Zhuorui Ye

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Yao Class 13, Tsinghua University

cuizhuyefei at gmail dot com

I am Zhourui Ye, a senior undergraduate student majoring in Computer Science at IIIS, Tsinghua University (a.k.a. Yao Class, directed by Andrew Chi-Chih Yao).

My research interests broadly lie in machine learning. Currently, I am deeply fascinated by several topics under the general theme of human-centered AI, including explainability and alignment, with the goal of helping humans better interact with AI. I am also interested in the intersection of decision making and foundation models. In my research, I employ rigorous empirical study and principled thinking to understand things deeply.

I was a visiting intern in Professor Fei Fang’s group in CMU, also in collaboration with Professor Geoffrey J. Gordon and Professor Lei Li. Previously, I worked with Professor Farzan Farnia in Chinese University of Hong Kong, and Professor Li Yi in Tsinghua University. I appreciate the opportunities to work with all of my kind and amazing collaborators.

I am applying for PhD in 2025 Fall. I also love generally chatting about research or life. Feel free to reach out for any reason!

Selected Publications

  1. RLC Workshop
    Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels
    Zhuorui Ye*, Stephanie Milani*, Geoffrey J. Gordon, and Fei Fang
    2024
    RLC InterpPol Workshop 2024 (Oral), ICML AutoRL Workshop 2024
  2. EMNLP
    Sing it, Narrate it: Quality Musical Lyrics Translation
    Zhuorui Ye*, Jinhan Li*, and Rongwu Xu
    2024
    EMNLP 2024 (Findings)
  3. AAAI
    Semantic Complete Scene Forecasting from a 4D Dynamic Point Cloud Sequence
    Zifan Wang*Zhuorui Ye*, Haoran Wu*, Junyu Chen, and Li Yi
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2024
  4. Under Review
    On the Trade-Off between Stability and Fidelity of Gaussian-Smoothed Saliency Maps
    Zhuorui Ye, and Farzan Farnia
    2024
    Under Review
  5. Under Review
    Cooperative Strategic Planning Enhances Reasoning Capabilities in Large Language Models
    Danqing Wang, Zhuorui Ye, Fei Fang, and Lei Li
    2024
    Under Review