Publications

You can also find my publications on my Google Scholar profile.

Publications

Preprints / Under Review

1. Vidur Sinha, Muhammed Ustaomeroglu, Guannan Qu.
   Transformer-Based Scalable Multi-Agent Reinforcement Learning for Networked Systems with Long-Range Interactions.
   arXiv:2511.13103, 2025. [link]

2. Muhammed Ustaomeroglu, Guannan Qu.
   BLOCK-EM: Preventing Emergent Misalignment by Blocking Causal Features.
   arXiv:2602.00767, 2026. [link]

3. Ozan Baris Mulayim, Elias Pergantis, Levi D. Reyes Premer, Bingqing Chen, Guannan Qu, Kevin J. Kircher, Mario Bergés.
   Comparative Field Deployment of Reinforcement Learning and Model Predictive Control for Residential HVAC.
   Under review. [link]

4. Qinghua Ma, Reetam Sen Biswas, Denis Osipov, Guannan Qu, Soummya Kar, Shimiao Li.
   Multi-Period Sparse Optimization for Proactive Grid Blackout Diagnosis.
   arXiv:2510.14045, 2025. [link]

5. Shimiao Li, Guannan Qu, Bryan Hooi, Vyas Sekar, Soummya Kar, Larry Pileggi.
   Cyber-Resilient System Identification for Power Grid through Bayesian Integration.
   arXiv:2510.14043, 2025. [link]

6. Alex DeWeese, Guannan Qu.
   Thinking Beyond Visibility: A Near-Optimal Policy Framework for Locally Interdependent Multi-Agent MDPs.
   arXiv:2506.04215, 2025. [link]

7. John Z. Zhang, Taylor A. Howell, Zeji Yi, Chaoyi Pan, Guanya Shi, Guannan Qu, Tom Erez, Yuval Tassa, Zachary Manchester.
   Whole-Body Model-Predictive Control of Legged Robots with MuJoCo.
   Under review, 2025. [link]

8. Chaoyi Pan, Zeji Yi, John Zhang, Zachary Manchester, Guannan Qu, Guanya Shi.
   FS-MPC: Stabilizing Sampling-Based MPC with Adaptive Feedback Design.
   Under review, 2025.

Journal and Selected Conference Publications

1. Chaoyi Pan, Giri Anantharaman, Nai-Chieh Huang, Claire Jin, Daniel Pfrommer, Chenyang Yuan, Frank Permenter, Guannan Qu, Nicholas Boffi, Guanya Shi, Max Simchowitz.
   Much Ado About Noising: Dispelling the Myths of Generative Robotic Control.
   ICLR, 2026. [link]

2. Xingyu Xu, Ziyi Zhang, Yorie Nakahira, Guannan Qu, Yuejie Chi.
   Polynomial Convergence of Riemannian Diffusion Models.
   ICLR, 2026. [link]

3. Muhammed Ustaomeroglu, Baris Askin, Gauri Joshi, Carlee Joe-Wong, Guannan Qu.
   Language Model Planning from an Information Theoretic Perspective.
   ICLR, 2026. [link]

4. Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, Gauri Joshi.
   Natural Policy Gradient for Average Reward Non-Stationary RL.
   Transactions on Machine Learning Research (TMLR), 2025. [link]

5. Ziyi Zhang, Yorie Nakahira, Guannan Qu.
   Stabilizing Linear Systems under Partial Observability: Sample Complexity and Fundamental Limits.
   NeurIPS, 2025. [link]

6. Emile Anand, Ishani Karmarkar, Guannan Qu.
   Mean-field Sampling for Cooperative Multi-Agent Reinforcement Learning.
   NeurIPS, 2025 (Spotlight). [link]

7. Muhammed Ustaomeroglu, Guannan Qu.
   A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization.
   ICML, 2025. [link]

8. Ziyi Zhang, Guannan Qu, Yorie Nakahira.
   Fast Bandit-based Policy Adaptation in Diverse Environments.
   ACC, 2025. [link]

9. Tairan He, Jiawei Gao, Wenli Xiao, Yuanhang Zhang, Zi Wang, Jiashun Wang, Zhengyi Luo, Guanqi He, Nikhil Sobanbab, Chaoyi Pan, Zeji Yi, Guannan Qu, Kris Kitani, Jessica Hodgins, Linxi Fan, Yuke Zhu, Changliu Liu, Guanya Shi.
   ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills.
   RSS, 2025. [link]

10. Ziyi Zhang, Yorie Nakahira, Guannan Qu.
    Learning to Stabilize LTI Systems on a Single Trajectory under Stochastic Noise.
    UAI, 2025. [link]

11. Haoru Xue, Chaoyi Pan, Zeji Yi, Guannan Qu, Guanya Shi.
    Full-order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing.
    ICRA, 2025 (Best Conference Paper Award Finalist). [link]

