based Top-K Designed Nodes Finding in Contextual Social Graphs, ICWS 2017.
  39. M. Hu, Z. Li, Y. Shen, A. Liu, G. Liu, K. Zheng and L. Zhao, CNN- IETS: A CNN-based Probabilistic Approach for Information Extraction by Text Segmentation, CIKM 2017.
  40. F. Zhu, G. Liu, Y. Wang, M. A Orgun, A. Liu, Z. Li and K. Zheng, A Robust Approach to Finding Trustworthy Influencers in Social E-Commerce Environments, ICSOC 2016.
  41. G. Liu, Y. Wang, M. A Orgun, X. Zheng, A. Liu, Z. Li and K. Zheng, Strong Social Component-Aware Trust Sub-network Extraction in Contextual Social Networks, ICWS 2016.
  42. F. Zhu, G. Liu, Y. Wang, An Liu, Zhixu Li, P. Zhao and L. Li, A Context-Aware Trust-Oriented Influencers Finding in Online Social Networks, ICWS 2015.
  43. G. Liu, K. Zheng, Y. Wang, M. A. Orgun, A. Liu, L. Zhao and X. Zhou, Multi-Constrained Graph Pattern Matching in Large-Scale Contextual Social Graphs, ICDE 2015.
  44. G. Liu, A. Liu, Y. Wang and L. Li, An Efficient Multiple Trust Paths Finding Algorithm for Trustworthy Service Provider Selection in Real-Time Online Social Network Environments, ICWS 2014.
  45. G. Liu and Y. Wang, Social Context-Aware Trust Network Discovery in Complex Contextual Social Networks, AAAI 2012.
  46. G. Liu, Y. Wang and M. A. Orgun, Social Context-Aware Trust Network Discovery in Complex Contextual Social Networks, TrustCom 2012.
  47. G. Liu, Y. Wang, M. A. Orgun and H. Liu, Discovery Trust Networks for the Selection of Trustworthy Service Providers in Complex Contextual Social Networks, ICWS 2012.
  48. G. Liu, Y. Wang and M. A. Orgun, Trust Transitivity in Complex Social Networks, AAAI 2011.
  49. G. Liu, Y. Wang and M. A. Orgun, Finding K Optimal Social Trust Paths for Trustworthy Service Provider Selection in Complex Social Networks, ICWS 2011.
  50. G. Liu, Y. Wang and M. A. Orgun, Optimal Social Trust Path Selection in Complex Social Networks, AAAI 2010.
  51. G. Liu, Y. Wang, M. A. Orgun and E. P. Lim, A Heuristic Algorithm for Trust-Oriented Service Provider Selection in Complex Social Networks, SCC 2010. (Best Paper Award)
  52. G. Liu, Y. Wang and M. A. Orgun, Quality of Trust for Social Trust Path Selection in Complex Social Networks, AAMAS 2010.

Working and Visiting
  • Senior Lecturer, Macquarie University, Sydney, Australia, January 2022 - now
  • Lecturer/Assistant Professor, Macquarie University, Sydney, Australia, June 2018 - December 2021
  • Associate Professor, Soochow University, China, October 2013 - June 2017

Teaching
  • Data Science II, Macquarie University, S2 2022 (for Optus, Lecturer)
  • Data Science, Macquarie University, S2 2022, 2023 (for Postgraduate Students, Lecturer)
  • Mining Unstructured Data, Macquarie University, S1 2020, 2021, 2022, 2023 (for Postgraduate Students, Unit Convenor and Lecturer)
  • Big Data Technology, Macquarie University, S2 2019, 2020, 2021, 2022, 2023, 2024 (for Postgraduate Students, Unit Convenor and Lecturer)
  • Introduction to Systems Design and Data Management, Macquarie University, S1 2019, 2020, 2021 (for Undergraduate Students, Lecturer)
  • Advanced System and Network Security, Macquarie University, S2 2018 (for Postgraduate Students, Lecturer)
  • Enterprise Systems Integration, Macquarie University, S2 2018, S2 2019 (for Undergraduate Students, Lecturer)
  • Advanced Technology for High Dimensional Data, The University of Queensland, S1 2018 (for Postgraduate Students, Course Coordinator and Lecturer)
  • Information Retrieval and Web Search, The University of Queensland, S2 2017 (for Postgraduate Students, Course Coordinator and Lecturer)
  • Database System Concepts, Soochow University, S1 2015, 2017 (Lecturer)
  • Advanced Database Technology, Soochow University, S2 2014, 2015, 2016 (Lecturer)
  • Web Information Development, Soochow University, S1 2014 (Lecturer)
  • Web Technology, Macquarie University, 2013 (Lecturer)
  • Applications Modelling and Development, Macquarie University, 2010 (Lecturer)

