Shuang Qiu I am a research assistant professor in the Department of Mathematics at the Hong Kong University of Science and Technology. I was a postdoc in the Department of Mathematics at the Hong Kong University of Science and Technology working with Prof. Tong Zhang and in the Booth School of Business at the University of Chicago working with Prof. Mladen Kolar and Prof. Zhaoran Wang. I received my Ph.D. degree in Computer Science and Engineering from the University of Michigan, Ann Arbor in 2021, advised by Prof. Jieping Ye. Previously, I did my internship at Tencent AI Lab, Seattle in 2018, working with Dr. Ji Liu.


[Interest]        [Publication]        [Grant]        [Service]


Research Interest

My recent research interest generally focuses on solving sequential decision-making problems, which lies at the intersection of reinforcement learning, game theory, optimization, and statistical learning. In addition, I am also interested in the application of machine learning to the various areas such as large language models, econometrics, computer vision, and data mining.
  • Reinforcement Learning and Games
  • Optimization
  • Statistical Learning
  • Applications in Large Language Models, Econometrics, Computer Vision, and Data Mining


Selected Recent Publication [Full List]


Rewards-in-Context: Multi-Objective Alignment of Foundation Models with Dynamic Preference Adjustment
Rui Yang*, Xiaoman Pan*, Feng Luo*, Shuang Qiu*, Han Zhong, Dong Yu, Jianshu Chen
International Conference on Machine Learning (ICML), 2024
[PDF]  [Code]


Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu#, Mladen Kolar, Tong Zhang
International Conference on Machine Learning (ICML), 2024
[PDF]


ROPO: Robust Preference Optimization for Large Language Models
Xize Liang*, Chao Chen*, Shuang Qiu*, Jie Wang#, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye
(Preprint)
[PDF]


Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards
Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
Annual Meeting of the Association for Computational Linguistics (ACL main)
[PDF]  [Code]


Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach
Shuang Qiu*, Boxiang Lyu*, Qinglin Meng*, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan
Minor Revision for Journal of Machine Learning Research (JMLR)
[PDF]


Posterior Sampling for Competitive RL: Function Approximation and Partial Observation
Shuang Qiu*, Ziyu Dai*, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
Advances in Neural Information Processing Systems (NeurIPS), 2023
[PDF]


Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
Sirui Zheng, Lingxiao Wang, Shuang Qiu, Zhuoran Yang, Csaba Szepesvari, Zhaoran Wang
International Conference on Learning Representations (ICLR), 2023
[PDF]


Gradient-Variation Bound for Online Convex Optimization with Constraints
Shuang Qiu, Xiaohan Wei, Mladen Kolar
AAAI Conference on Artificial Intelligence (AAAI), 2023
[PDF]


Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
Shuang Qiu, Lingxiao Wang, Chenjia Bai, Zhuoran Yang, Zhaoran Wang
International Conference on Machine Learning (ICML), 2022
[PDF]  [Code]


In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu,
Jieping Ye, Ce Zhang

International Conference on Management of Data (SIGMOD), 2022
[PDF]   [Extended Version]


On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
International Conference on Machine Learning (ICML), 2021
[PDF]


Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
International Conference on Machine Learning (ICML), 2021
[PDF]


Stylized Neural Painting
Zhengxia Zou, Tianyang Shi, Shuang Qiu, Yi Yuan, Zhenwei Shi
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF]  [Code]  [Project]
- Featured Applications
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- Media Coverage
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Automatic Image-to-Painting Translation Method Generates Vivid Paintings in Controllable Styles
Stylized Neural Painter: An Image-To-Painting Translation Method That Generates Vivid And Realistic Painting Artworks With Controllable Styles


Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss
Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang
Advances in Neural Information Processing Systems (NeurIPS), 2020
[PDF]


Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis
Shuang Qiu*, Xiaohan Wei*, Zhuoran Yang
International Conference on Machine Learning (ICML), 2020
[PDF]



Grant
  • 2024-2027, Hong Kong RGC General Research Fund (GRF). PI: Shuang Qiu, Co-I: Dong Xia

  • 2022-2025, Hong Kong RGC General Research Fund (GRF). PI: Kani Chen,   Co-I: Shuang Qiu


Academic Service

Conference
  • AAAI Conference on Artificial Intelligence (AAAI), 2023-2025. Senior PC Member

  • International Conference on Learning Representations (ICLR), 2023-2024. Reviewer

  • International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. Reviewer

  • Advances in Neural Information Processing Systems (NeurIPS), 2018-2024. Reviewer

  • International Conference on Machine Learning (ICML), 2021-2024. Reviewer

  • AAAI Conference on Artificial Intelligence (AAAI), 2021. Program Committee Member

  • International Joint Conferences on Artificial Intelligence (IJCAI), 2021-2024. Program Committee Member

  • SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020, 2023. Reviewer
Journal
  • Journal of Machine Learning Research (JMLR). Reviewer

  • IEEE Transactions on Information Theory (TIT). Reviewer

  • IEEE Transactions on Knowledge and Data Engineering (TKDE). Reviewer

  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Reviewer

  • Springer Machine Learning (ML). Reviewer

  • IEEE Transactions on Signal Processing (TSP). Reviewer