PhD Student
ziqi.wang@fau.de
Room 03.311 | Friedrich-Alexander-Universität Erlangen-Nürnberg. FAU DCN-AvH Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship.
+49 9131 85-67124
Hi, I am Ziqi Wang, a PhD student at the Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship.
I received my bachelor’s degree from Northwestern Polytechnical University, Xi’an, China in 2018. Then I got my master’s degree in control science and engineering from Beihang University, Beijing, China in 2021.
My research interests include modeling and control of dynamical systems, motion planning, and machine learning.
Events
• CIN-PDE 2024 Poster: Fedadmm-insa: an Inexact and Self-adaptive Admm for Federated Learning (Yongcun Song, Ziqi Wang, Enrique Zuazua) | see poster. Conference on Control, Inversion and Numerics for PDEs (Oct. 7-10, 2024 at Fudan University, Shanghai)
• Mini-workshop “Analysis, Numerics and Control”. Geometric guidance strategies for terminal angle and time control problems (November 14, 2022)
• FAU DCN-AvH Jr. Seminar: Efficient federated learning via the alternating direction method of multipliers (April 25, 2024)
My posts on Math & Research
PINNs Introductory Code for the Heat Equation
Federated Learning: Protect your data and privacy
My posters
Fedadmm-insa: an Inexact and Self-adaptive Admm for Federated Learning
Publications
2025
- , , :
A Potential Game Perspective in Federated Learning
(2025)
DOI: 10.48550/arXiv.2411.11793
URL: https://arxiv.org/abs/2411.11793
BibTeX: Download - , , :
FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning
In: Neural Networks 181 (2025), Article No.: 106772
ISSN: 0893-6080
DOI: 10.1016/j.neunet.2024.106772
BibTeX: Download
