This project is conducted by a WASP PhD student (Thibault Marette) and a WASP professor (Aris Gionis) in Theoretical Computer Science (TCS) at KTH. It aims at complementing paper submissions to the ICLR 2026 conference, as well as corresponding future work and extensions. The paper presents a novel theoretical algorithm for consistent k-center clustering for evolving data, requiring experimental validation. We aim to run thorough experiments on large real-world datasets, to compare our algorithm with the state-of-the-art, on various metrics.