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
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
2020
Journal Article
CRSAL: conversational recommender systems with adversarial learning
Ren, Xuhui, Yin, Hongzhi, Chen, Tong, Wang, Hao, Hung, Nguyen Quoc Viet, Huang, Zi and Zhang, Xiangliang (2020). CRSAL: conversational recommender systems with adversarial learning. ACM Transactions on Information Systems, 38 (4) 3394592, 1-40. doi: 10.1145/3394592
2020
Conference Publication
Multi-level graph convolutional networks for cross-platform Anchor Link Prediction
Chen, Hongxu, Yin, Hongzhi, Sun, Xiangguo, Chen, Tong, Gabrys, Bogdan and Musial, Katarzyna (2020). Multi-level graph convolutional networks for cross-platform Anchor Link Prediction. ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Virtual Event, CA, United States, 23-27 August 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3394486.3403201
2020
Other Outputs
Sequence modelling for e-commerce
Chen, Tong (2020). Sequence modelling for e-commerce. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/uql.2020.1003
2020
Conference Publication
GAG: global attributed graph neural network for streaming session-based recommendation
Qiu, Ruihong, Yin, Hongzhi, Huang, Zi and Chen, Tong (2020). GAG: global attributed graph neural network for streaming session-based recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China , 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401109
2020
Conference Publication
Try this instead: personalized and interpretable substitute recommendation
Chen, Tong, Yin, Hongzhi, Ye, Guanhua, Huang, Zi, Wang, Yang and Wang, Meng (2020). Try this instead: personalized and interpretable substitute recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401042
2020
Journal Article
Social boosted recommendation with folded bipartite network embedding
Chen, Hongxu, Yin, Hongzhi, Chen, Tong, Wang, Weiqing, Li, Xue and Hu, Xia (2020). Social boosted recommendation with folded bipartite network embedding. IEEE Transactions on Knowledge and Data Engineering, 34 (2), 914-926. doi: 10.1109/tkde.2020.2982878
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
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
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
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
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
Funding
Current funding
Supervision
Availability
- Dr Rocky Chen is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Value Measurement of Data Products
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
Causal Analysis for Decision Support in Public Health
Principal Advisor
Other advisors: Professor Shazia Sadiq, 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
Lightweight Graph Neural Networks for Recommendation
Principal Advisor
Other advisors: Professor Hongzhi Yin
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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
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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
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
Graph Condensation for Real-World Graph Representation at Scale
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
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
Completed supervision
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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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