My academic experience is a bit limited because I decided to pursue an industry job after I finished my doctoral studies, but still there are many projects, research and experiences that are worth highlighting here.

Open Source Projects


A direct-summation *N-*body integrator, which can be use in clusters/nodes with different flavours of parallelism (OpenMP, MPI or CUDA). It's based on the Hermite 4th order scheme, but can be extended to other integration methods.

Gadget Snapshot Reader

Simple python module to read Gadget snapshot (type 1).

Research Projects

Here you can find the ideas of the on-going projects which I'm involved.

Numerical modelling of Black holes binaries

Being the main topic of my PhD thesis, I'm currently involved in a few projects that study the dynamical evolution of black hole binaries in gas rich environments, but also considering the gas properties and how we can get some information related to circum-binary structures.

For this topic, I use Gadget, which is a cosmological N-body/Smooth Particle Hydrodynamics code.

Currently, two-papers are in progress related to this topic, which will be ready on 2017.

Collaborators: F. Goicovic, L. del Valle, A. Sesana, M. Dotti, P. Amaro-Seoane

Dynamical evolution of Globular clusters

During my Master, I decided to study astrophysical simulation of N-body systems which became the first project for my PhD. I developed GraviDy to be able to have a well structured code as base for future projects.

Collaborators: P. Amaro-Seoane

Medical Image Processing

Inmmunohistochemistry (IHC) analysis is a common practice to evaluate the evolution of different types of cancer. This process needs a biomarker to identify the cell membrane, like the Human Epidermal growth factor Receptor 2 (HER2). To study this images, one can use different texture features at a pixel-level, to be able to get the changes in the cells and classify them.

I'm currently helping Raquel Pezoa on this project, adapting a code that calculate the Haralick texture features of these images, to run in a large HPC clusters.



Computer Science