Hongzhi Yin

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 predictive analytics, recommendation systems, graph learning, social media analytics, 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, Rising Star of Science Award (2022-2024) and 2024 Computer Science in Australia Leader Award, AI 2000 Most Influential Scholar Honorable Mention in Data Mining (2022-2025). 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 over 350+ papers with an H-index of 86 (24000+ citations), including 280+ CCF A/CORE A* and 70+ CCF B/CORE A, such as ICML, KDD, SIGIR, WWW, ACL, WSDM, SIGMOD, VLDB, ICDE, NeurIPS, AAAI, IJCAI, ACM Multimedia, ECCV, IEEE TKDE, TNNL, VLDB Journal, and ACM TOIS. He has been the leading author (first/co-first author or corresponding author) for 250+. He has been an SPC/PC member for many top conferences, such as AAAI, IJCAI, KDD, ICML, ICLR, NeurIPS, SIGIR, WWW, WSDM, VLDB, ICDE, ICDM, and CIKM. 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, SBS Radio Interviews, UQ News, Sohu.com, Faculty News of EAIT, 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 two PhD scholarships.

• https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/building-trustworthy-information-recommendation-system

• https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/build-trustworthy-information-recommendation-system

Latest News

1. [28 August 2025] I have been recognised in the "2025 AI 2000 Global Artificial Intelligence Scholars List" and awarded the "2025 AI 2000 Most Influential Scholar Award Honorable Mention" in both areas of Data Mining (Ranked #43) and IR and Recommendation (Ranked #60).

2. [26 August 2025] Our research work "Towards Propagation-aware Representation Learning for Supervised Social Media Graph Analytics" was accetped as regular research paper by the top confernce ICDM 2025 (CORE A*, acceptance rate 13.5%).

3. [5 August 2025] We have 4 research papers accepted by the top conference CIKM 2025 (CORE A).

   • Harnessing Large Language Models for Group POI Recommendations

   • Efficient Multimodal Streaming Recommendation via Expandable Side Mixture-of-Experts

   • HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning

   • NR-GCF: Graph Collaborative Filtering with Improved Noise Resistance

4. [10 July 2025] Our survey paper "On-Device Recommender Systems: A Comprehensive Survey" has been accepted by Data Science and Engineering (Q1, 中科院一区).

5. [25 June 2025] Our ARC Linkage Project "Revolutionise Australian Strata Management with Large Language Model" has been granted and funded.

6. [5 May 2025] I was invited to serve as Area Chair for the top data mining conference ICDM 2025 (CORE A*).

7. [23 May 2025] I was ranked #52 in Australia among Best Scientists for 2025 and have also been recognized with the Computer Science Leader Award for 2025 in Research.com.

8. [15 May 2025] We have four research papers and one applied data science paper accepted by the top conference KDD 2025 (CORE A*, CCF A).

   • Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation

   • Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning

   • Data Watermarking for Sequential Recommender Systems

   • FLUID-MMRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation

   • Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems

9. [11 May 2025] Our research work "RobGC: Towards Robust Graph Condensation" has been accepted by the top journal TKDE 2025 (CORE A*, CCF A). Congratulations to Xinyi.

10. [1 May 2025] Our research work "Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective" has been accepted by the top conference ICML 2025 (CORE A*, CCF A). Congratulations to Hechuan.

11. [4 April 2025] We have four full research papers accepted by the top conference SIGIR 2025 (CORE A*, CCF A).

    • ID-Free Not Risk-Free: LLM-Powered Agents Unveil Risks in ID-Free Recommender Systems

    • Diversity-aware Dual-promotion Poisoning Attack on Sequential Recommendation

    • Towards Distribution Matching between Collaborative and Language Spaces for Generative Recommendation

    • STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation

12. [2 April 2025] Congratulations to the four new doctors, Dr. Wei Yuan, Dr. Jing Long, Dr. Yuting Sun and Dr. Ruiqi Zheng, who were awarded their PhD by The University of Queensland.

13. [10 March 2025] Our survey paper "A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security " has been accepted by TKDE 2025 (CORE A*, CCF A).

14. [21 Feb 2025] Our joint foundation work "On the Trustworthiness of Generative Foundation Models– Guideline, Assessment, and Perspective" has been released on both arXiv and Hugging Face. This research is the result of a broad collaboration with leading universities and research institutions worldwide, including the University of Notre Dame, Massachusetts Institute of Technology, University of Waterloo, Carnegie Mellon University, University of Illinois Urbana-Champaign, Stanford University, University of California, Santa Barbara, IBM Research, Microsoft Research, The University of Queensland and more.

15. [20 Feb 2025] I have been recognized as a Highly Ranked Scholar - Prior 5 Years (top 0.05% of all scholars) and #15 in Data Mining on ScholarGPS.

16. [26 January 2025] Our survey paper "Graph Condensation: A Survey" has been accepted by TKDE 2025 (CORE A*, CCF A).

17. [20 January 2025] We have three full research papers and one demo paper accepted by the top conference WWW 2025 (CORE A*, CCF A).

    • Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition

    • On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective

    • Epidemiology-informed Network for Robust Rumor Detection

    • BiasNavi: LLM-Empowered Data Bias Management

18. [18 January 2025] We have two research papers accepted by AAAI 2025 (CCF A, CORE A*) for Oral Presentation.

    • Efficient Traffic Prediction through Spatio-Temporal Distillation

    • Rethinking Cancer Gene Identification through Graph Anomaly Analysis