Junliang YU

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Email: jl.yu at uq.edu.au

Hello, this is Junliang Yu. I am currently a Postdoctoral Research Fellow with the Data Science discipline at The University of Queensland, where I work closely 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, where I was supervised by Prof. Min Gao. I am dedicated to conducting influential and reproducible research. My work has received over 3,200 citations as of September 2024, with five of my conference papers being recognized as The Most Influential Papers by Paper Digest and three of my journal papers being recognized as ESI Hot / Highly Cited Papers in my research areas. I am also actively involved in the open-source community and have developed two popular recommender system frameworks, QRec and SELFRec, which have together garnered over 2,000 stars.

Research Interests

:fire: I will commence my ARC DECRA Fellowship in 2025. Two fully funded PhD scholarships are available—one for an international student and one for a domestic student, with flexible enrolment in 2025. The PhD candidates will be co-supervised by me and Prof. Hongzhi Yin (associate supervisor). If you are interested in recommender systems and data science, please feel free to drop me an email.



News

Oct 4, 2024 We have released a survey preprint on point-of-interest recommender systems.
Sep 20, 2024 We have released a preprint on LLM-powered attack against ID-free recommender systems.
Aug 24, 2024 I have been awarded the ARC DECRA Fellowship.
May 24, 2024 We have released a preprint on graph condensation acceleration.
May 17, 2024 Two co-authored papers on poisoning attacks and contrastive learning are accepted by KDD.
Feb 17, 2024 I have been awarded the 2023 UQ Dean’s Award for Outstanding Higher Degree by Research Theses.
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.

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

    ESI Highly Cited Paper

  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

  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

    ESI Hot and Highly Cited Paper

  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

    One of the most influential papers in KDD’21

  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

  6. TKDE
    Enhancing social recommendation with adversarial graph convolutional networks
    Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, and Lizhen Cui
    IEEE Transactions on Knowledge and Data Engineering, 2020

    ESI Highly Cited Paper