Shuang Qiu I am an Assistant Professor in the Department of Systems Engineering and Department of Computer Science (secondary) at City University of Hong Kong since 2025. Prior to CityU, I did research in the Department of Mathematics at the Hong Kong University of Science and Technology as a research assistant professor working with Prof. Tong Zhang (张潼) and in the Booth School of Business at the University of Chicago as a postdoc researcher  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 advised by Prof. Jieping Ye (叶杰平).

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

Openings

I am actively seeking self-motivated students with strong mathematical or programming skills for the following positions:
  • Postdoc & Research Assistant
    • Multiple Postdoc and long-term / short-term RA positions available now

  • Ph.D. Students (Fall 2026)
    • Exceptionally qualified Ph.D. applicants will be encouraged to apply for the Hong Kong PhD Fellowship Scheme (HKPFS).

    🎓We offer a special PhD application track for applicants with a bachelor’s degree from C9 League, UCAS, and QS/THE Top 20 universities, featuring an expedited offer process and a much higher scholarship. Welcome eligible applicants to get in touch with me as soon as possible!
    C9 League: THU, PKU, SJTU, FDU, ZJU, NJU, USTC, XJTU, HIT

    🎓We offer a joint PhD program for Ph.D. students from FDU, ZJU, NJU, USTC, XJTU, and HIT. Welcome eligible applicants to get in touch with me as soon as possible!


If you have a background in or are passionate about both applied and theoretical aspects of the following topics:
  • Agentic AI
  • (Multimodal) Large Language Model Reasoning
  • Embodied AI
  • Reinforcement Learning
please do not hesitate to contact me (shuanqiu [AT] cityu [DOT] edu [DOT] hk) with your CV and transcript.


News

09/2025 📃 We release our world model work LatticeWorld for building an industry-grade 3D world with multimodal LLMs. Check out this demo!

09/2025 🎓We offer a special PhD application track for applicants with a bachelor’s degree from C9 League, UCAS, and QS/THE Top 20 universities, featuring an expedited offer process and a much higher scholarship. Welcome eligible applicants to get in touch with me as soon as possible! 📧 (Limited Openings)

09/2025 🎓We offer a joint PhD program for Ph.D. students from FDU, ZJU, NJU, USTC, XJTU, and HIT. Welcome eligible applicants to get in touch with me as soon as possible! 📧

09/2025 🎉 I will be serving as Area Chair of ICLR 2026

08/2025 🎉 Great honor to receive research funding from renowned VC MiraclePlus (奇绩创坛) to support our research on Agentic AI and LLMs.

07/2025 🎉 I will be serving as Senior PC of AAAI 2026


Research Interest
My recent research interests generally focus on sequential decision-making problems and their applications in Agentic AI, Large Language Models, and Embodied AI. Specifically, my research interest include both applications and theories of reinforcement learning, game theory, large language models, robotics, AI agents, diffusion models, and nonconvex optimization.

Selected Recent Publication [Full List]
[World Model] LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation
Yinglin Duan*, Zhengxia Zou*, Tongwei Gu*, Wei Jia, Zhan Zhao, Luyi Xu, Xinzhu Liu, Hao Jiang, Kang Chen#, Shuang Qiu#
(Preprint)
[PDF]  [Demo Video]



[World Model] Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective
Yang Zhang, Xinran Li, Jianing Ye, Shuang Qiu, Delin Qu, Chongjie Zhang, Xiu Li, Chenjia Bai
Advances in Neural Information Processing Systems (NeurIPS), 2025
[PDF]


[LLM Reasoning] Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models
Yiran Guo, Lijie Xu, Jie Liu, Dan Ye, Shuang Qiu
Advances in Neural Information Processing Systems (NeurIPS), 2025
[PDF]  [Code]  [Chinese Media Coverage | Highlighted as Lead Story]


[Multi-Objective RL] Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning
Shuang Qiu, Dake Zhang, Rui Yang, Boxiang Lyu, Tong Zhang
(Preprint)
[PDF]


[Robust LLM] 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
International Conference on Machine Learning (ICML), 2025
[PDF]


[RL] On the Value of Myopic Behavior in Policy Reuse
Chenjia Bai, Kang Xu, Shuang Qiu, Haoran He, Bin Zhao, Zhen Wang, Wei Li, Xuelong Li
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
[PDF]


[LLM] Online Preference Alignment for Language Models via Count-based Exploration
Chenjia Bai, Yang Zhang, Shuang Qiu, Qiaosheng Zhang, Kang Xu, Xuelong Li
International Conference on Learning Representations (ICLR Spotlight), 2025
[PDF]  [Code]  [Chinese Media Coverage]


[Robust RL] Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
Jiawei Xu, Rui Yang, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han
International Conference on Learning Representations (ICLR), 2025
[PDF]


[RL & Diffusion] Forward KL Regularized Preference Optimization for Aligning Diffusion Policies
Zhao Shan, Chenyou Fan, Shuang Qiu, Jiyuan Shi, Chenjia Bai
AAAI Conference on Artificial Intelligence (AAAI), 2025
[PDF]


[RL & Econ] Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach
Shuang Qiu*, Boxiang Lyu*, Qinglin Meng*, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan
Journal of Machine Learning Research (JMLR), 2024
[PDF]


[Multi-Objective LLM] 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]


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


[Multi-Objective LLM] 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), 2024
[PDF]  [Code]


[RL & Game] 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]


[RL] 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]


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


[RL & Game] 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]


[Optimization] 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]


[RL & Game] 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]


[RL & Game] 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]


[RL] On Finite-Time Convergence of Actor-Critic Algorithm
Shuang Qiu , Zhuoran Yang, Jieping Ye, Zhaoran Wang
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2021
[PDF]


[Image Rendering] 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
REMINI, an AI photo enhancer with 50M+ users worldwide
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RunwayML, a web-based video editing software
- Media Coverage
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有 了这支矢量神 经风 格画 笔，无需GAN也可生成精美绘画
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


[Graph Embedding] Pine: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
[PDF]


 [Safe RL] 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]
[Compressed Sensing] 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
  • International Conference on Learning Representations (ICLR), 2026. Area Chair

  • AAAI Conference on Artificial Intelligence (AAAI), 2023-2026. Senior PC Member

  • Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2025. Area Chair

  • The 4th Innovation Forum on Intelligence Computing @ Zhejiang Lab, 2024. Session Chair

  • International Conference on Learning Representations (ICLR), 2023-2025. Reviewer

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

  • Advances in Neural Information Processing Systems (NeurIPS), 2018-2026. Reviewer

  • International Conference on Machine Learning (ICML), 2021-2025. 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 the American Statistical Association (JASA). Reviewer

  • 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