I'm an external collaborator of this project. I'm using the HPC software to simulate diffusion MRI in the Von Economo neurons published on NeuroMorpho database. The preliminary results were quite promising and submitted to the ISMRM 2018 conference.
I'm one of the main developers of the online course on high-performance finite element method. More than 4000 enrolled students were recorded on 20th Dec 2017 after 3 months and the number of involvements keeps growing.
I have been involving in the project as a doctoral researcher in computer science. My main tasks consist of (1) implementing a framework to simulate turbulence of a rotating vertical axis wind turbine whose CAD was given by the Uppsala University by using the adaptive stabilized finite element method developed within the group recent years, (2) validating numerical results against experimental data and (3) developing a slip velocity model for internal interfaces in a fluid-structure interaction framework. The work is in a good progress and I have delivered at least two papers.
I'm one of developers of the software with two main contributions: (1) computational diffusion MRI and (2) simulating turbulence of a vertical axis wind turbine. As far as I can see (1) is the first use of HPFEM in this field and it can become a powerful to uncover diffusion inside complicated biological tissues and at least two papers have been released related to the code development.
In this project, I worked as a postdoctoral researcher with a main focus on the ADER-DG method for the elastic wave equations. The method was implemented in Matlab using the nodal basis functions for 1D problem with some numerical verifications and comparisions against other methods. This work facilitated a reference for the implementation of higher dimensional problems on the structure code OOFE developed at MSSMAT, Ecole Central Paris. We have a submitted manuscript.
I proposed a finite elements method to solve the Bloch-Torrey equation applied to diffusion MRI. Some applications of the method for studying the dMRI signal inside multi-compartment models were considered. I also proposed an efficient one-dimensional model for accurately computing the dMRI signal inside neurites trees to test the validity of a semi-analytical expression for the dMRI signal arising from neurites trees. I ended the project with 7 peer-reviewed journals, one conference proceedings and one finite element code developed in the FEniCS.