Hongyi Wen

(pronounced as: HongE When)

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🏢S712, Qiantan Campus

I’m an Assistant Professor of Computer Science at NYU Shanghai. Prior to that, I received my Ph.D. in Information Science from Cornell University advised by Deborah Estrin. I hold a B.Eng in Computer Science from Tsinghua University.

My research interest lies in developing human-in-the-loop machine learning systems and improving long-term values of personalizations. I lead the Multimodal Agentic Personalization Systems (MAPS) research group at NYU Shanghai. Our recent work focuses on Generative Models and their applications in Personalizations for Learning and Creativity.

📢 I’m looking for PhDs to join our research group. Check our PhD program and contact me at hongyi.wen@nyu.edu if you are interested in the following topics:

  • Understanding Generative Models(LLM, Diffusion, etc) and making them more personalized for individual users
  • AI for Learning and Creativity, especially for educational purposes

selected publications

  1. ICCV
    ImageGem: In-the-wild Generative Image Interaction Dataset for Generative Model Personalization
    Guo, Yuanhe, Xie, Linxi, Chen, Zhuoran, Yu, Kangrui, Po, Ryan, Yang, Guandao, Wetztein, Gordon, and Wen, Hongyi
    2025
  2. EMNLP
    Reveal and Release: Iterative LLM Unlearning with Self-generated Data
    Xie, Linxi, Teng, Xin, Ke, Shichang,  Wen, Hongyi, and Wang, Shengjie
    2025
  3. WSDM
    GEMRec: Towards Generative Model Recommendation
    Guo, Yuanhe, Liu, Haoming, and Wen, Hongyi
    Proceedings of ACM International Conference on Web Search and Data Mining 2024
  4. preprint
    Diffusion Cocktail: Fused Generation from Diffusion Models
    Liu, Haoming, Guo, Yuanhe, Wang, Shengjie, and Wen, Hongyi
    arXiv preprint arXiv:2312.08873 2023
  5. WWW
    Distributionally-robust Recommendations for Improving Worst-case User Experience
    Wen, Hongyi, Yi, Xinyang, Yao, Tiansheng, Tang, Jiaxi, Hong, Lichan, and Chi, Ed H
    In Proceedings of the ACM Web Conference 2022
  6. RecSys
    Revisiting adversarially learned injection attacks against recommender systems
    Tang, Jiaxi,  Wen, Hongyi, and Wang, Ke
    In Fourteenth ACM conference on recommender systems 2020