12. Ziyi Zhang, Yorie Nakahira, Guannan Qu.
    Predictive Control and Regret Analysis of Non-Stationary MDP with Look-ahead Information.
    TMLR, 2025. [link]

13. Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu.
    Model-based Diffusion for Trajectory Optimization.
    NeurIPS, 2024. [link]

14. Alex DeWeese, Guannan Qu.
    Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies.
    ICML, 2024. [link]

15. Neharika Jali, Guannan Qu, Weina Wang, Gauri Joshi.
    Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems.
    AISTATS, 2024. [link]

16. Eric Xu, Guannan Qu.
    Stability and Regret Bounds on Distributed Truncated Predictive Control for Networked Dynamical Systems.
    ACC, 2024. [link]

17. Jie Feng, Yuanyuan Shi, Guannan Qu, Steven H. Low, Anima Anandkumar, Adam Wierman.
    Stability Constrained Reinforcement Learning for Decentralized Real-Time Voltage Control.
    IEEE Transactions on Control of Network Systems, 2023. [link]

18. Sahin Lale, Yuanyuan Shi, Guannan Qu, Kamyar Azizzadenesheli, Adam Wierman, Anima Anandkumar.
    KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems.
    CDC, 2023. [link]

19. Eric Xu, Guannan Qu.
    Natural Policy Gradient Preserves Spatial Decay Properties for Control of Networked Dynamical Systems.
    CDC, 2023. [link]

20. Sungho Shin, Yiheng Lin, Guannan Qu, Adam Wierman, Mihai Anitescu.
    Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems.
    SIAM Journal on Control and Optimization, 2023. [link]

21. Tongxin Li, Ruixiao Yang, Guannan Qu, Yiheng Lin, Adam Wierman, Steven Low.
    Certifying Black-Box Policies with Stability for Nonlinear Control.
    IEEE Open Journal of Control Systems, 2023. [link]

22. Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman.
    *Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning.
    ACM SIGMETRICS, 2023. (Equal contribution) [link]

23. Yang Hu, Adam Wierman, Guannan Qu.
    On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory.
    NeurIPS, 2022. [link]

24. Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman.
    Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity.
    NeurIPS, 2022. [link]

25. Yuanyuan Shi, Guannan Qu, Steven Low, Anima Anandkumar, Adam Wierman.
    Stability Constrained Reinforcement Learning for Real-Time Voltage Control.
    ACC, 2022. (Equal contribution) [link]

26. Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven Low.
    Robustness and Consistency in Linear Quadratic Control with Predictions.
    ACM SIGMETRICS, 2022. [link]

27. Yiheng Lin, Judy Gan, Guannan Qu, Yash Kanoria, Adam Wierman.
    Decentralized Online Convex Optimization in Networked Systems.
    ICML, 2022. [link]

28. Xin Chen, Guannan Qu, Yujie Tang, Steven Low, Na Li.
    Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges.
    IEEE Transactions on Smart Grid, 2022. [link]

29. Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven Low.
    Robustness and Consistency in Linear Quadratic Control with Predictions.
    Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2022. [link]

30. Guannan Qu, Adam Wierman, Na Li.
    Scalable Reinforcement Learning of Multi-Agent Networked Systems.
    Operations Research, 2022. [link]

31. Yiheng Lin, Yang Hu, Haoyuan Sun, Guanya Shi, Guannan Qu, Adam Wierman.
    *Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems.
    NeurIPS, 2021 (Spotlight). (Equal contribution) [link]

32. Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman.
    Multi-agent Reinforcement Learning in Stochastic Networked Systems.
    NeurIPS, 2021. [link]

33. Niloy Patari, Anurag K. Srivastava, Guannan Qu, Na Li.
    Distributed Voltage Control for Three-Phase Unbalanced Distribution Systems with DERs and Practical Constraints.
    IEEE Transactions on Industry Applications, 2021. [link]

34. Yingying Li, Guannan Qu, Na Li.
    Online Optimization with Predictions and Switching Costs: Fast Algorithms and the Fundamental Limit.
    IEEE Transactions on Automatic Control, 2021. [link]

35. Guannan Qu, Chenkai Yu, Steven Low, Adam Wierman.
    Exploiting Linear Models for Model-Free Nonlinear Control: A Provably Convergent Policy Gradient Approach.
    CDC, 2021. [link]

36. Guannan Qu, Yiheng Lin, Adam Wierman, Na Li.
    Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward.
    NeurIPS, 2020. [link]

37. Yujie Tang, Guannan Qu, Na Li.
    Semi-Global Exponential Stability of Primal-Dual Gradient Dynamics for Constrained Convex Optimization.
    Systems & Control Letters, 2020. [link]

38. Sindri Magnússon, Guannan Qu, Na Li.
    Distributed Optimal Voltage Control with Asynchronous and Delayed Communication.
    IEEE Transactions on Smart Grid, 2020. [link]

