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
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
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
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
Scalable and Lightweight On-Device Recommender Systems
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
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
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
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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
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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