Wei Yuan

Wei Yuan

Ph.D. student at The University of Queensland (UQ).

Bio

I am a final-year PhD student at the School of Electrical Engineering and Computer Science, The University of Queensland (UQ), supervised by Prof. Hongzhi Yin. My research mainly focuses on Recommender Systems and Decentralized Learning. Before at UQ, I received my Master’s degree from Nanjing University supervised by A/Prof Tieke He. Outside of research, I like powerlifting and swimming.

Education and Research Experience

  • PhD, Data Science, University of Queensland, Australia, 2022.01 ~ present.
  • Research Assistant, Nanjing University, 2021.07 ~ 2021.12.
  • MS, Software Engineering, Nanjing University, China, 2019.09 ~ 2021.06.
  • BS, Software Engineering, Southwest Jiaotong University, China, 2015.09 ~ 2019.06.

Research Interests

  • Recommender System
  • Urban Computing
  • Federated/Decentralized Learning and Edge Intelligence,
  • Information Security
  • Natural Language Generation.

News

  • (13/09/2024) I have been invited to serve as PC for the Australasian Database Conference (ADC) 2024.
  • (04/09/2024) One co-authored paper titled “PDC-FRS: Privacy-preserving Data Contribution for Federated Recommender System” has been accepted by ADMA 2024 (CCF C).
  • (15/08/2024) I have been invited to serve as PC for the top conference WWW 2025 (CCF A, CORE A*).
  • (16/07/2024) One co-authored paper titled “Watermarking Recommender Systems” has been accepted by CIKM 2024 (CCF B, CORE A).
  • (06/06/2024) We have released a survey for poisoning attacks and defenses in recommendations: Poisoning Attacks and Defenses in Recommender Systems: A Survey.
  • (22/05/2024) One co-authored paper titled “Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion” has been accepted by the journal ACM Transactions on Information Systems (TOIS) 2024 (CCF A, CORE A).
  • (11/03/2024) I have been invited to serve as PC for the top conference CIKM 2024 (CCF B, CORE A).
  • (11/02/2024) One co-authored paper titled “Hide Your Model: A Parameter Transmission-free Federated Recommender System” has been accepted by the top conference ICDE 2024 (CCF A, CORE A*).
  • (23/01/2024) One co-authored paper titled “Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation” has been accepted by the top conference WWW 2024 (CCF A, CORE A*).
  • (22/01/2024) We have released a survey for on-device recommender systems: On-Device Recommender Systems: A Comprehensive Survey.
  • (21/01/2024) I have been invited to serve as PC for the top conference KDD 2024 (CCF A, CORE A*).

Academic Services

  • PC member: CIKM 2023/2024, The Web Conference (WWW) 2024/2025, KDD 2024, ADC 2024.
  • Journal reviewer: TKDE, TOIS, TKDD, Neural Networks, Science China Information Science, etc.

Publications

  1. Chaoqun Yang, Wei Yuan, Liang Qu, Thanh Tam Nguyen: PDC-FRS: Privacy-preserving Data Contribution for Federated Recommender System. ADMA 2024. (CCF C)
  2. Sixiao Zhang, Cheng Long, Wei Yuan, Hongxu Chen, Hongzhi Yin: Watermarking Recommender Systems. CIKM 2024 (CCF B, CORE A)
  3. Lijian Chen, Wei Yuan*, Tong Chen, Quoc Viet Hung Nguyen, Lizhen Cui, Hongzhi Yin: Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion. TOIS 2024 (CCF A, CORE A). *Contributing equally with the first author.
  4. Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin: Hide Your Model: A Parameter Transmission-free Federated Recommender System. ICDE 2024 (CCF A, CORE A*)
  5. Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin: Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation. WWW 2024 (CCF A, CORE A*).
  6. Wei Yuan, Liang Qu, Lizhen Cui, Yongxin Tong, Xiaofang Zhou, Hongzhi Yin: HeteFedRec: Federated Recommender Systems with Model Heterogeneity. ICDE 2024 (CCF A, CORE A*).
  7. Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin: Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures. TOIS 2023 (CCF A, CORE A).
  8. Shijie Zhang, Wei Yuan, Hongzhi Yin: Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks. TKDE 2023 (CCF A, CORE A*).
  9. Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, Hongzhi Yin: KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment. ACL 2023 (CCF A, CORE A*).
  10. Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin: Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures. SIGIR 2023 (CCF A, CORE A*, Code).
  11. Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He, Hongzhi Yin: Interaction-level Membership Inference Attack Against Federated Recommender Systems. WWW 2023 (CCF A, CORE A*).
  12. Wei Yuan, Hongzhi Yin, Fangzhao Wu, Shijie Zhang, Tieke He, Hao Wang: Federated Unlearning for On-Device Recommendation. WSDM 2023 (CCF B, CORE A*, Code).
  13. Wei Yuan, Quanjun Zhang, Tieke He, Chunrong Fang, Nguyen Quoc Viet Hung, Xiaodong Hao, Hongzhi Yin: CIRCLE: Continual Repair across Programming Languages. ISSTA 2022 (CCF A, CORE A).
  14. Wei Yuan, Hongzhi Yin, Tieke He, Tong Chen, Qiufeng Wang, Lizhen Cui: Unified Question Generation with Continual Lifelong Learning. WWW 2022 (CCF A, CORE A*).
  15. Wei Yuan, Tieke He, Xinyu Dai: Improving Neural Question Generation using Deep Linguistic Representation. WWW 2021 (CCF A, CORE A*).
  16. Chao Guo, Tieke He, Wei Yuan, Yue Guo, Rui Hao: Crowdsourced Requirements Generation for Automatic Testing via Knowledge Graph. ISSTA 2020 (CCF A, CORE A).
  17. Yifei Yang, Wei Yuan, Yansong Li, Desheng Wang, Jia Liu, Tieke He: An Empirical Study of Law Articles Prediction on Transportation Legal Cases. DSA 2020.
  18. Wei Yuan, Peng Wang, Mengyao Yuan, Yue Guo, Tieke He: N2One: Identifying Coreference Object Among User Generated Content with Siamese Network. WISA 2020.
  19. Wei Yuan, Peng Wang, Yue Guo, Linyang He, Tieke He: Mining the Software Engineering Forums: What’s New and What’s Left. WISA 2020.

Teaching Assistantship

  1. Social Media Analytics, The University of Queensland
  2. Comprehensive Practice and Application of Data Science, Nanjing University
  3. Fundamentals of Computer Systems, Nanjing University
  4. Big Data Analysis, Nanjing University

Awards & Honor

  1. SIGIR Student Travel Grant, 2023
  2. UQ-CSC Full Ph.D. Scholarship (2022.01 - 2025.12)
  3. School Outstanding Student, Nanjing University, 2020.12
  4. Second-class Talent Scholarship, Nanjing University, 2020.11
  5. Ranked Top-1 (with both preliminary and final scores) in the national postgraduate entrance exam of the Software Engineering of Nanjing University, 2019

Motto

The way of study and inquiry is none other than the search for the lost mind. (Mencius)
学问之道无他,求其放心而已矣。《孟子.告子章句上》