About

Oxford Theoretical Physics graduate, currently Marie Curie PhD Fellow at Sorbonne/CERN, specializing in artificial intelligence for High Energy Physics. Strong background in mathematical modeling, with expertise in high-frequency data analysis, real-time ML on GPUs and FPGAs, and high-performance computing with C++ and Julia. Experience in time series anomaly detection with ML, deploying and backtesting quantitative trading strategies, and stochastic processes. Transitioning expertise to financial markets, alpha research, volatility modeling, and market microstructure research.

Contact

You can contact me on LinkedIn or using the contact form.

Education

• PhD in High-Energy Physics
  Sorbonne University and CERN, France
  Oct 2022 – Sep 2025
  • Thesis: “Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures”
• MSc in Applied Mechanics
  National Technical University of Athens (NTUA), Greece
  Oct 2020 - Jul 2022
  • Thesis: “Quantum Chaos in Many-Body Systems Without a Classical Analogue”
• MMathPhys in Mathematical and Theoretical Physics
  University of Oxford, United Kingdom
  Oct 2015 – Jul 2019
  • First Class and Distinction
  • Thesis: “On the Yang–Mills Existence and Mass Gap Problem”