Maggie(Ziwei) Wu

Maggie(Ziwei) Wu

University of Illinois, Urbana-Champaign

I am a final-year PhD student at University of Illinois at Urbana-Champaign (UIUC). I am fortunate to be advised by Professor Jingrui He. Before that, I completed my bachlor degree in Computer Science at University of Science and Technology of China (USTC). My research interest mainly lies in trustworthy machine learning with a special focus on fairness, robustness and scalability. I am particularly interested in applying these principles to critical real-world applications including medicare, e-commerce, and social systems. I am also interested in understanding bias in foundation models.

📖 Educations

  • 2020 - 2025 (expected), University of Illinois Urbana-Champaign

    Ph.D. in Information Sciences, Advisor: Prof. Jingrui He

  • 2016 - 2020, University of Science and Technology of China.

    Bachelor of Computer Science, Advisor: Prof. Xiangyang Li and Prof. Xiangnan He

📝 Publications

Preprint

  • Fair Anomaly Detection For Imbalanced Groups

    Ziwei Wu*, Lecheng Zheng*, Yuancheng Yu, Ruizhong Qiu, John Birge, Jingrui He

    preprint 2024.

  • Preference-aware Gradient Matching for Fairness

    Ziwei Wu, Yikun Ban, Jingrui He

    preprint 2024.

  • Rethinking Fairness in LLM Tabular Tasks: A Mixture of LoRA Experts Approach

    Ziwei Wu, Yiwei Cai, Rashid Islam

    preprint 2024.

  • Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative

    Zihao Li, Xiao Lin, Zhining Liu, Jiaru Zou, Ziwei Wu, Lecheng Zheng, Dongqi Fu, Yada Zhu, Hendrik Hamann, Hanghang Tong, Jingrui He

    preprint 2024.

Conference

  • Neural Active Learning Beyond Bandits.

    Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He

  • ICLR 2024.

     Code Paper

  • Training Fair Deep Neural Networks by Balancing Influence.

    Haonan Wang*, Ziwei Wu\*, Jingrui He

  • WSDM 2024.

     Code Paper

  • Deep Active Learning by Leveraging Training Dynamics.

    Haonan Wang, Wei Huang, Ziwei Wu, Andrew Margenot, Hanghang Tong, Jingrui He., Jingrui He

  • NeurIPS 2022.

     Code Paper

  • Fairness-aware Model-agnostic Positive and Unlabeled Learning. Distinguished Paper Award

    Ziwei Wu, Jingrui He

  • FAccT 2022.

     Code Paper

  • Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. Most Influential KDD Papers

    Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He

  • SIGKDD 2021.

     Code Paper

  • Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning.

    Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, Wei Wang.

  • ICDM 2020.

     Code Paper

🎖 Honors and Awards

  • Distinguished Paper Award of FAccT, 2022
  • Best Program Committee of CIKM, 2022
  • Most Influential KDD Papers, 2021
  • Valedictorian of Class of 2020 of USTC, 2020
  • Guo Moruo Scholarship (Summa Cum Laude), 2019
  • Tang Lixin Scholarship, 2018
  • National Scholarship of China, 2017