I have completed my PhD in Applied Mathematics at King's College London.

I am part a global effort of Delta Leap to predict which patients will respond to chemotherapy and why. As part of the Schumacher group, I help developing the computational methods used to analyse the data generated by the experimental teams from patients with Triple Negative Breast Cancer. In the analysis, I contribute through different ML algorithms for visualisation, clustering and predictions.

Furthermore, I am interested in modelling of gene regulatory networks, I ask questions like "What are the key features that makes gene regulation so precise and effective?" This investigation requires a multidisciplinary approach and I develop mathematical modelling. My research interests include network theory and statistical mechanics.

Openess and transparency in research are very important, the code to reproduce my research papers is here!

I had some fun coding as well! 🎁 Have you ever wondered how to recycle gifts you don't like to your friends without being caught? Well, here there is an implementation using genetic algorithms.

I code mainly in Python, but here you can find also code in Matlab and CUDA C.

Here is the link to my Google Scholar account and get updated with latest news from the Disordered Systems Group website. :dancers: I’m looking to collaborate on the integration of models with data. If you have any comments, ideas, or just want to approach me, please get in touch with me via email 📫 gtorrisi@ed.ac.uk