Overview
Background
Rocky Tong Chen is currently an Associate Professor 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
- Associate Professor 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
2020
Conference Publication
Sequence-aware factorization machines for temporal predictive analytics
Chen, Tong, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Peng, Wen-Chih, Li, Xue and Zhou, Xiaofang (2020). Sequence-aware factorization machines for temporal predictive analytics. 2020 IEEE 36th International Conference on Data Engineering, Dallas, Texas, United States, 20-24 April 2020. LOS ALAMITOS: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00125
2020
Conference Publication
GCN-based user representation learning for unifying robust recommendation and fraudster detection
Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Hung, Quoc Viet Nguyen, Huang, Zi and Cui, Lizhen (2020). GCN-based user representation learning for unifying robust recommendation and fraudster detection. SIGIR '20: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Online, July 2020. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3397271.3401165
2020
Conference Publication
Decentralized embedding framework for large-scale networks
Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Shao, Yingxia, Zhang, Xiangliang and Zhou, Xiaofang (2020). Decentralized embedding framework for large-scale networks. International Conference on Database Systems for Advanced Applications, Jeju, South Korea, 24-27 September 2020. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-59419-0_26
2020
Journal Article
A guide to human microbiome research: Study design, sample collection, and bioinformatics analysis
Qian, Xu-Bo, Chen, Tong, Xu, Yi-Ping, Chen, Lei, Sun, Fu-Xiang, Lu, Mei-Ping and Liu, Yong-Xin (2020). A guide to human microbiome research: Study design, sample collection, and bioinformatics analysis. Chinese Medical Journal, 133 (15), 1844-1855. doi: 10.1097/CM9.0000000000000871
2020
Conference Publication
Next point-of-interest recommendation on resource-constrained mobile devices
Wang, Qinyong, Yin, Hongzhi, Chen, Tong, Huang, Zi, Wang, Hao, Zhao, Yanchang and Viet Hung, Nguyen Quoc (2020). Next point-of-interest recommendation on resource-constrained mobile devices. WWW '20: The Web Conference 2020, Taipei, Taiwan, April 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3366423.3380170
2020
Conference Publication
Where to go next: modeling long- and short-term user preferences for point-of-interest recommendation
Sun, Ke, Qian, Tieyun, Chen, Tong, Liang, Yile, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2020). Where to go next: modeling long- and short-term user preferences for point-of-interest recommendation. AAAI Conference on Artificial Intelligence, New York, NY, United States, 7-12 February 2020. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v34i01.5353
2019
Journal Article
Screening active ingredients of rosemary based on spectrum-effect relationships between UPLC fingerprint and vasorelaxant activity using three chemometrics
Zhang, Jidan, Chen, Tong, Li, Ke, Xu, Haiyu, Liang, Rixin, Wang, Weihao, Li, Hua, Shao, Aijuan and Yang, Bin (2019). Screening active ingredients of rosemary based on spectrum-effect relationships between UPLC fingerprint and vasorelaxant activity using three chemometrics. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, 1134-1135 121854, 1134. doi: 10.1016/j.jchromb.2019.121854
2019
Journal Article
Online sales prediction via trend alignment-based multitask recurrent neural networks
Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Wang, Hao, Zhou, Xiaofang and Li, Xue (2019). Online sales prediction via trend alignment-based multitask recurrent neural networks. Knowledge and Information Systems, 62 (6), 2139-2167. doi: 10.1007/s10115-019-01404-8
2019
Journal Article
An integrated strategy to identify genes responsible for sesquiterpene biosynthesis in turmeric
Sun, Jingru, Cui, Guanghong, Ma, Xiaohui, Zhan, Zhilai, Ma, Ying, Teng, Zhongqiu, Gao, Wei, Wang, Yanan, Chen, Tong, Lai, Changjiangsheng, Zhao, Yujun, Tang, Jinfu, Lin, Huixin, Shen, Ye, Zeng, Wen, Guo, Juan and Huang, Luqi (2019). An integrated strategy to identify genes responsible for sesquiterpene biosynthesis in turmeric. Plant Molecular Biology, 101 (3), 221-234. doi: 10.1007/s11103-019-00892-0
2019
Conference Publication
Minimal path based particle tracking in low SNR fluorescence microscopy images
Lu, Sheng, Chen, Tong, Yang, Fan, Peng, Chenglei, Du, Sidan and Li, Yang (2019). Minimal path based particle tracking in low SNR fluorescence microscopy images. ICBIP '19: 2019 4th International Conference on Biomedical Signal and Image Processing, Chendgu, China, 13 - 15 August 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3354031.3354035
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
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
2018
Conference Publication
Codedvision: Towards joint image understanding and compression via end-to-end learning
Shen, Qiu, Cai, Juanjuan, Liu, Linfeng, Liu, Haojie, Chen, Tong, Ye, Long and Ma, Zhan (2018). Codedvision: Towards joint image understanding and compression via end-to-end learning. 19th Pacific-Rim Conference on Multimedia, Hefei, China, September 21-22, 2018. CHAM: Springer Verlag. doi: 10.1007/978-3-030-00776-8_1
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
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
Funding
Current funding
Supervision
Availability
- Associate Professor Rocky Chen is:
- Available for supervision
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Supervision history
Current supervision
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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
Multimodal Representation Learning for Responsive Video-sharing Services
Principal Advisor
Other advisors: Professor Helen Huang, Dr Yadan Luo
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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
An Accessibility-Aware POI Recommender System
Principal Advisor
Other advisors: Dr Junliang Yu
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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
Value Measurement of Data Products
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
Data as a Service Architecture
Principal Advisor
Other advisors: Professor Shazia Sadiq
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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
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
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
Decentralised Collaborative Predictive Analytics on Personal Smart Devices
Associate Advisor
Other advisors: Professor Hongzhi Yin
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Doctor Philosophy
Race, Gender and Platform Logic: Twitter Harassment of Chinese Women in Australia Across the COVID-19 Timeline
Associate Advisor
Other advisors: Professor Janeen Baxter, Dr Rennie Lee
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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
Fairness-aware Recommender Systems for Marginalized User Groups
Associate Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Revolutionise Australian Strata Management with Large Language Models
Associate Advisor
Other advisors: Professor Hongzhi Yin
Completed supervision
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2026
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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2026
Doctor Philosophy
Lightweight Embedding Learning for Recommender Systems
Associate Advisor
Other advisors: Professor Hongzhi Yin
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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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