Overview
Background
Rocky Tong Chen is currently a Senior Lecturer (~Associate Professor in North America) and ARC DECRA Fellow with the Data Science Discipline, School of Electrical Engineering and Computer Science, The University of Queensland. Dr Chen's main research interests include recommender systems, LLM agents, graph and sequential data mining, and social media content moderation. His research outputs shares a common focus on developing accurate, efficient, and trustworthy data mining solutions to discover actionable patterns and intelligence from large-scale user data to facilitate prediction and recommendation in a wide range of domains.
To date, Dr Chen has published 90+ peer-reviewed papers in the most prestigious, CORE A*/A-ranked and CCF A-ranked conferences (e.g., KDD, SIGIR, WWW, ICDM, ICDE, AAAI and IJCAI) and journals (e.g., VLDBJ, IEEE TKDE, IEEE TNNLS, ACM TOIS and WWWJ). Dr Chen's work has attracted 7,500+ citations and an h-index of 40 on Google Scholar. a Field-Weighted Citation Impact of 4.51 (SciVal), i.e., his publications attract 4.51 times of the citations in comparison to similar papers of the same age, type and area. According to CNCI (Web of Science), 10 and 36 of his papers are respectively the top-1% and top-10% most cited. His publications have won 4 Best Paper Awards, 1 Best Paper Nomination, and 2 Travel Awards.
Dr Chen has been regularly providing services in the data science discipline as reviewers for CORE A*/A journals like TKDE, TNNLS, TOIS, and as program committee members for CORE A*/A conferences like KDD, SIGIR, NeurIPS, WSDM, ICDM, ACL. He is one of the Area Chairs of top conferences KDD, WWW, and ACL in 2024-2025, and the Program Chair of the 2024 Australasian Database Conference (ADC’24). In 2025, he is appointed as an Associate Editor of the SJR Q1-ranked journal Neural Networks. Besides, he led and delivered a series of technical tutorials at WWW (the No. 1 international web mining conference) in 2022, 2024, and 2025, as well as WSDM’25 (CORE A-ranked conference) and DASFAA’23 (top database conference), which all aimed to promote trustworthy, resource-efficient, and unbiased personalisation algorithms.
Availability
- Dr Rocky Chen is:
- Available for supervision
Qualifications
- Bachelor of Software Engineering, Northwest A&F University (西北农林科技大学)
- Doctor of Philosophy, The University of Queensland
Research interests
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Data Mining
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Recommender Systems
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Predictive Analytics
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Machine Learning
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Health Informatics
Research impacts
Dr Chen's research impact has received extensive recognitions, including:
- 2025: Brisbane Lord Mayor’s Convention Trailblazer Award (6 awardees per annum).
- 2025: Outstanding Program Committee Member, KDD’25 (CORE A* data mining conference).
- 2025: Excellent Program Committee Member, SIGIR’25 (CORE A* information retrieval conference).
- 2024: Best Student Paper Award, CIKM’24 (1/347, CORE A data science conference, principal supervisor of first author).
- 2024: World’s Top 2% Scientist in 2024, Stanford University.
- 2024: UQ Faculty of EAIT Early Career Research Leadership Award.
- 2022: ARC Discovery Early Career Researcher Award (2023).
- 2022: UQ EAIT Faculty Early Career Researcher Award.
- 2020: Best Student Paper Award, DASFAA’20 (1/162, top database conference, lead author).
- 2018: Best Paper Award Nomination, ICDM’18 (CORE A* data mining conference, first author).
- 2018: Best Paper Award as the first author in PAKDD’18 (CORE A conference) Workshop on Social Computing.
- 2017: Best Paper Award in ACM WWW’17 (CORE A* conference) Companion on Social Computing.
He has been continuously contributing to the following research areas:
- Recommender Systems and Personalisation. Dr Chen has been continuously publishing in the field of personalisation algorithms and recommender systems [SIGIR’20-25, WWW’23-25, CIKM’23-24, ICDE’19-20]. His work also features pioneering research utilizing (large) language models to build interactive, conversational systems for recommendation, retrieval, and decision support [SIGIR’25, KDD’24, TIST’23, WWW’22, SIGIR’21, TOIS’20].
- Fairness-aware and Trustworthy Machine Learning. Dr Chen leads the area of fairness-aware algorithms, represented by his work on social media analytics [ICDM’25, MM’25, WWW’25, KDD’24]. Besides, his research highlights trustworthiness, where research outcomes span areas like explainable recommendation [ICDE’23, SIGIR’21], knowledge graph reasoning [ICDE’25, TIST’24], anomaly prediction [ICDE’24, WWWJ’23], robust spatial-temporal prediction [ECML’25, CIKM’24, ICDE’24, TKDE’21], and causal inference and machine unlearning [ICML’25, KDD’25, TKDE’24, ICDM’23, ACL’23], which reflect the societal value of his research.
- Combating the Digital Divide across Individuals. The era of personalised computing calls for solutions to the unbalanced computing capacity among individuals. Dr Chen leads the area of on-device personalised recommender systems [KDD’21, WWW’21, VLDB’21, CIKM’21, WWW’20]. Supported by his DRCRA, his recent research focuses on scaling up personalised computing techniques to achieve digitalisation equity [WWW’25, SIGIR’24, WSDM’24, TKDE’24, ICDM’23, SIGIR’23, TOIS’22] and privacy [TOIS’25, CIKM’25, KDD’24, WWW’24] across individuals.
