Professor Hongzhi Yin
Professor

Hongzhi Yin

Email: 
Phone: 
+61 7 336 54739

Background

Prof. Hongzhi Yin works as an ARC Future Fellow and Professor and director of the Responsible Big Data & Intelligence Lab (RBDI) at The University of Queensland, Australia. He has made notable contributions to recommendation systems, structured foundation model, spatial-temporal prediction, LLM and ChatBI, and decentralized and edge intelligence. He has received numerous awards and recognition for his research achievements. He has been named to IEEE Computer Society’s AI’s 10 to Watch 2022 and Field Leader of Data Mining & Analysis in The Australian's Research 2020 magazine. In addition, he has received the prestigious 2023 Young Tall Poppy Science Awards, Australian Research Council Future Fellowship 2021, the Discovery Early Career Researcher Award 2016, UQ Foundation Research Excellence Award 2019, 2024 and 2025 Computer Science in Australia Leader Award, AI 2000 Most Influential Scholar Awards in Data Mining (2022-2026) and Information Retrieval and Recommendation (2025-2026), 2024 and 2025 ScholarGPS Highly Ranked Scholar (top 0.05%). His research has won 8 international and national Best Paper Awards, including Best Student Full Paper Award at CIKM 2024, Best Paper Award - Honorable Mention at WSDM 2023, Best Paper Award at ICDE 2019, Best Student Paper Award at DASFAA 2020, Best Paper Award Nomination at ICDM 2018, ACM Computing Reviews' 21 Annual Best of Computing Notable Books and Articles, Best Paper Award at ADC 2018 and 2016. His Ph.D. thesis won Peking University Outstanding Ph.D. Dissertation Award 2014 and CCF Outstanding Ph.D. Dissertation Award (Nomination) 2014. He has ten conference papers recognized as the Most Influential Papers in Paper Digest, including KDD 2021 and 2013, AAAI 2021, SIGIR 2022, WWW 2023 and 2021, CIKM 2021, 2019, 2016, and 2015. He has published 300+ papers in CCF A/CORE A* ranked venues, such as ICML, ICLR, NeurIPS, KDD, SIGIR, WWW, ACL, ICDM, SIGMOD, VLDB, ICDE, AAAI, IJCAI, ACM Multimedia, ECCV, IEEE TKDE, VLDB Journal, and ACM TOIS, achieving an H-index of 93 with over 30,000 citations. He serves as the PC Co-Chair for the top confernces ICDM 2027 and ADMA 2026, and Track Chair/Senior Area Chair for KDD 2027, AAAI 2027, WWW 2027, WWW 2025 and IEEE SSCI 2027. He has also served extensively as an Area Chair/SPC member for many top conferences, such as NeurIPS, KDD, ICDE, SIGIR, WWW, ACL, AAAI, IJCAI, ICDM, ICMR, and CIKM. In addition, he has been serving as Associate Editor/Guest Editor/Editorial Board for Neural Networks (JCR Q1, CCF B, 中科院一区), Science China Information Sciences (JCR Q1, CCF A, 中科院一区), Data Science and Engineering (JCR Q1, 中科院一区), Journal of Computer Science and Technology (JCST, CCF B), Journal of Social Computing, ACM Transactions on Information Systems 2022-2023 (JCR Q1, CCF A, CORE A, 中科院一区), ACM Transactions on Intelligent Systems and Technology 2020-2021 (JCR Q1), Information Systems 2020-2021 (CORE A*), and World Wide Web 2020-2021 and 2017-2018 (CORE A, CCF B). Dr. Yin has also been attracting wide media coverage, such as The Australian, The Australian Institute of Policy & Science (AIPS), Queensland Government, SBS Radio, UQ News, Sohu News, IEEE Computer Society, ACM Computing Reviews.

I am now looking for highly motivated Ph.D. students. The University of Queensland ranks in the top 50 as measured by the Performance Ranking of Scientific Papers for World Universities. The University also ranks 40 in the QS World University Rankings and 41 in the US News Best Global Universities Rankings. The University of Queensland is the best in Australia according to the Australian Financial Review (AFR), which has now ranked UQ in the #1 position for 2 consecutive years. Please find the following three PhD scholarships.

