Ruizhong Qiu

rq5 AT illinois DOT edu
[Google Scholar] | [LinkedIn] | [GitHub]
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Hi there! I am a Ph.D. student in computer science at the University of Illinois Urbana–Champaign (UIUC), fortunately advised by Professor Hanghang Tong. Prior to this, I earned an M.S. degree in computer science at UIUC and a B.E. degree in operations research and a minor in statistics at Tsinghua University. I have worked on large language models (LLMs) & agents, graph machine learning, and time series analysis. My research interests lie broadly in theoretical foundations and methodological advances of machine learning (ML).

Experience

  • Jump Trading | Quantitative Researcher Intern | New York, NY
    June 15 – August 21, 2026
  • Meta AI | Part-Time Student Researcher | Remote
    Reinforcement routing for mixtures of LoRAs in LLM finetuning, August 25 – December 12, 2025
    Mentors: Hanqing Zeng, Yinglong Xia
  • Meta AI | Research Scientist Intern | Menlo Park, CA
    Soft graph clustering for LLM-based generative recommendation, May 19 – August 15, 2025
    Mentors: Yinglong Xia, Hanqing Zeng
  • Qualcomm AI Research | Research Engineering Intern | San Diego, CA
    Automatic mixed-precision quantization of diffusion models, June 4 – August 9, 2024
    Mentors: Burak Bartan, Weiliang Will Zeng
  • Qualcomm AI Research | Research Engineering Intern | San Diego, CA
    Code generation with large language models, May 22 – August 4, 2023
    Mentor: Weiliang Will Zeng

Education

  • University of Illinois Urbana–Champaign | Siebel School of Computing and Data Science
    M.S. & Ph.D. in Computer Science, Fall 2022 – Spring 2027 (Expected)
    Advisor: Professor Hanghang Tong
  • Tsinghua University | Department of Industrial Engineering
    B.E. in Operations Research & Minor in Statistics, Fall 2018 – Spring 2022

Research

Large Language Models & Agents
Graph Machine Learning
Time Series Analysis

* Equal contribution.

Awards

Publications

Conference Papers
Journal Papers
Workshop Papers
Preprints
  • Hierarchical credit assignment for RLVR on fused Gromov–Wasserstein geometry
    Qi Yu, Ruizhong Qiu, Zhichen Zeng, Xuying Ning, Yanjun Zhao, Dongqi Fu, Yinglong Xia, Hong Li, Hanghang Tong
    arXiv preprint, 2026
    [arXiv]
  • From inference to adaptation: A unified optimal transport view of vision language model
    Qi Yu, Zhichen Zeng, Katherine Tieu, Xiyuan Yang, Ruizhong Qiu, Yuchen Yan, Lihui Liu, Yanjun Zhao, Lingjie Chen, Jingrui He, Hanghang Tong
    arXiv preprint, 2026
    [arXiv]
  • Code as agent harness
    Xuying Ning*, Katherine Tieu*, Dongqi Fu*, Tianxin Wei*, Zihao Li*, Yuanchen Bei*, Jiaru Zou, Mengting Ai, Zhining Liu, Ting-Wei Li, Lingjie Chen, Yanjun Zhao, Ke Yang, Bingxuan Li, Cheng Qian, Gaotang Li, Xiao Lin, Zhichen Zeng, Ruizhong Qiu, Sirui Chen, Yifan Sun, Xiyuan Yang, Ruida Wang, Rui Pan, Chenyuan Yang, Dylan Zhang, Liri Fang, Zikun Cui, Yang Cao, Pan Chen, Dorothy Sun, Ren Chen, Mahesh Srinivasan, Nipun Mathur, Yinglong Xia, Hong Li, Hong Yan, Pan Lu, Lingming Zhang, Tong Zhang, Hanghang Tong, Jingrui He
    arXiv preprint, 2026
    [arXiv]
  • PolymerArena: Benchmarking multi-task graph learning models on polymer property prediction
    Yinqi Zeng, Ruizhong Qiu, Yuanchen Bei, Hanghang Tong, Renjie Li
    ChemRxiv preprint, 2026
    [ChemRxiv]
  • Hierarchical LoRA MoE for efficient CTR model scaling
    Zhichen Zeng, Mengyue Hang, Xiaolong Liu, Xiaoyi Liu, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Zhining Liu, Siyang Yuan, Chaofei Yang, Yiqun Liu, Hang Yin, Jiyan Yang, Hanghang Tong
    arXiv preprint, 2025
    [arXiv]
  • WAPITI: A watermark for finetuned open-source LLMs
    Lingjie Chen*, Ruizhong Qiu*, Siyu Yuan, Zhining Liu, Tianxin Wei, Hyunsik Yoo, Zhichen Zeng, Deqing Yang
    arXiv preprint, 2024
    [Code] | [arXiv]
  • Logic query of thoughts: Guiding large language models to answer complex logic queries with knowledge graphs
    Lihui Liu, Zihao Wang, Ruizhong Qiu, Yikun Ban, Eunice Chan, Yangqiu Song, Jingrui He, Hanghang Tong
    arXiv preprint, 2024
    [arXiv]

* Equal contribution.

Activities

Invited Talks
Academic Service