Curriculum vitae - July 12 2025
Download PDFI am a physicist with 5+ years of experience in machine learning research and development. Currently finishing my PhD in physics, I am working on quantum computing, machine learning and their intersection. I am also consulting companies, developing custom models or optimizing existing ones.
PhD in Physics, Sapienza University of Rome, Italy
Topics: physics-inspired algorithms, quantum computing, machine learning and quantum machine learning
Group: Fisica AI&QC group
Supervisors: Stefano Giagu, Fabio Sciarrino
PhD in Computer Engineering, Technical University of Munich, Germany
Topics: classical-quantum compound channels and algorithms for the automatic generation of quantum graph states
Group: Theoretical quantum system design group
Supervisors: Janis Nötzel, Jonathan Finley
M.Sc. in Physics, Sapienza University of Rome, Italy
Thesis: “Deep learning for the parameter estimation of tight-binding Hamiltonians”
Supervisors: Stefano Giagu, Stefan Bauer
Grade: 109/110
B.Sc. in Physics, Sapienza University of Rome, Italy
Thesis: “Hidden Markov model”
Supervisor : Luciano Pietronero
Grade: 110/110 with honors
ML Consulting, Individual clients, Italy
Topics: training NNs to solve PDEs in finance - implementation of diffusion models - training NNs on incomplete datasets - invoice reconciliation using an online LLM
ML Consulting, Grid +, Rome, Italy
Topic: Automatic analysis of legal documents and anomaly detection
Tutoring, Individual clients, Italy
Topics: mathematics, physics and computer science for university students
ML Consulting, Hypercube SA, Lugano, Switzerland
Topic: application of ML techniques to the detection of time series anomalies
ML Consulting, Primis Group SRL, Milan, Italy
Tasks: determine best ML solutions tailored to LiDAR and satellite data, design of an anomaly detection algorithm for LiDAR data (contract of Rete Ferroviaria Italiana SPA)
Tutoring, Technical University of Munich, Germany
Task: assisting students of the "Quantum networking" class
Research Internship, Max Planck Institute for Intelligent Systems, Tübingen, Germany
Topics: Deep learning for estimating tight-binding Hamiltonians, quantum machine learning models and their connection with kernel methods
Research grant, Sapienza University of Rome, Italy
"Development of quantum machine learning algorithms" - 1000 €
Excellence program for honor students, Sapienza University of Rome, Italy
Quantum Computing @ INFN, Padova, Italy, Talk
"Quantum diffusion models for quantum data learning"
38° cycle PhD seminar, Rome, Italy, Talk
"Quantum machine learning and physics-informed deep learning algorithms"
EuCAIFCon2024, Amsterdam, Netherlands, Flash Talk
"Quantum diffusion models"
QAIXIAQ2023 Workshop, Rome, Italy, Talk
"Quantum diffusion models using parameterized quantum circuits for data denoising"
ISIT, 2021 IEEE International Symposium on Information Theory, Talk
"Compound channel capacities under energy constraints and application"