Latest News

  1. [30 August 2026] Our research work "Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation" was accepted by the top journal TKDE (CCF A, CORE A*).

  2. [17 August 2026] We have four research papers accpeted by the top conference ICDM 2026 (CORE A*).

  3. [12 August 2026] We have two research papers accpeted by the top conference CIKM 2026 (CORE A, CCF B).

  4. [11 August 2026] Our research work "RuleAgent: Discovering Rules for Recommendation Denoising with Autonomous Language Agents" was accepted by the top journal ACM TOIS (CCF A).

  5. [4 August 2026] I was invited to serve as Research Track Chair for ACM Web Conference 2027 (ACM Web 2027).

  6. [28 July 2026] I have been included in the "2026 AI 2000 Global Artificial Intelligence Scholars List" and awarded the "2026 AI 2000 Most Influential Scholar Award Honorable Mention" in both areas of "Data Mining" and "IR and Recommendation".

  7. [8 July 2026] I was honored to be invited to serve as a Senior Area Chair for the KDD 2027 conference.

  8. [1 July 2026] I was invited to serve as Symposium Chair for 2027 IEEE Symposium Series on Computational Intelligence (SSCI).

  9. [20 May 2026] Our ARC Linkage Project 2025 "AI-Powered Design Co-Pilot for Reimagining Australian Single-Family Homes" has been successfully granted and funded.

  10. [16 May 2026] We have three research papers accepted by the top conference KDD 2026 Research Track (CORE A*, CCF A, Acceptance Rate ~18%).

  11. [12 May 2026] I have been recognised in 2026 Edition of Best Scientists in the field of Computer Science and ranked 42 in Australia on Research.com, a leading academic platform.

  12. [8 May 2026] Our research paper "Efficient Prompt Learning for Traffic Forecasting" has been accepted by VLDB Journal (CORE A*, CCF A)

  13. [3 April 2026] We have 3 research papers accepted by the top conference SIGIR 2026.

    • Prompt-Unknown Promotion Attacks against LLM-based Sequential Recommender Systems

    • ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems

    • ProEchoMem: Enhancing Long Video Understanding via Multi-Trace Probe-Echo Memory

  14. [27 March 2026] We have successfully secured the opportunity to host the top-tier conference ICDM 2027 in Brisbane.

  15. [24 Feb 2026] We have 3 research papers on ChatBI accepted by the top conferences ICLR 2026 (CORE A*, CCF A) and ICDE 2026 (CORE A*, CCF A).

  16. [21 Feb 2026] I’m pleased to join the Organizing Committee of the premier conference WSDM 2027 as the Conference Awards Co-Chair.

  17. [18 Feb 2026] I’m pleased to join the Organizing Committee of the data mining flagship conference ADMA 2026 as the PC Co-Chair.

  18. [5 Feb 2026] We are organizing a workshop "LLM-UP: LLM-powered User Profiling for Search and Recommendation" at SIGIR 2026.

  19. [26 January 2026] We have 3 papers accepted by the top conference ICLR 2026 (CORE A*).

  20. [20 January 2026] I was invited to serve as Area Chair in the top conference KDD 2026 (CORE A*, CCF A), IJCAI 2026 (CORE A*, CCF A), ARR-ACL 2026 (CORE A*, CCF A) and ICDM 2026 (CORE A*, CCF B).

  21. [14 January] We have two research papers accepted by the top conference WWW 2026 (CORE A*, CCF A). Congratulations to Xinyi and Hung.

  22. [13 January 2025] We have two research papers recognized as ESI Hot Papers and five research papers recognized as ESI Highly Cited Papers.

  23. [19 December 2025] I was invited to serve as Area Chair in the top conference SIGIR 2026 (CORE A*, CCF A) and senior PC member at the top conference ICMR 2026 (CORE A, CCF B).

  24. [9 December 2025] I have been recognized as 2025 ScholarGPS Highly Ranked Scholar (top 0.05% of all scholars), #3 in Data Mining, #8 in Information Engineering.