Works
Search Professor Rocky Chen’s works on UQ eSpace
2019
Conference Publication
Exploiting centrality information with graph convolutions for network representation learning
Chen, Hongxu, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Peng, Wen-Chih and Li, Xue (2019). Exploiting centrality information with graph convolutions for network representation learning. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00059
2019
Conference Publication
Streaming Session-based Recommendation
Guo, Lei, Chen, Tong, Yin, Hongzhi, Zhou, Alexander, Wang, Qinyong and Hung, Nguyen Quoc Viet (2019). Streaming Session-based Recommendation. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Anchorage, AK United States, 4-8 August 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3292500.3330839
2019
Conference Publication
What can history tell us? Identifying relevant sessions for next-item recommendation
Sun, Ke, Qian, Tieyun, Yin, Hongzhi, Chen, Tong, Chen, Yiqi and Chen, Ling (2019). What can history tell us? Identifying relevant sessions for next-item recommendation. 28th ACM International Conference on Information and Knowledge Management, Beijing, China, 3-7 November 2019. New York, United States: Association for Computing Machinery. doi: 10.1145/3357384.3358050
2019
Conference Publication
AIR: Attentional intention-aware recommender systems
Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Yan, Rui, Nguyen, Quoc Viet Hung and Li, Xue (2019). AIR: Attentional intention-aware recommender systems. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00035
2019
Conference Publication
Inferring substitutable products with deep network embedding
Zhang, Shijie, Yin, Hongzhi, Wang, Qinyong, Chen, Tong, Chen, Hongxu and Nguyen, Quoc Viet Hung (2019). Inferring substitutable products with deep network embedding. International Joint Conference on Artificial Intelligence, Macao, China, 10-16 August 2019. California: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2019/598
2018
Conference Publication
Call attention to rumors: deep attention based recurrent neural networks for early rumor detection
Chen, Tong, Li, Xue, Yin, Hongzhi and Zhang, Jun (2018). Call attention to rumors: deep attention based recurrent neural networks for early rumor detection. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, Australia, 3 June 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_4
2018
Conference Publication
Rumor detection via recurrent neural networks: a case study on adaptivity with varied data compositions
Chen, Tong, Chen, Hongxu and Li, Xue (2018). Rumor detection via recurrent neural networks: a case study on adaptivity with varied data compositions. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, Australia, 3 June 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_10
2018
Conference Publication
TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales prediction
Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Wu, Lin, Wang, Hao, Zhou, Xiaofang and Li, Xue (2018). TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales prediction. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17-20 November 2018. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ICDM.2018.00020
2017
Conference Publication
Generating life course trajectory sequences with recurrent neural networks and application to early detection of social disadvantage
Wu, Lin, Haynes, Michele, Smith, Andrew, Chen, Tong and Li, Xue (2017). Generating life course trajectory sequences with recurrent neural networks and application to early detection of social disadvantage. Advanced Data Mining and Applications 13th International Conference, Singapore, November 5–6, 2017. Heidelberg, Germany: Springer . doi: 10.1007/978-3-319-69179-4_16
2017
Conference Publication
People opinion topic model: opinion based user clustering in social networks
Chen, Hongxu, Yin, Hongzhi, Li, Xue, Wang, Meng, Chen, Weitong and Chen, Tong (2017). People opinion topic model: opinion based user clustering in social networks. International Conference on World Wide Web Companion, Perth, Australia, 3-7 April 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee. doi: 10.1145/3041021.3051159
Funding
Current funding
Supervision
Availability
- Dr Rocky Chen is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Supervision history
Current supervision
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Doctor Philosophy
Data as a Service Architecture
Principal Advisor
Other advisors: Professor Shazia Sadiq
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Doctor Philosophy
Sustainable On-Device Recommender Systems
Principal Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Scalable and Lightweight On-Device Recommender Systems
Principal Advisor
Other advisors: Professor Hongzhi Yin, Dr Junliang Yu
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Doctor Philosophy
Value Measurement of Data Products
Principal Advisor
Other advisors: Professor Shazia Sadiq
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Doctor Philosophy
Advancing Causal Effect Estimation: From Training Data Expansion to Estimator Design
Principal Advisor
Other advisors: Professor Shazia Sadiq, Professor Hongzhi Yin
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Doctor Philosophy
Lightweight Graph Neural Networks for Recommendation
Principal Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Scalable and Lightweight On-Device Recommender Systems
Principal Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Scalable and Generalizable Graph Neural Networks
Principal Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Establishment LCA method coupled with an activated sludge model for sustainable nitrogen management technology evaluation.
Associate Advisor
Other advisors: Professor Liu Ye, Dr Shakil Ahmmed
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Doctor Philosophy
Improving Traffic Dynamics Simulation Quality for Enhanced Safety and Efficiency: Evaluation, Modelling, and Application
Associate Advisor
Other advisors: Professor Zuduo Zheng
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Doctor Philosophy
LLM-enhanced Recommender System
Associate Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Decentralised Collaborative Predictive Analytics on Personal Smart Devices
Associate Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Decentralised Collaborative Predictive Analytics on Personal Smart Devices
Associate Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Lightweight Embedding Learning for Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
Completed supervision
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2025
Doctor Philosophy
Graph Condensation for Real-World Graph Representation at Scale
Associate Advisor
Other advisors: Professor Hongzhi Yin
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2025
Doctor Philosophy
Decentralized Learning for On-device Recommendation
Associate Advisor
Other advisors: Professor Hongzhi Yin
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2025
Doctor Philosophy
Decentralized Point-Of-Interest (POI) Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
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2022
Doctor Philosophy
Neural Attentive Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin, Professor Helen Huang
Media
Enquiries
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