Research output per year
Research output per year
Personal profile
Biography
Dr Fanzhen Liu is a Postdoctoral Research Fellow in the School of Computing, Macquarie University, Australia, where he received his PhD in 2024. His current research interests include graph mining, anomaly detection, trustworthy AI/ML, and social network analysis. Dr Liu has contributed to notable publications in esteemed venues in data science and artificial intelligence, including VLDBJ, IEEE TKDE, IEEE TNNLS, KDD, ICDM, EMNLP, and IJCAI.
External positions
Visiting Scientist, CSIRO’s Data61
Mar 2024 → Sept 2025
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Adversarial attacks against automated fact-checking: A survey
Liu, F., Abuadbba, A., Moore, K., Nepal, S., Paris, C., Wu, J., Yang, J. & Sheng, Q. Z., Nov 2025, EMNLP 2025: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. Christodoulopoulos, C., Chakraborty, T., Rose, C. & Peng, V. (eds.). Kerrville, TX: Association for Computational Linguistics (ACL), p. 22979–23001 23 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open Access -
GCFL: a gradient correction-based federated learning framework for privacy-preserving CPSS
Wan, J., Zhu, X., Liu, F., Fan, W. & Xu, X., 5 Aug 2025, (E-pub ahead of print) In: IEEE Transactions on Computational Social Systems. 12 p.Research output: Contribution to journal › Article › peer-review
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Rethinking unsupervised graph anomaly detection with deep learning: residuals and objectives
Ma, X., Liu, F., Wu, J., Yang, J., Xue, S. & Sheng, Q. Z., Feb 2025, In: IEEE Transactions on Knowledge and Data Engineering. 37, 2, p. 881-895 15 p.Research output: Contribution to journal › Article › peer-review
2 Citations (Scopus) -
A comprehensive survey on community detection with deep learning
Su, X., Xue, S., Liu, F., Wu, J., Yang, J., Zhou, C., Hu, W., Paris, C., Nepal, S., Jin, D., Sheng, Q. Z. & Yu, P. S., Apr 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 4, p. 4682-4702 21 p.Research output: Contribution to journal › Article › peer-review
264 Citations (Scopus) -
Graph anomaly detection with few labels: a data-centric approach
Ma, X., Li, R., Liu, F., Ding, K., Yang, J. & Wu, J., 2024, KDD '24: proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York: Association for Computing Machinery, p. 2153–2164 12 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile7 Citations (Scopus)615 Downloads (Pure)
Prizes
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Most Influential IJCAI2020 Paper Award for “Deep learning for community detection: Progress, challenges and opportunities”
Liu, F. (Recipient), Xue, E. (Recipient), Wu, J. (Recipient), Zhou, C. (Recipient), Hu, W. (Recipient), Paris, C. (Recipient), Nepal, S. (Recipient), Yang, J. (Recipient) & Yu, P. S. (Recipient), 2020
Prize
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Executive Dean's Commendation for Academic Excellence in Year 2 Master of Research
Liu, F. (Recipient), 2020
Prize: Honorary award
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Vice-Chancellor’s Commendation for Academic Excellence
Liu, F. (Recipient), Oct 2024
Prize: Honorary award