About

I am an M.S. student in computer science at UIUC, fortunately advised by Dr. Hanghang Tong. Prior to this, I obtained my B.E. degree in industrial engineering at Tsinghua University. My research interests lie broadly in graph machine learning, with a current emphasis on discrete and combinatorial problems on graphs.

Education

• University of Illinois Urbana-Champaign | Siebel School of Computing and Data Science
  Doctor of Philosophy in Computer Science, August 2024 – May 2027 (Expected)
  Advisor: Hanghang Tong
• University of Illinois Urbana-Champaign | Siebel School of Computing and Data Science
  Master of Science in Computer Science, August 2022 – May 2024
  Advisor: Hanghang Tong
• Tsinghua University | Department of Industrial Engineering
  Bachelor of Engineering in Industrial Engineering, August 2018 – June 2022

Experience

• Qualcomm AI Research | Research Intern
  Code generation with large language models, May – August 2023

Publications

• [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
• [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
• [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
• [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]
• [WebConf 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]
• [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]
• [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]
• [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]

Honors

• Siebel Scholar, Class of 2024 (83 recipients across 16 universities worldwide)
• UIUC Graduate College Conference Presentation Award, Fall 2022
• NeurIPS Scholar Award, 2022