Overview
Background
Rocky Tong Chen is currently a Senior Lecturer and ARC DECRA Fellow with the Data Science Discipline, School of Electrical Engineering and Computer Science, The University of Queensland. His research has been focused 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, he has published 70+ peer-reviewed papers in the most prestigious conferences (e.g., KDD, SIGIR, WWW, ICDM, ICDE, AAAI and IJCAI) and journals (e.g., VLDBJ, IEEE TKDE, IEEE TNNLS, ACM TOIS and WWWJ). His publications have won 3 Best Paper Awards, 1 Best Paper Nomination, and 2 Travel Awards.
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
Works
Search Professor Rocky Chen’s works on UQ eSpace
2022
Conference Publication
PipA!ack: poisoning federated recommender systems for manipulating item promotion
Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Huang, Zi, Nguyen, Quoc Viet Hung and Cui, Lizhen (2022). PipA!ack: poisoning federated recommender systems for manipulating item promotion. WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, Virtual, AZ, United States, 21 - 25 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3488560.3498386
2022
Journal Article
An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants
Li, Kaili, Duan, Haoran, Liu, Linfeng, Qiu, Ruihong, van den Akker, Ben, Ni, Bing-Jie, Chen, Tong, Yin, Hongzhi, Yuan, Zhiguo and Ye, Liu (2022). An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants. Environmental Science and Technology, 56 (4) acs.est.1c05020, 2816-2826. doi: 10.1021/acs.est.1c05020
2022
Journal Article
Passenger mobility prediction via representation learning for dynamic directed and weighted graphs
Wang, Yuandong, Yin, Hongzhi, Chen, Tong, Liu, Chunyang, Wang, Ben, Wo, Tianyu and Xu, Jie (2022). Passenger mobility prediction via representation learning for dynamic directed and weighted graphs. ACM Transactions on Intelligent Systems and Technology, 13 (1) 2, 1-25. doi: 10.1145/3446344
2022
Journal Article
Hierarchical hyperedge embedding-based representation learning for group recommendation
Guo, Lei, Yin, Hongzhi, Chen, Tong, Zhang, Xiangliang and Zheng, Kai (2022). Hierarchical hyperedge embedding-based representation learning for group recommendation. ACM Transactions on Information Systems, 40 (1) 3, 1-27. doi: 10.1145/3457949
2022
Journal Article
Personalized on-device e-health analytics with decentralized block coordinate descent
Ye, Guanhua, Yin, Hongzhi, Chen, Tong, Xu, Miao, Nguyen, Quoc Viet Hung and Song, Jiangning (2022). Personalized on-device e-health analytics with decentralized block coordinate descent. IEEE Journal of Biomedical and Health Informatics, 26 (6), 1-1. doi: 10.1109/JBHI.2022.3140455
2021
Conference Publication
Lightweight self-attentive sequential recommendation
Li, Yang, Chen, Tong, Zhang, Peng-Fei and Yin, Hongzhi (2021). Lightweight self-attentive sequential recommendation. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482448
2021
Journal Article
Quaternion factorization machines: a lightweight solution to intricate feature interaction modeling
Chen, Tong, Yin, Hongzhi, Zhang, Xiangliang, Huang, Zi, Wang, Yang and Wang, Meng (2021). Quaternion factorization machines: a lightweight solution to intricate feature interaction modeling. IEEE Transactions on Neural Networks and Learning Systems, PP (99), 1-14. doi: 10.1109/TNNLS.2021.3118706
2021
Journal Article
Fast-adapting and privacy-preserving federated recommender system
Wang, Qinyong, Yin, Hongzhi, Chen, Tong, Yu, Junliang, Zhou, Alexander and Zhang, Xiangliang (2021). Fast-adapting and privacy-preserving federated recommender system. The VLDB Journal, 31 (5), 877-896. doi: 10.1007/s00778-021-00700-6
2021
Conference Publication
Learning elastic embeddings for customizing on-device recommenders
Chen, Tong, Yin, Hongzhi, Zheng, Yujia, Huang, Zi, Wang, Yang and Wang, Meng (2021). Learning elastic embeddings for customizing on-device recommenders. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467220
2021
Conference Publication
Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation
Li, Yang, Chen, Tong, Luo, Yadan, Yin, Hongzhi and Huang, Zi (2021). Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, QC Canada, 19 - 27 August 2021. Palo Alto, CA United States: A A A I Press. doi: 10.24963/ijcai.2021/206
