Stefano Veroni

Modelled COVID-19 pandemic with a system of 9 first order differential equations. The system was fitted to the values of the pandemic in Italy, UK, India, Brazil and Sweden, and numerically solved using MCMC statistical methods in python’s lmfit module. Estimates of the real number of infected people and predictions for the future were then made.

Team Based Problem Solving. January-March 2023. Fitting of B^0->K^*0 mu-mu+ decay. University project. 23 students involved. It is a copy of the orginal APerezFadon/TBPS.

Research Interfaces.

Produced animations of bouncing balls in a container, analysed and plotted the properties of the simulated gas and fitted and compared the ideal gas and van der Waal equations of state for such simulations.

Project on the mathematical complexity and scalefree behaviour of random Network's Growth with thourough statistical analysis

Python (version 3.8) source code (with mypy typing support) to generate and plot causal sets as well as use them in numerical calculations.

Improving Close Photons' Resolution in CERN's CMS HGCAL Next Detector with Machine Learning Techniques (XGBoost, Pytorch's NN)

Analysis of Oslo Model simulations in the context of self-organised criticality, to investigate its time evolution, the critical state main fetaures, and the avalanche sze distributions, both for boundary and bulk driven models.

A series of minimisation methods were developed to optimise the Likelihhod asssociated with the observation of muon neutrinos at T2K, hence fitting the oscillations' parameters (data was actually simulated by Imperial College London professors)

PYTHIA (C++) and DJANGOH (Fortran) were used to simulate DIS events and following parton showers, and to extract vauable parameters of the events.

A repository for my science communication works. No code.

Shown the significance of the Higgs’ boson signal by fitting the data and finding χ2 distributions and p-value to reject background only hypothesis.