Publications

Under Review

• W. Huo, C. Liu, K. Ding, K. H. Johansson, L. Shi, “Decentralized Optimization with Amplified Privacy via Efficient Communication”.
• C. Liu, N. Bastianello, W. Huo, Y. Shi, K. H. Johansson, “A Survey on Secure Decentralized Optimization and Learning”.
• X. Chen, W. Huo, K. Ding, S. Dey, L. Shi, “Differentially Private Distributed NE Seeking with Compressed Communication”.
• W. Huo, H. Yang, N. Yang, Z. Yang, J. Zhang, F. Nan, X. Chen, Y. Mao, S. Hu, P. Wang, X. Zheng, M. Zhao, L. Shi, “Recent Advances in Data-driven Intelligent Control for Wireless Communication: A Comprehensive Survey”.

6G for Agentic AI

• W. Tong, W. Huo, T. Lejkin, J. Penhoat, C. Peng, C. Pereira, F. Wang, S. Wu, L. Yang, Y. Shi, “A-Core: A Novel Framework of Agentic AI in the 6G Core Network”, WS06 IEEE ICC 2025 Workshop on Task-Oriented and Generative Communications for 6G.

Communication & Privacy in Distributed Systems

• W. Huo, C. Liu, K. Ding, K. H. Johansson, L. Shi, “Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy”, Automatica, 183, p. 112531, 2026.
• W. Huo, X. Chen, L. Huang, K. H. Johansson, L. Shi, “Differentially Private Dual Gradient Tracking for Distributed Resource Allocation over Directed Networks”, Automatica, 182, p. 112521, 2025.
• J. Zhang, W. Huo, X. Chen, D. E. Quevedo and L. Shi, “Remote State Estimation with Discounted Multi-Armed Bandits for Non-Stationary Channel Selection”, IEEE Control System Letters (L-CSS), vol. 9, pp. 787-792, 2025.
• X. Chen, W. Huo, Y. Wu, S. Dey, L. Shi, “An Efficient Distributed Nash Equilibrium Seeking with Compressed and Event-triggered Communication”, IEEE Transactions on Automatica Control, vol. 70, no. 3, pp. 2035-2042, 2025.
• X. Chen, W. Huo, K. Ding, S. Dey, L. Shi, “Communication-efficient and Differentially-private Distributed Nash Equilibrium Seeking with Linear Convergence”, IEEE Control System Letters (L-CSS), vol. 8, pp. 1787-1792, 2024.
• W. Huo, X. Chen, K. Ding, S. Dey, L. Shi, “Compression-based Privacy Preservation for Distributed Nash Equilibrium Seeking in Aggregative Games”, IEEE Control System Letters (L-CSS), vol. 8, pp. 886-891, 2024.
• W. Huo, K. F. E. Tsang, Y. Yan, K. H. Johansson, L. Shi, “Distributed Nash Equilibrium Seeking with Stochastic Event-triggered Mechanism”, Automatica, 162, p.111486, 2024.
• W. Huo, L. Huang, S. Dey, L. Shi, “Neural Network-based Distributed Generalized Nash Equilibrium Seeking for Uncertain Nonlinear Multi-agent Systems”, IEEE Transactions on Control of Network Systems.

Mixed Integer Programming

• M. Huang^*, L. Huang^*, Y. Zhong^*, H. Yang^*, X. Chen^*, W. Huo^*, J. Wang, F. Zhang, B. Bai, L. Shi, “MILP Acceleration: A Survey from Perspectives of Simplex Initialization and Learning-Based Branch and Bound”, Journal of the Operations Research Society of China, 1-55, 2023.
• L. Huang^*, X. Chen^*, W. Huo^*, J. Wang, F. Zhang, B. Bai, L. Shi, “Improving Primal Heuristics for Mixed Integer Programming Problems based on Problem Reduction: A Learning-based Approach”, in the 2022 17th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 181-186.

Complex Networks

• X. Tang, W. Huo, Y. Yuan, X. Li, L. Shi, H. Ding, J. Kurths, “Dynamical Network Size Estimation from Local Observations”, New Journal of Physics, vol. 22, no. 9, pp. 093031, 2020.

[* denotes equal contribution]