  25. [8 November 2025] Our research paper "SmartAgent: Chain-of-User-Thought for Embodied Personalized Agent in Cyber World" was accepted by the top conference AAAI 2026 (CCF A and CORE A*). Congratulations to Jiaqi.

  26. [4 November 2025] We have released the first survey on Reasoning-Aware Recommender Systems in the LLM Era.

  27. [28 October 2025] My ARC Discovery Project 2026 "Advancing Federated Learning for Unified Urban Spatio-Temporal Predictions" has been successfully granted and funded.

  28. [13 October 2025] I was invited to be Area Chair for ACL Rolling Review (ARR).

  29. [1 October 2025] I have been recognised in the Stanford/Elsevier Top 2% Scientists List Career Long (2022-2025) and Single Year (2020-2025).

Availability

Professor Hongzhi Yin is:
Available for supervision

Qualifications

  • Postgraduate Diploma, Peking University
  • Doctor of Philosophy, Peking University

Research interests

  • Structured Foundation Model

  • Spatial-temporal Prediction

  • LLM and ChatBI

  • Recommender System and User Modeling

  • Edge Machine Learning and Applications

  • Time Series and Sequence Mining and Prediction

  • Trustworthy Machine Learning and Applications

Research impacts

Prof. Yin is currently directing the Responsible Big Data Intelligence Lab (RBDI). RBDI Lab aims and strives to develop decentralized, on-device, and trustworthy (e.g., privacy-preserving, robust, explainable and fair) data mining and machine learning techniques with theoretical backbones to better discover actionable patterns and intelligence from large-scale, heterogeneous, networked, dynamic and sparse data. RBDI joins forces with other fields such as urban transportation, healthcare, agriculture, E-commerce and marketing to help solve societal, environmental and economic challenges facing humanity in pursuit of a sustainable future. His research has also attracted media coverage, such as The Australian, SBS, UQ News, Faculty News of EAIT, ACM Computing Reviews, 360 News.

Search Professor Hongzhi Yin’s works on UQ eSpace

445 works between 2011 and 2026
All (445) Book (2) Journal Article (179) Edited Outputs (6) Conference Publication (255) Book Chapter (3)

161 - 180 of 445 works

2023

Conference Publication

Semantic-aware node synthesis for imbalanced heterogeneous information networks

Gao, Xinyi, Zhang, Wentao, Chen, Tong, Yu, Junliang, Nguyen, Hung Quoc Viet and Yin, Hongzhi (2023). Semantic-aware node synthesis for imbalanced heterogeneous information networks. 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom, 21–25 October 2023. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3583780.3615055

Semantic-aware node synthesis for imbalanced heterogeneous information networks

2023

Conference Publication

Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graph

Liu, Yi, Xuan, Hongrui, Li, Bohan, Wang, Meng, Chen, Tong and Yin, Hongzhi (2023). Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graph. 32nd ACM International Conference on Information and Knowledge Management (CIKM), Birmingham, United States, 21-25 October 2023. New York, NY, United States: ACM. doi: 10.1145/3583780.3615054

Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graph

2023

Journal Article

Efficient on-device session-based recommendation

Xia, Xin, Yu, Junliang, Wang, Qinyong, Yang, Chaoqun, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2023). Efficient on-device session-based recommendation. ACM Transactions on Information Systems, 41 (4) 102, 1-24. doi: 10.1145/3580364

Efficient on-device session-based recommendation

2023

Journal Article

Scalable maximal subgraph mining with backbone-preserving graph convolutions

Nguyen, Thanh Toan, Huynh, Thanh Trung, Weidlich, Matthias, Tho, Quan Thanh, Yin, Hongzhi, Aberer, Karl and Nguyen, Quoc Viet Hung (2023). Scalable maximal subgraph mining with backbone-preserving graph convolutions. Information Sciences, 644 119287, 119287. doi: 10.1016/j.ins.2023.119287

