PhD Thesis: Cyber-attack resilient distributed state estimation for sensor networks: learning-based and moving horizon estimation
Abstract: The thesis focuses on the problem of distributed state estimation over sensor networks. It studies the method of distributed moving horizon estimation, with the objective to improve robustness of such a methods from communications vulnerabilities and errors.
Duration: January 2026 – December 2028
Funding: ONERA / AID
Supervision team: Cristina Stoica (HDR, L2S CentraleSupélec) – Sylvain Bertrand (DTIS – ONERA)