2021
Conference Publication
DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation
Guo, Lei, Tang, Li, Chen, Tong, Zhu, Lei, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2021). DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation. International Joint Conference on Artificial Intelligence, Montreal, Canada, 19-27 August 2021. San Francisco, CA, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2021/342
2021
Journal Article
Attribute-aware explainable complementary clothing recommendation
Li, Yang, Chen, Tong and Huang, Zi (2021). Attribute-aware explainable complementary clothing recommendation. World Wide Web, 24 (5), 1885-1901. doi: 10.1007/s11280-021-00913-3
2021
Conference Publication
Learning to ask appropriate questions in conversational recommendation
Ren, Xuhui, Yin, Hongzhi, Chen, Tong, Wang, Hao, Huang, Zi and Zheng, Kai (2021). Learning to ask appropriate questions in conversational recommendation. SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, 11-15 July 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3404835.3462839
2021
Conference Publication
Graph embedding for recommendation against attribute inference attacks
Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Huang, Zi, Cui, Lizhen and Zhang, Xiangliang (2021). Graph embedding for recommendation against attribute inference attacks. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-22 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449813
2021
Conference Publication
Gallat: A spatiotemporal graph attention network for passenger demand prediction
Wang, Yuandong, Yin, Hongzhi, Chen, Tong, Liu, Chunyang, Wang, Ben, Wo, Tianyu and Xu, Jie (2021). Gallat: A spatiotemporal graph attention network for passenger demand prediction. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00212
2021
Conference Publication
DDHH: A decentralized deep learning framework for large-scale heterogeneous networks
Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi, Zhang, Xiangliang and Zheng, Kai (2021). DDHH: A decentralized deep learning framework for large-scale heterogeneous networks. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00196
2021
Journal Article
Disease prediction via graph neural networks
Sun, Zhenchao, Yin, Hongzhi, Chen, Hongxu, Chen, Tong, Cui, Lizhen and Yang, Fan (2021). Disease prediction via graph neural networks. IEEE Journal of Biomedical and Health Informatics, 25 (3) 9122573, 818-826. doi: 10.1109/JBHI.2020.3004143
2021
Journal Article
An integrated model based on deep multimodal and rank learning for point-of-interest recommendation
Liao, Jianxin, Liu, Tongcun, Yin, Hongzhi, Chen, Tong, Wang, Jingyu and Wang, Yulong (2021). An integrated model based on deep multimodal and rank learning for point-of-interest recommendation. World Wide Web, 24 (2), 631-655. doi: 10.1007/s11280-021-00865-8
2021
Journal Article
Secure your ride: real-time matching success rate prediction for passenger-driver pairs
Wang, Yuandong, Yin, Hongzhi, Wu, Lian, Chen, Tong and Liu, Chunyang (2021). Secure your ride: real-time matching success rate prediction for passenger-driver pairs. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-14. doi: 10.1109/tkde.2021.3112739
2021
Journal Article
FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection
Ye, Guanhua, Yin, Hongzhi, Chen, Tong, Chen, Hongxu, Cui, Lizhen and Zhang, Xiangliang (2021). FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection. IEEE Journal of Biomedical and Health Informatics, 25 (8) 9320528, 2848-2856. doi: 10.1109/JBHI.2021.3050113
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
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
Value Measurement of Data Products
Principal Advisor
Other advisors: Professor Shazia Sadiq
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Doctor Philosophy
Causal Analysis for Decision Support in Public Health
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
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
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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
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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