Scalable maximal subgraph mining with backbone-preserving graph convolutions

2023

Journal Article

Structure learning via meta-hyperedge for dynamic rumor detection

Sun, Xiangguo, Yin, Hongzhi, Liu, Bo, Meng, Qing, Cao, Jiuxin, Zhou, Alexander and Chen, Hongxu (2023). Structure learning via meta-hyperedge for dynamic rumor detection. IEEE Transactions on Knowledge and Data Engineering, 35 (9), 9128-9139. doi: 10.1109/tkde.2022.3221438

Structure learning via meta-hyperedge for dynamic rumor detection

2023

Conference Publication

Efficient bi-level optimization for recommendation denoising

Wang, Zongwei, Gao, Min, Li, Wentao, Yu, Junliang, Guo, Linxin and Yin, Hongzhi (2023). Efficient bi-level optimization for recommendation denoising. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, United States, 6-10 August 2023. New York, NY, United States: ACM. doi: 10.1145/3580305.3599324

Efficient bi-level optimization for recommendation denoising

2023

Journal Article

Trustworthy recommendation and search: introduction to the special section - part 2

Yin, Hongzhi, Sun, Yizhou, Xu, Guandong and Kanoulas, Evangelos (2023). Trustworthy recommendation and search: introduction to the special section - part 2. ACM Transactions on Information Systems, 41 (4) 82, 1-6. doi: 10.1145/3604776

Trustworthy recommendation and search: introduction to the special section - part 2

2023

Conference Publication

Model-agnostic decentralized collaborative learning for on-device POI recommendation

Long, Jing, Chen, Tong, Nguyen, Quoc Viet Hung, Xu, Guandong, Zheng, Kai and Yin, Hongzhi (2023). Model-agnostic decentralized collaborative learning for on-device POI recommendation. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591733

Model-agnostic decentralized collaborative learning for on-device POI recommendation

2023

Conference Publication

DREAM: adaptive reinforcement learning based on attention mechanism for temporal knowledge graph reasoning

Zheng, Shangfei, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Chen, Wei and Zhao, Lei (2023). DREAM: adaptive reinforcement learning based on attention mechanism for temporal knowledge graph reasoning. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23–27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591671

DREAM: adaptive reinforcement learning based on attention mechanism for temporal knowledge graph reasoning

2023

Conference Publication

Continuous input embedding size search for recommender systems

Qu, Yunke, Chen, Tong, Zhao, Xiangyu, Cui, Lizhen, Zheng, Kai and Yin, Hongzhi (2023). Continuous input embedding size search for recommender systems. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591653

Continuous input embedding size search for recommender systems

2023

Conference Publication

Manipulating federated recommender systems: poisoning with synthetic users and its countermeasures

Yuan, Wei, Nguyen, Quoc Viet Hung, He, Tieke, Chen, Liang and Yin, Hongzhi (2023). Manipulating federated recommender systems: poisoning with synthetic users and its countermeasures. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591722

Manipulating federated recommender systems: poisoning with synthetic users and its countermeasures

2023

Conference Publication

KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

Wang, Lingzhi, Chen, Tong, Yuan, Wei, Zeng, Xingshan, Wong, Kam-Fai and Yin, Hongzhi (2023). KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment. 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9 - 14 July 2023. Stroudsburg, PA United States: Association for Computational Linguistics. doi: 10.18653/v1/2023.acl-long.740

KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

2023

Journal Article

Spatial-temporal meta-path guided explainable crime prediction

Sun, Yuting, Chen, Tong and Yin, Hongzhi (2023). Spatial-temporal meta-path guided explainable crime prediction. World Wide Web, 26 (4), 2237-2263. doi: 10.1007/s11280-023-01137-3

Spatial-temporal meta-path guided explainable crime prediction

2023

Journal Article

Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1

Yin, Hongzhi, Sun, Yizhou, Xu, Guandong and Kanoulas, Evangelos (2023). Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1. ACM Transactions on Information Systems, 41 (3) 51, 1-5. doi: 10.1145/3579995

Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1

2023

Journal Article

Reinforcement learning-enhanced shared-account cross-domain sequential recommendation

Guo, Lei, Zhang, Jinyu, Chen, Tong, Wang, Xinhua and Yin, Hongzhi (2023). Reinforcement learning-enhanced shared-account cross-domain sequential recommendation. IEEE Transactions on Knowledge and Data Engineering, 35 (7), 7397-7411. doi: 10.1109/tkde.2022.3185101

