I am a Ph.D. student in computer science (CS) at the University of Illinois Urbana–Champaign (UIUC), fortunately advised by Professor Hanghang Tong. Prior to this, I received an M.S. degree in CS at UIUC and a B.E. degree in operations research and a minor in statistics at Tsinghua University. My research interests lie broadly in machine learning (ML), with a current emphasis on theoretical foundations and methodological advances of language models.

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

Publications

Conference Papers

• [ICLR 2025] Ask, and it shall be given: On the Turing completeness of prompting
  Ruizhong Qiu, Zhe Xu, Wenxuan Bao, Hanghang Tong
  The Thirteenth International Conference on Learning Representations, 2025
  [Demo] | [Paper] | [Poster] | [arXiv]
• [ICLR 2025] How efficient is LLM-generated code? A rigorous & high-standard benchmark
  Ruizhong Qiu, Weiliang Will Zeng, James Ezick, Christopher Lott, Hanghang Tong
  The Thirteenth International Conference on Learning Representations, 2025
  [GitHub] | [HuggingFace] | [PyPI] | [Paper] | [Poster] | [arXiv]
• [ICML 2024] Gradient compressed sensing: A query-efficient gradient estimator for high-dimensional zeroth-order optimization
  Ruizhong Qiu, Hanghang Tong
  Proceedings of the 41st International Conference on Machine Learning, 2024
  [Code] | [Paper] | [Poster] | [arXiv]
• [ICML 2024] Graph mixup on approximate Gromov–Wasserstein geodesics
  Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He, Hanghang Tong
  Proceedings of the 41st International Conference on Machine Learning, 2024
  [Code] | [Paper]
• [ICML 2024] Class-imbalanced graph learning without class rebalancing
  Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong
  Proceedings of the 41st International Conference on Machine Learning, 2024
  [Code] | [Paper] | [arXiv]
• [NeurIPS 2024] Discrete-state continuous-time diffusion for graph generation
  Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong
  Advances in Neural Information Processing Systems 37, 2024
  [Code] | [Paper] | [arXiv]
• [NeurIPS 2024 Spotlight] BackTime: Backdoor attacks on multivariate time series forecasting
  Xiao Lin, Zhining Liu, Dongqi Fu, Ruizhong Qiu, Hanghang Tong
  Advances in Neural Information Processing Systems 37, 2024
  [Code] | [Paper] | [arXiv]
• [NeurIPS 2022] DIMES: A differentiable meta solver for combinatorial optimization problems
  Ruizhong Qiu*, Zhiqing Sun*, Yiming Yang
  Advances in Neural Information Processing Systems 35, 2022
  [Code] | [Paper] | [Slides] | [Poster] | [arXiv]
• [VLDB 2025] TUCKET: A tensor time series data structure for efficient and accurate factor analysis over time ranges
  Ruizhong Qiu*, Jun-Gi Jang*, Xiao Lin, Lihui Liu, Hanghang Tong
  Proceedings of the VLDB Endowment 17(13), 2024
  [Code] | [Paper] | [arXiv]
• [KDD 2025] Generalizable recommender system during temporal popularity distribution shifts
  Hyunsik Yoo, Ruizhong Qiu, Charlie Xu, Fei Wang, Hanghang Tong
  Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025
  [Code] | [Paper]
• [KDD 2024] AIM: Attributing, interpreting, mitigating data-encoded unfairness
  Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik Hamann, Hanghang Tong
  Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
  [Code] | [Paper] | [arXiv]
• [KDD 2023] Reconstructing graph diffusion history from a single snapshot
  Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong
  Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  [Code] | [Paper] | [Slides] | [Poster] | [arXiv]
• [KDD 2023] Networked time series imputation via position-aware graph enhanced variational autoencoders
  Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew J. Margenot, Hanghang Tong
  Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  [Paper] | [Extended] | [arXiv]
• [SIGIR 2025] Embracing plasticity: Balancing stability and plasticity in continual recommender systems
  Hyunsik Yoo, SeongKu Kang, Ruizhong Qiu, Charlie Xu, Fei Wang, Hanghang Tong
  Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
• [WWW 2024] Ensuring user-side fairness in dynamic recommender systems
  Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong
  Proceedings of the ACM Web Conference 2024, 2024
  [Code] | [Paper] | [Appendix] | [arXiv]
• [CIKM 2024] On the sensitivity of individual fairness: Measures and robust algorithms
  Xinyu He, Jian Kang, Ruizhong Qiu, Fei Wang, Jose Sepulveda, Hanghang Tong
  Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
• [FAccT 2024] Group fairness via group consensus
  Eunice Chan*, Zhining Liu*, Ruizhong Qiu, Yuheng Zhang, Ross Maciejewski, Hanghang Tong
  Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024
  [Paper]

Preprints

• 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
• Fair anomaly detection for imbalanced groups
  Ziwei Wu, Lecheng Zheng, Yuancheng Yu, Ruizhong Qiu, John Birge, Jingrui He
  arXiv preprint, 2024
• 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

* Equal contribution.

Experience

Work Experience

• Qualcomm AI Research | Research Engineering Intern
  Mixed-precision quantization of large vision models, June 4 – August 9, 2024
  Mentors: Burak Bartan, Weiliang Will Zeng
• Qualcomm AI Research | Research Engineering Intern
  Code generation with large language models, May 22 – August 4, 2023
  Mentor: Weiliang Will Zeng

Invited Talks

• Ask, and it shall be given: On the Turing completeness of prompting, Seminars on Formal Languages and Neural Networks (FLaNN), 2025
• Ask, and it shall be given: On the Turing completeness of prompting, Ploutos, 2025
• Reconstructing graph diffusion history from a single snapshot, Minisymposium on New Frontier of Graph Machine Learning, SIAM Conference on Mathematics of Data Science (MDS), 2024
• DIMES: A differentiable meta solver for combinatorial optimization problems, AI Time (in Chinese), 2022

Academic Service

• Program Committee Member, The 33rd ACM International Conference on Information and Knowledge Management (CIKM 2025)
• Reviewer, The Thirty-Nineth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)
• Program Committee Member (2 papers), 19th ACM Conference on Recommender Systems (RecSys 2025)
• Reviewer (5 papers), Forty-Second International Conference on Machine Learning (ICML 2025)
• Reviewer (5 papers), The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025)
• Reviewer (1 paper), IEEE Transactions on Big Data
• Reviewer (1 paper), The 2025 ACM Web Conference (WWW 2025)
• Reviewer (2 papers), The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025)
• Program Committee Member (1 paper), The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025)
• Reviewer (1 paper), The Thirteenth International Conference on Learning Representations (ICLR 2025)
• Reviewer (6 papers), The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
• Program Committee Member (2 papers), The 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024)
• Program Committee Member & Reviewer (7 papers), The 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024)

Awards

• Siebel Scholar, Class of 2024 (83 recipients in U.S.A., China, France, Italy, and Japan)
• Conference Presentation Award, UIUC Graduate College, Fall 2022
• NeurIPS Scholar Award, NeurIPS 2022
• Gold Medal (rank 6/353), ACM International Collegiate Programming Contest (ICPC), Asia QingDao Regional, 2018
• Silver Medal, National Olympiad in Informatics, China, 2017