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Dr Rocky Chen
Dr

Rocky Chen

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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

  • Data Mining

  • Recommender Systems

  • Predictive Analytics

  • Machine Learning

  • Health Informatics

Works

Search Professor Rocky Chen’s works on UQ eSpace

101 works between 2017 and 2025

61 - 80 of 101 works

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

Passenger mobility prediction via representation learning for dynamic directed and weighted graphs

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

Hierarchical hyperedge embedding-based representation learning for group recommendation

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

Personalized on-device e-health analytics with decentralized block coordinate descent

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

Lightweight self-attentive sequential recommendation

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

Quaternion factorization machines: a lightweight solution to intricate feature interaction modeling

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

Fast-adapting and privacy-preserving federated recommender system

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

Learning elastic embeddings for customizing on-device recommenders

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

Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation

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

DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation

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

Attribute-aware explainable complementary clothing recommendation

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

Learning to ask appropriate questions in conversational recommendation

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

Graph embedding for recommendation against attribute inference attacks

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

Gallat: A spatiotemporal graph attention network for passenger demand prediction

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

DDHH: A decentralized deep learning framework for large-scale heterogeneous networks

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

Disease prediction via graph neural networks

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

An integrated model based on deep multimodal and rank learning for point-of-interest recommendation

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

Secure your ride: real-time matching success rate prediction for passenger-driver pairs

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

FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection

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

CRSAL: conversational recommender systems with adversarial learning

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

Multi-level graph convolutional networks for cross-platform Anchor Link Prediction

Funding

Current funding

  • 2025 - 2028
    Building an Aussie Information Recommendation System You Can Trust
    ARC Linkage Projects
    Open grant
  • 2024 - 2027
    Embracing Changes for Responsive Video-sharing Services
    ARC Discovery Projects
    Open grant
  • 2023 - 2026
    Scalable and Lightweight On-Device Recommender Systems
    ARC Discovery Early Career Researcher Award
    Open grant
  • 2021 - 2026
    ARC Training Centre for Information Resilience
    ARC Industrial Transformation Training Centres
    Open grant

Supervision

Availability

Dr Rocky Chen is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Lightweight Graph Neural Networks for Recommendation

    Principal Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Value Measurement of Data Products

    Principal Advisor

    Other advisors: Professor Shazia Sadiq

  • Doctor Philosophy

    Causal Analysis for Decision Support in Public Health

    Principal Advisor

    Other advisors: Professor Shazia Sadiq, Professor Hongzhi Yin

  • Doctor Philosophy

    Scalable and Lightweight On-Device Recommender Systems

    Principal Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Scalable and Lightweight On-Device Recommender Systems

    Principal Advisor

    Other advisors: Professor Hongzhi Yin, Dr Junliang Yu

  • Doctor Philosophy

    Sustainable On-Device Recommender Systems

    Principal Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Data as a Service Architecture

    Principal Advisor

    Other advisors: Professor Shazia Sadiq

  • Doctor Philosophy

    Scalable and Generalizable Graph Neural Networks

    Principal Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    LLM-enhanced Recommender System

    Associate Advisor

    Other advisors: Professor Hongzhi Yin

  • 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

  • Doctor Philosophy

    Quantitative Coupling Relationship between Safety and Efficiency of Mixed Traffic Flow with Connected and Automated vehicles and Human-driven vehicles

    Associate Advisor

    Other advisors: Professor Zuduo Zheng

  • Doctor Philosophy

    Decentralised Collaborative Predictive Analytics on Personal Smart Devices

    Associate Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Decentralised Collaborative Predictive Analytics on Personal Smart Devices

    Associate Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Joint Feature Learning for Recommender System

    Associate Advisor

    Other advisors: Professor Hongzhi Yin

  • Doctor Philosophy

    Decentralised Collaborative Predictive Analytics on Personal Smart Devices

    Associate Advisor

    Other advisors: Professor Hongzhi Yin

Completed supervision

Media

Enquiries

For media enquiries about Dr Rocky Chen's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au