Projects per year
Personal profile
Biography
Dr Shan (Emma) Xue is a Senior Lecturer in Computing. She joined the School of Computing in January 2023. Dr Xue received her PhD in Software Engineering from the University of Technology Sydney in 2019, and her PhD in Information Management and Information System from Shanghai University in 2018. She worked as a Lecturer at University of Wollongong (2022) and did her Postdoc at Macquarie University, jointly supported by CSIRO Data61 (2019-2022).
She is available to supervise PhD and Master by Research students with backgrounds in graph analytics, graph representation, deep learning and business/web intelligence.
Research interests
Dr Xue is an experienced researcher with expertise in deep learning, adaptive artificial intelligence, data mining and knowledge discovery in the complex cyber environment. She has been working closely within university research groups, CSIRO Data61 and Australian industry end-users. Her research outcomes mainly contribute to social network analytics, pattern mining and applicational intelligence. They are published in CORE A* international conferences, such as NeurIPS, IJCAI, WSDM, ICDM, and high-impact refereed journals, such as Pattern Recognition, The VLDB Journal, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Knowledge and Data Engineering (TKDE) and IEEE Transactions on Industrial Informatics (TII). She has been general sessional chair at IJCNN, and SPC/PC member at top international conferences, including AAAI, IJCAI, WWW, WSDM and KDD.
External positions
Researcher, CSIRO
18 Feb 2019 → 17 Feb 2022
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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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Optimizing Residential Electricity Usage through Artificial Intelligence enabled Behavioural Modelling
Beheshti, A. (Primary Chief Investigator), Xue, E. (Chief Investigator), Taghizadeh, F. (Chief Investigator), Asadnia, M. (Chief Investigator) & Abbassi, R. (Chief Investigator)
1/01/25 → 1/01/29
Project: Research
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Next-Gen Banking: Towards Customized and Personalized Banking Solutions through Generative AI Technologies
Beheshti, A. (Primary Chief Investigator), Wu, J. (Chief Investigator), Zhang, X. (Chief Investigator), Qi, Y. (Chief Investigator), Xue, E. (Chief Investigator) & Alinejad Rokny, H. (Chief Investigator)
1/07/24 → 30/06/28
Project: Research
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MQRAS 24: Enhancing Natural Disaster Response Networks with Advanced Graph-based Rescue Simulation
Xue, E. (Primary Chief Investigator), Beheshti, A. (Chief Investigator), Asadnia, M. (Chief Investigator), Wu, J. (Chief Investigator), Gore, D. (Chief Investigator), Domingo, S. A. (Partner Investigator) & McKnight, B. (Partner Investigator)
1/07/24 → 31/12/25
Project: Research
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Generative Adversarial Network (GAN) Development for Counter-Fraud Training
Beheshti, A. (Primary Chief Investigator), Xue, E. (Chief Investigator), Lotfi, F. (PhD Student) & Simpson, M. (Partner Investigator)
1/01/24 → 31/12/24
Project: Research
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A bidirectional feedback actor–critic approach for collaborative target search in heterogeneous intelligent agent systems
Cao, X., Luo, H., Wang, G., Xue, S., Yang, J., Beheshti, A. & Wu, J., Mar 2026, In: IEEE Systems Journal. 20, 1, p. 123-134 12 p.Research output: Contribution to journal › Article › peer-review
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Adaptive graph search for multi-agent rescue operations in natural disaster response
Lyu, Q., Xin, C., Yu, Y., Xue, S., Yang, J., Yang, Z., Beheshti, A. & Wu, J., Jul 2026, In: International Journal of Machine Learning and Cybernetics. 17, 7, p. 1-24 24 p., 338.Research output: Contribution to journal › Article › peer-review
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Extract and refine brain subgraph for disorder analysis via cross-domain learning
Luo, X., Wu, J., Zhang, S., Dong, G., Xue, S., Peng, H., Yang, J., Zhou, C., Hu, W. & Beheshti, A., 27 Feb 2026, (E-pub ahead of print) In: IEEE Transactions on Big Data.Research output: Contribution to journal › Article › peer-review
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LHG: LLM-enhanced and Heterogeneous Graph-induced for unsupervised social event detection
Qiu, Z., Xu, R., Ma, C., Xue, S., Yang, J., Liu, G., Sheng, Q. Z., Beheshti, A. & Wu, J., 2026, WWW '26: proceedings of the ACM Web Conference 2026. New York, US: Association for Computing Machinery, p. 3612-3623 12 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile3 Downloads (Pure) -
PIGCN: Physics-Inspired Graph Convolution Networks for heterogeneous social event detection
Yu, Y., Ma, C., Qiu, Z., Xue, S., Yang, J. & Wu, J., 2026, WWW '26: proceedings of the ACM Web Conference 2026. New York, US: Association for Computing Machinery, p. 992-1003 12 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile4 Downloads (Pure)
Prizes
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Best Student Paper Awards for “A Framework of Transferring Structures Across Large-scale Information Networks”
Xue, E. (Recipient), Lu, J. (Recipient), Zhang, G. (Recipient) & Xiong, L. (Recipient), 2018
Prize
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Best Student Paper Awards for “FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance”
Zhang, G. (Recipient), Wu, J. (Recipient), Yang, J. (Recipient), Beheshti, A. (Recipient), Xue, E. (Recipient), Zhou, C. (Recipient) & Sheng, M. (Recipient), 2021
Prize
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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