Jean Nicolas Brunet

R&D Software Engineer, Ph.D.
photo of Jean Nicolas Brunet, Ph.D. student

Jean Nicolas Brunet

R&D Software Engineer, Ph.D.


Member of the Inria MIMESIS research staff. Research activities focus on computer assisted medical training, planning and guidance. My responsibilities involve the development as well as the evolution of the real-time computation and data-driven simulation models available within the open-source SOFA framework. Patient-specific applications vary from augmented reality liver surgery assistance to surgical training.

I completed my doctoral thesis (Ph.D) in computer science in Strasbourg, France, and my master thesis (M.Sc.A) in computer science engineering in Montreal, Canada. So far, my main contributions can be found on real-time simulation of linear elastic and hyperelastic objects using meshless and immersed boundary methods.

I am also the main contributor of the caribou project, bringing non-linear finite elements and hyperelastic materials to SOFA.

Doctoral thesis

Selected as part of 16 PhD students for the High Perfomance Soft Tissue Navigation (HiPerNav) European project funded by a Marie Skłodowska-Curie grant. My research focused on the development of new numerical methods for the simulation of soft tissue deformations in the context of augmented reality surgery assistance and was conducted under the supervision of Stéphane Cotin, Research Director at Inria and leader of the MIMESIS team. Several research initiatives have been put in place to identify new methods for solving deformable dynamics that are not only accurate and fast, but also robust enough to manage unpredictable and often non-physical inputs. The first part of my thesis focused on the so-called meshless or element-free methods. The second part of the thesis was dedicated to the traditional methods of discretization with isoparametric elements. However, unlike traditional finite element methods, the concept of fictitious domains was investigated.

Master thesis

Joined the Inria MIMESIS team as a research internship. Main responsibilities included the analysis of meshless methods for real-time surgical simulation applications using the well-known SOFA Framework. Recipient of a Mitacs Globalink fellowship.




Exploring new numerical methods for the simulation of soft tissue deformations in surgery assistance
Jean-Nicolas Brunet
Thesis, Université de Strasbourg, 2020.
Use of stereo-laparoscopic liver surface reconstruction to compensate for pneumoperitoneum deformation through biomechanical modeling.
Andrea Teatini, Jean-Nicolas Brunet, Sergei Nikolaev, Bjørn Edwin, Stéphane Cotin, Ole Jakob Elle
VPH2020, Virtual Physiological Human, Paris, 2020.
Data-driven simulation for augmented surgery.
Andrea Mendizabal, Eleonora Tagliabue, Tristan Hoellinger, Jean-Nicolas Brunet, Sergei Nikolaev, Stéphane Cotin
Developments and Novel Approaches in Biomechanics and Metamaterials. Springer, Cham, 2020. 71-96.
Physics-based deep neural network for real-time lesion tracking in ultrasound-guided breast biopsy.
Andrea Mendizabal, Eleonora Tagliabue, Jean-Nicolas Brunet, Diego Dall’Alba, Paolo Fiorini, Stéphane Cotin
Computational Biomechanics for Medicine. Springer, Cham, 2019.
Physics-based deep neural network for augmented reality during liver surgery.
Jean-Nicolas Brunet, Andrea Mendizabal, Antoine Petit, Nicolas Golse, Eric Vibert, Stéphane Cotin
International Conference on Medical image computing and computer-assisted intervention. Springer, Cham, 2019.
Corotated meshless implicit dynamics for deformable bodies.
Jean-Nicolas Brunet, Vincent Magnoux, Benoît Ozell, Stéphane Cotin
WSCG 2019-27th International Conference on Computer Graphics, Visualization and Computer Vision. Západočeská univerzita, 2019.
Analyse des méthodes par éléments finis et méthodes sans maillage pour la déformation de corps mous en simulation chirurgicale.
Jean-Nicolas Brunet
Dissertation, École Polytechnique de Montréal, 2017.