Reinforcement learning-enhanced shared-account cross-domain sequential recommendation

2023

Conference Publication

Interaction-level membership inference attack against federated recommender systems

Yuan, Wei, Yang, Chaoqun, Nguyen, Quoc Viet Hung, Cui, Lizhen, He, Tieke and Yin, Hongzhi (2023). Interaction-level membership inference attack against federated recommender systems. The ACM Web Conference 2023, Austin, TX, United States, 30 April - 4 May 2023. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3543507.3583359

Interaction-level membership inference attack against federated recommender systems

2023

Conference Publication

Semi-decentralized federated ego graph learning for recommendation

Qu, Liang, Tang, Ningzhi, Zheng, Ruiqi, Nguyen, Quoc Viet Hung, Huang, Zi, Shi, Yuhui and Yin, Hongzhi (2023). Semi-decentralized federated ego graph learning for recommendation. The ACM Web Conference 2023, Austin, TX United States, 30 April - 4 May 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3543507.3583337

Semi-decentralized federated ego graph learning for recommendation

2023

Edited Outputs

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part IV

Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao and Hongzhi Yin eds. (2023). Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part IV. 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), Tianjin, China, 17-20 April 2023. Heidelberg, Germany: Springer.

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part IV

2023

Edited Outputs

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17-20, 2023, Proceedings, Part I

Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao and Hongzhi Yin eds. (2023). Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17-20, 2023, Proceedings, Part I. 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), Tianjin, China, 17-20 April 2023. Heidelberg, Germany: Springer.

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17-20, 2023, Proceedings, Part I

2023

Edited Outputs

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part II

Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao and Hongzhi Yin eds. (2023). Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part II. 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), Tianjin, China, 17-20 April 2023. Heidelberg, Germany: Springer.

Database systems for advanced applications: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part II

Current funding

  • 2027 - 2028
    AI-Powered Design Co-Pilot for Reimagining Australian Single-Family Homes
    ARC Linkage Projects
    Open grant
  • 2026 - 2029
    Advancing Federated Learning for Unified Urban Spatio-Temporal Predictions
    ARC Discovery Projects
    Open grant
  • 2025 - 2028
    Revolutionise Australian Strata Management with Large Language Models
    ARC Linkage Projects
    Open grant
  • 2025 - 2028
    Building an Aussie Information Recommendation System You Can Trust
    ARC Linkage Projects
    Open grant
  • 2024 - 2027
    Privacy-Aware and Personalised Explanation Overlays for Recommender Systems (ARC Discovery Project administered by Griffith University)
    ARC Discovery Projects
    Open grant
  • 2021 - 2027
    ARC Training Centre for Information Resilience
    ARC Industrial Transformation Training Centres
    Open grant

Past funding

  • 2022 - 2026
    Decentralised Collaborative Predictive Analytics on Personal Smart Devices
    ARC Future Fellowships
    Open grant
  • 2022 - 2023
    A Secured Smart Sensing and Industry Analytics Facility for Industry 4.0 (ARC LIEF application led by University of Technology Sydney)
    University of Technology Sydney
    Open grant
  • 2020 - 2021
    Developing a Privacy-Preserving and Energy-Efficient Mobile Recommender System Architecture
    UQ Foundation Research Excellence Awards
    Open grant
  • 2019 - 2024
    Challenging Big Data for Scalable, Robust and Real-time Recommendations
    ARC Discovery Projects
    Open grant
  • 2017 - 2020
    Monitoring Social Events for User Online Behaviour Analytics
    ARC Discovery Projects
    Open grant
  • 2016 - 2018
    Mobile User Modeling for Intelligent Recommendation
    ARC Discovery Early Career Researcher Award
    Open grant

Availability

Professor Hongzhi Yin is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • Building an Trustworthy Information Recommendation System

    Build a trustworthy information recommender system by spearheading the design and development of cutting-edge LLM4Rec techniques, misinformation filters, and privacy protection mechanisms.

    This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Supervision history

Current supervision

Completed supervision

Enquiries

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