I am a Ph.D. student at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), where I work at the Chair for Dynamics, Control, Machine Learning and Numerics–Alexander von Humboldt Professorship, under the supervision of Prof. Enrique Zuazua.

My research focuses on distributed optimization, federated learning, and dynamical systems. I am particularly interested in federated learning from a multi-level perspective, including client-level drift control and local optimization, server-level fair and robust aggregation, system-level game-theoretic incentives, and privacy risks in distributed training.

Selected Publications

^* Alphabetical authorship according to mathematical tradition, corresponding author.

• Kang Liu, Ziqi Wang^*, and Enrique Zuazua, “Nonlinear Equilibrium Transitions in a Potential Game Model for Federated Learning,” Physica D: Nonlinear Phenomena, 2026.
• Yongcun Song, Ziqi Wang^*, and Enrique Zuazua, “Approximate and Weighted Data Reconstruction Attack in Federated Learning,” IEEE Transactions on Big Data, 2026.
• Yongcun Song, Ziqi Wang^*, and Enrique Zuazua, “FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning,” Neural Networks, 2025.

See the research page for the full list.