39. Guannan Qu, Na Li.
    Accelerated Distributed Nesterov Gradient Descent.
    IEEE Transactions on Automatic Control, 2020. [link]

40. Guannan Qu, Na Li.
    Optimal Distributed Feedback Voltage Control under Limited Reactive Power.
    IEEE Transactions on Power Systems, 2020. [link]

41. Sindri Magnússon, Guannan Qu, Carlo Fischione, Na Li.
    Voltage Control Using Limited Communication.
    IEEE Transactions on Control of Network Systems, 2019. [link]

42. Guannan Qu, Na Li.
    Exploiting Fast Decaying and Locality in Multi-Agent MDP with Tree Dependence Structure.
    CDC, 2019. [link]

43. Guannan Qu, David Brown, Na Li.
    Distributed Greedy Algorithm for Multi-Agent Task Assignment Problem with Submodular Utility Functions.
    Automatica, 2019. [link]

44. Guannan Qu, Na Li.
    On the Exponential Stability of Primal-Dual Gradient Dynamics.
    IEEE Control Systems Letters, 2019. [link]

45. Xiaoqi Tan, Guannan Qu, Bo Sun, Na Li, Danny H.K. Tsang.
    Optimal Scheduling of Battery Charging Station Serving Electric Vehicles Based on Battery Swapping.
    IEEE Transactions on Smart Grid, 2019. [link]

46. Guannan Qu, Na Li.
    Harnessing Smoothness to Accelerate Distributed Optimization.
    IEEE Transactions on Control of Network Systems, 2018. [link]

47. Yingying Li, Guannan Qu, Na Li.
    Using Predictions in Online Optimization with Switching Costs: Algorithms and Fundamental Limits.
    ACC, 2018. [link]

48. Guannan Qu, Na Li.
    Accelerated Distributed Nesterov Gradient Descent for Smooth and Convex Functions.
    CDC, 2017. [link]

49. Guannan Qu, Na Li.
    Harnessing Smoothness to Accelerate Distributed Optimization.
    CDC, 2016. [link]

Other Conference and Workshop Publications

1. Zeji Yi, Chaoyi Pan, Guanqi He, Guannan Qu, Guanya Shi.
   CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design.
   L4DC, 2024. [link]

2. Junxuan Shen, Adam Wierman, Guannan Qu.
   Combining Model-based Controller and ML Advice via Convex Reparameterization.
   L4DC, 2024. [link]

3. Songyuan Zhang, Yumeng Xiu, Guannan Qu, Chuchu Fan.
   Compositional Neural Certificates for Networked Dynamical Systems.
   L4DC, 2023 (Oral Presentation). [link]

4. Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman.
   *Stable Online Control of Linear Time-Varying Systems.
   L4DC, 2021. (Equal contribution) [link]

5. Andreas Venzke, Guannan Qu, Steven Low, Spyros Chatzivasileiadis.
   Learning Optimal Power Flow: Worst-Case Guarantees for Neural Networks.
   SmartGridComm, 2020 (Best Student Paper Award). [link]

6. Guannan Qu, Adam Wierman, Na Li.
   Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems.
   L4DC, 2020 (Oral Presentation, Top 10%). [link]

7. Guannan Qu, Adam Wierman.
   Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-learning.
   COLT, 2020. [link]

8. Niloy Patari, Anurag Srivastava, Guannan Qu, Na Li.
   Distributed Optimal Voltage Control for Three Phase Unbalanced Distribution Systems with DERs.
   IEEE Industry Applications Annual Meeting, 2020. [link]

9. Yingying Li, Aoxiao Zhong, Guannan Qu, Na Li.
   Online Markov Decision Processes with Time-Varying Transition Probabilities and Rewards.
   ICML Real-World Sequential Decision Making Workshop, 2019.

10. Guannan Qu, Na Li.
    An Optimal and Distributed Feedback Voltage Control under Limited Reactive Power.
    Power Systems Computation Conference, 2018. [link]

11. Guannan Qu, Na Li.
    Accelerated Distributed Nesterov Gradient Descent for Smooth and Strongly Convex Functions.
    Allerton Conference, 2016. [link]

12. Guannan Qu, David Brown, Na Li.
    Distributed Greedy Algorithm for Satellite Assignment Problem with Submodular Utility Function.
    IFAC Workshop on Estimation and Control of Networked Systems, 2015. [link]

13. Na Li, Guannan Qu, Munther Dahleh.
    Real-time Decentralized Voltage Control in Distribution Networks.
    Allerton Conference, 2014. [link]

Technical Reports

1. Han Xu, Jialin Zheng, Guannan Qu.
   A Scalable Network-Aware Multi-Agent Reinforcement Learning Framework for Decentralized Inverter-based Voltage Control.
   arXiv:2312.04371, 2023. [link]

2. Guannan Qu, Na Li, Munther Dahleh.
   Real-time Decentralized and Robust Voltage Control in Distribution Networks.
   arXiv:1606.08101, 2016. [link]