Weixin Chen  Ph.D. Student HCI-RecSys Group Department of Computer Science Faculty of Science, Hong Kong Baptist University Kowloon Tong, Hong Kong SAR [Google Scholar] [Github] [Twitter] [LinkedIn] E-mail: me@weixinchen.com Address: DLB 625, Level 6, David C. Lam Building, Shaw Campus, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR

Recent News

• [2025.09] Happy to join in Rutgers WISE Lab as a visiting student researcher!
• [2025.07] One paper is accepted by RecSys 2025.
• [2025.06] One paper is accepted by TOIS 2025.
• [2025.03] One paper is accepted by TORS 2025.
• [2022.09] Start my PhD journey @ HKBU COMP.
• [2022.06] One paper is accepted by RecSys 2022.

About Me

I am currently visiting Prof. Yongfeng Zhang at the Department of Computer Science, Rutgers University, from September, 2025. I am a fourth-year Ph.D. student at HCI-RecSys Group in the Department of Computer Science, Hong Kong Baptist University, advised by Prof. Li Chen. Before that, I received my B.Eng. degree from Shenzhen University in 2020, advised by Prof. Weike Pan.

My current research focuses on fairness in recommendation and large language models (LLMs).

Research Experience

• Visiting PhD Student, 2025.09 - Present
  WISE Lab, Department of Computer Science, Rutgers University
  Advised by Prof. Yongfeng Zhang
  New Brunswick, New Jersey, United States

Education

• Ph.D. student, 2022.09 - 2026.08 (expected)
  Department of Computer Science, Faculty of Science
  Hong Kong Baptist University (HKBU), Hong Kong

• B.Eng., 2016.09 - 2020.06
  College of Computer Science & Software Engineering
  Shenzhen University (SZU), Shenzhen, China

Publication

• W. Chen*, Y. Zhao*, L. Chen, W. Pan.
  Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users.
  In ACM Conference on Recommender Systems (RecSys 2025), Prague, 2025. Fairness Cross-domain
  [PDF] [Code] [Slides] [Poster] [Video] [BibTeX] [Spotlight Oral] Loading citations...

  @inproceedings{chen2025leave,
      title        = {Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users},
      author       = {Chen, Weixin and Zhao, Yuhan and Chen, Li and Pan, Weike},
      year         = 2025,
      booktitle    = {Proceedings of the 19th ACM Conference on Recommender Systems (RecSys'25)},
  }

• W. Chen, L. Chen, Y. Ni, Y. Zhao.
  Causality-Inspired Fair Representation Learning for Multimodal Recommendation.
  In ACM Transactions on Information Systems (TOIS), 2025. Fairness Multimodal
  [PDF] [Code] [BibTeX] Loading citations...

  @article{chen2025causality,
      title        = {Causality-Inspired Fair Representation Learning for Multimodal Recommendation},
      author       = {Chen, Weixin and Chen, Li and Ni, Yongxin and Zhao, Yuhan},
      year         = 2025,
      journal    = {ACM Transactions on Information Systems},
      volume = {43},
      number = {6},
      articleno = {153},
      numpages = {29},
  }

• W. Chen, Y. Zhao, L. Chen.
  Investigating User-Side Fairness in Outcome and Process for Multi-Type Sensitive Attributes in Recommendations.
  In ACM Transactions on Recommender Systems (TORS), 2025. Fairness
  [PDF] [Code] [BibTeX] Loading citations...

  @article{chen2025investigating,
      title        = {Investigating User-side fairness in outcome and process for multi-type sensitive attributes in recommendations},
      author       = {Chen, Weixin and Chen, Li and Zhao, Yuhan},
      year         = 2025,
      journal    = {ACM Transactions on Recommender Systems},
  }

• W. Chen, M. He, Y. Ni, W. Pan, Z. Ming, L. Chen.
  Global and Personalized Graphs for Heterogeneous Sequential Recommendation by Learning Behavior Transitions and User Intentions.
  In ACM Conference on Recommender Systems (RecSys 2022), Seattle, 2022. Sequential
  [PDF] [Code] [Video] [BibTeX] [Oral] Loading citations...

  @inproceedings{chen2022global,
      title        = {Global and personalized graphs for heterogeneous sequential recommendation by learning behavior transitions and user intentions},
      author       = {Chen, Weixin and He, Mingkai and Ni, Yongxin and Pan, Weike and Chen, Li and Ming, Zhong},
      year         = 2022,
      booktitle    = {Proceedings of the 16th ACM Conference on Recommender Systems (RecSys'22)},
      pages        = {268--277}
  }

• R. Lai, L. Chen, W. Chen, R. Chen.
  Matryoshka Representation Learning for Recommendation.
  arXiv preprint arXiv:2406.07432, 2024. Sequential
  [PDF] [Code] [BibTeX] Loading citations...

  @article{lai2024matryoshka,
      title        = {Matryoshka Representation Learning for Recommendation},
      author       = {Lai, Riwei and Chen, Li and Chen, Weixin and Chen, Rui},
      year         = 2024,
      journal      = {arXiv preprint arXiv:2406.07432},
      url          = {https://arxiv.org/abs/2406.07432}
  }

Honors & Award

• (Excellent) Teaching Assistant Performance Award, HKBU (2023, 2024)
• Star of SZU (荔园之星), SZU (2017)
• University Scholarship, SZU (2017, 2018, 2019)

Teaching

(Assistance in following courses)

• COMP7250(PG): Data Security and Privacy, Fall (2025)

• COMP7240(PG): Recommender Systems, Fall (2023, 2024)

• COMP3005(UG): Design and Analysis of Algorithms, Spring (2023, 2024)

• COMP4135(UG): Recommender Systems and Applications, Fall (2023, 2024)

• COMP4127(UG): Information Security, Fall (2025)

Academic Service

• Conference Reviewer: WWW (2023), RecSys (2025).
• Journal Reviewer: JiiS (2022), TiiS (2023), TORS (2025), TKDE (2025).