Jian-Hua WANG

I am a postdoctoral researcher at the Cedric Laboratory (CNAM) and the LEME Laboratory at Paris Nanterre University. I collaborate with Arnaud Breloy as part of the ANR project MASSILIA, which aims to develop new methodological tools for graph learning and its applications, leveraging the spectral decomposition of Laplacian and adjacency matrices. My work focuses in particular on graph learning and optimization.

During my PhD, under the supervision of Pascal Larzabal, Mohammed Nabil El Korso and Lucien Bacharach within the Signal Processing Group (MOSS) at the SATIE (Laboratoire des systèmes et applications des technologies de l’information et de l’énergie) laboratory of Paris-Saclay University, I contributed to the field of radio-interferometry. My research focuses on signal processing methodologies for designing efficient algorithms that reduce computational load while preserving image reconstruction quality, particularly in the presence of interference in next-generation radio interferometric imaging systems. Inspired by the operational flexibility of the Square Kilometre Array (SKA), we explored the idea of deliberately switching between several specialized subarrays to enhance observational performance. Implementing this antenna-switching strategy required the formulation and resolution of optimization problems arising in maximum likelihood estimation using algorithms such as Expectation–Maximization (EM), as well as the development of robust statistical models based on compound Gaussian distributions to effectively handle radio-frequency interference (RFI).

I earned my B.S. degree in Mathematics and Applied Mathematics from Beihang University, Beijing, China, in 2018. In 2021, I completed my Master’s degree under the supervision of HAN Liang, majoring in Automation and Reinforcement Learning. My research focused on the cooperative control of multi-agent systems, formation tracking for multi-UAV systems, and applications of reinforcement learning. For further details on my work from this period, please visit my Master’s research homepage..