Junliang YU

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Email: jl dot yu at uq.edu.au

Hello, this is Junliang Yu (余俊良 in Chinese). I am currently a postdoctoral research fellow in Data Science at The University of Queensland, working with Prof. Hongzhi Yin and Prof. Shazia Sadiq. Prior to starting my postdoc in 2023, I completed my PhD degree at The University of Queensland under the supervision of Prof. Hongzhi Yin. Before that, I earned my M.Sc. and B.E. degrees at Chongqing University, supervised by Prof. Min Gao. I am dedicated to conducting influential and reproducible research. To date, I have six papers recognized as either the most influential or as ESI highly cited papers.

Research Interests

Academic Services


News

May 17, 2024 Two co-authored papers on poisoning attacks and contrastive learning are accepted by KDD.
Feb 17, 2024 I have received the 2023 UQ Dean’s Award for Outstanding Higher Degree by Research Theses (link).
Jan 23, 2024 We have a paper on prompt learning and cross-domain recommendation accepted by WWW.
Jan 23, 2024 We have released a survey on Graph Condensation [link].
Jan 4, 2024 We have released a survey on poisoning attacks against recommender systems [link].

Selected Publications

  1. TKDE
    XSimGCL: Towards extremely simple graph contrastive learning for recommendation
    Junliang Yu, Xin Xia, Tong Chen, Lizhen Cui, Nguyen Quoc Viet Hung, and Hongzhi Yin
    IEEE Transactions on Knowledge and Data Engineering, 2023
    PDF Code
  2. SIGIR
    Are graph augmentations necessary? simple graph contrastive learning for recommendation
    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, and Quoc Viet Hung Nguyen
    Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

    *The most cited paper in SIGIR’22, applied in Tencent Music.

    PDF Code
  3. TKDE
    Self-supervised learning for recommender systems: A survey
    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, and Zi Huang
    IEEE Transactions on Knowledge and Data Engineering, 2022
    PDF Code
  4. KDD
    Socially-aware self-supervised tri-training for recommendation
    Junliang Yu, Hongzhi Yin, Min Gao, Xin Xia, Xiangliang Zhang, and Nguyen Quoc Viet Hung
    Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021
    PDF Code
  5. WWW
    Self-supervised multi-channel hypergraph convolutional network for social recommendation
    Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang
    Proceedings of the Web Conference, 2021

    *The 2nd most cited paper in WWW’21.

    PDF Code
  6. CIKM
    Adaptive implicit friends identification over heterogeneous network for social recommendation
    Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin, and Huan Liu
    Proceedings of the 27th ACM international conference on information and knowledge management, 2018
    PDF Code