Physicist by education, I enjoy studying complex networks with tools from physics (statistical mechanics) and machine learning. I am a scientific programmer with real-world expertise in C/C++, Matlab and Python and the ability to learn very fast any new programming framework for data analysis. I like to tackle new problems that require mathematical modeling and advanced computational methods.

I’ve always been involved with scientific computation in general. In this last years, as a postdoctoral researcher, I’ve focused my studies in the complex interaction between the physics of machine learning, the complexity of large scale networked systems, and probability theory. All this theoretical stuff is always followed by numerical simulations, done with the latest Python libraries, and when necessary using C++ and their highly efficient compiled numerical libraries.

I am now working on computational models of brain fMRI activity exploiting the powerful theoretical machinery of complex networks.

This blog contains temporary results, vague ideas and notebooks that I collect during my daily work. For this reason, most of the content of this website is under construction, and mathematical contents are not complete, so please do not take it for granted.

My latest blog posts

• The Woodbury matrix identity
• Eigenvectors from eigenvalues a numpy implementation
• The link between machine learning and statistical physics
• Quantum statistical mechanics of complex networks in networkqit
• Hidden Markov Models

My PhD studies