Professional Services
  • Co-EIC, EAI Endorsed Transactions on Cloud Systems, EUDL, Since 2020.
  • Associate Editor, Human-centric Computing and Information Sciences (HCIS), Since 2021.
  • Associate Editor, Frontiers in Big Data, Frontiers, Since 2018.
  • Editorial Board, Computer, Materials & Continua (CMC), Tech Science Press, Since 2024.
  • Editorial Board, Electronics, MDPI, Since 2021.
  • General Co-Chair, IEEE DSAA2023 Special Session: Private, Secure, and Trust Data Analytics (PSTDA2023), 9-13 October, 2023, Thessaloniki, Greece.
  • General Co-Chair, IEEE DSAA2022 Special Session: Private, Secure, and Trust Data Analytics (PSTDA2022), 13-16 October, 2022, Shenzhen, China.
  • General Co-Chair, The 3rd International Workshop on Privacy, Security, and Trust in Computational Intelligence (PSTCI2021) in conjunction with CIKM 2021, 1-5 November, 2021, Queensland, Australia.
  • General Co-Chair, The 9th EAI International Conference on Cloud Computing (CloudComp2019), 4-5 December, 2019, Sydney, NSW, Australia.
  • General Co-Chair, The International Workshop on Web Information Systems in the Era of AI in conjunction with WISE 2019, 26-30 November, 2019, Hong Kong, China.
  • Guest Editor:
    • 2024: Current Genomics (Q3), Electronics (Q2)
    • 2023: Applied Sciences (Q2), Electronics (Q2)
    • 2022: Applied Sciences (Q2)
    • 2021: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI, Q1)
    • 2020: Complexity (Q1), Journal of Database Management (Q2)
    • 2019: World Wide Web Journal (Q1)
    • 2018: World Wide Web Journal (Q1)
  • PC Co-Chair, The 3rd International Workshop on Privacy, Security, and Trust in Computational Intelligence (PSTCI2021), in conjunction with CIKM2021, Gold Coast, Queensland, Australia, 1-5, November, 2021.
  • PC Co-Chair, Australasian Web Conference 2020 (AWC2020), 2-7 February, 2020, Melbourne, VIC, Australia.
  • PC Co-Chair, Australasian Web Conference 2019 (AWC2019), 29-31 January, 2019, Sydney, NSW, Australia.
  • PC Co-Chair, The First Internal Workshops on Knowledge Acquisition, Representation and Management (KARM 2017) in conjunction with WISE2017, Moscow, Russia, 7-11 October, 2017.
  • PC Co-Chair, The Second International Workshop on Big Data Management and Service (BDMS2015) in conjunction with DASFAA2015, Hanoi, Vietnam, 20-23 April, 2015.
  • Panel Discussion Chair: ADMA2024
  • Special Session Chair: DSAA2020
  • Publication Chair: APWeb2014, APWeb2016, BESC2016
  • Publicity Chair: ADC2024, ATC2013, ATC2014
  • PC Member: KDD2024, WSDM2024, WWW2024, SDM2024, IJCAI2024, WISE2024
  • PC Member: ICDE2023, WSDM2023, WWW2023, IJCAI2023, KDD2023, CIKM2023 (Senior PC)
  • PC Member: KDD2022, IJCAI2022, AAAI2022, WWW2022, IEEE BigComp2022, WISE2022
  • PC Member: IJCAI2021(Senior PC), CIKM2021(Senior PC), WWW2021, AAAI2021, WISE2021
  • PC Member: IJCAI2020 (Senior PC), VLDB2020 Demo, AAAI2020, WWW2020, DASFAA2020, ECAI2020, SCC2020, WISE2020
  • PC Member: KDD2019, IJCAI2019, AAAI2019, CIKM2019, WISE2019, AI2019, BigComp2019, NDBC2019, IEEE DSC2019, IEEE SCC2019
  • PC Member: DASFAA2018, NDBC2018, IJCAI2018, IEEE SCC2018, IEEE BigComp2018
  • PC Member: ICYCSEE2017, BESC2017, IoP2017, NDBC2017, SOCA2017
  • PC Member: ICWS2016, ICSOC2016, BESC2016, APWEB2016, TrustCom2016
  • PC Member: APWeb2015, BESC2015, TrustCom2015
  • PC Member: APWeb2014, ATC2014