CV

Contact Information

Name Vincenzo Di Florio
Position Post-doctoral Research Fellow
Institution MOX – Modeling and Scientific Computing, Politecnico di Milano
Email vincenzo.diflorio@polimi.it

Professional Summary

Physicist and computational scientist working at the intersection of applied mathematics, numerical methods, and machine learning. My research focuses on biomolecular electrostatics — developing PDE solvers, Physics-Informed Neural Networks (PINNs), and Physics-Guided Neural Networks (PGNNs) — alongside non-equilibrium statistical dynamics.

Education

  • 2021 - 2025

    Turin, Italy

    PhD in Pure and Applied Mathematics
    Politecnico di Torino & Istituto Italiano di Tecnologia
    • Research topics: Biomolecular modeling, continuum electrostatics, software development for biological systems
    • Thesis: Mathematical, Algorithmic and Numerical Solutions to Enhance Electrostatic Calculations for Biomolecules in Electrolytic Solutions
    • Supervisors: Dr. Walter Rocchia, Prof. Lamberto Rondoni
  • 2019 - 2021

    Turin, Italy

    Master's in Physics of Complex Systems
    Università degli Studi di Torino
    • GPA: 110/110 cum Laude
    • Related coursework: Statistical Physics and Mathematical Modelling
    • Thesis: State equations and order fluctuations in 1D and 3D
    • Advisor: Prof. Lamberto Rondoni
  • 2016 - 2019

    Trieste, Italy

    Bachelor in Physics
    Università degli Studi di Trieste
    • GPA: 110/110 cum Laude
    • Related coursework: Major in Physics, minor in Numerical Analysis and Dynamical Systems
    • Thesis: Quantum dots for quantum computation
    • Advisor: Prof. Angelo Bassi

Experience

  • 2025 - Present

    Milan, Italy

    Research Fellow
    MOX – Modeling and Scientific Computing, Politecnico di Milano
    • Developing hybrid physics-based models for biomolecular electrostatics
    • Investigating non-equilibrium statistical dynamics and low-dimensional systems
  • 2024

    New York, USA

    Internship
    City College of New York (CUNY)
    • Integrated NextGenPB as an electrostatic solver within the MCCE workflow
    • Developed benchmark applications for pK_a calculations
  • 2018

    Trieste, Italy

    Internship
    SISSA
    • Sparse identification of dynamical systems from data

Teaching

  • 2024

    Turin, Italy

    Tutor – Methods for Environmental Engineering
    Politecnico di Torino
  • 2022 - 2023

    Turin, Italy

    Teaching Assistant – Calculus 1
    Politecnico di Torino
  • 2021

    Turin, Italy

    Teaching Assistant – Physics 1
    Università degli Studi di Torino

Publications

Skills

Programming Languages Python, C++, OCTAVE/MATLAB, Bash, Fortran
Scientific Computing Numerical PDEs, Finite Element Methods, Poisson-Boltzmann solvers, PINNs, PGNNs
Tools & Frameworks Git, Docker, NumPy, SciPy, Matplotlib, LaTeX
Operating Systems Linux, macOS

Languages

Italian : Native speaker
English : Fluent

Open Source Projects

  • NextGenPB
    • Electrostatic solver for biomolecules based on the Poisson-Boltzmann Equation with analytical refinement and high-resolution accuracy