I defended my Ph.D. thesis at the University of Rennes 1 in November, 2020. My primary research interests lie at the intersection of deformable image registration and biomechanical modeling. My goal is to leverage the synergy between these two domains to develop assistance mechanisms for various clinical applications. During my doctoral research, I investigated the potential of a hybrid framework based on deformable image registration of intraoperative cone-beam CT (CBCT) images and a poroelastic biomechanical model for assisting minimally invasive lung surgery. I pursued this research as a post-doctoral fellow at the University Grenoble-Alpes, focusing in the application of porous mechanics to modeling macroscopic air-tissue exchanges in the lung, particularly for modeling pneumothroax (lung deflation) during VATS. Since 2023, I joined the Inria MIMESIS team as a postoctoral fellow. My current goal is to enforce the physical plausibility of displacement field estimations in deformable image registration contexts, both in the classical and machine learning settings.