PhD Thesis Now Online

I’m happy to share that the pre-defense version of my PhD thesis is now publicly available on arXiv!

The thesis

Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures

explores how modern machine learning models can be deployed efficiently in high-energy physics environments, with a focus on maximizing throughput and minimizing energy consumption.

Here’s a peek at the table of contents:

You can:

• Read more about the project here: Project

• Read the ML intro chapter here: From Machine Learning to Graph Neural Networks and Quantization – An Introduction

• Read the HPC intro chapter here: From GPUs to FPGAs – An Introduction to High-Performance Computing

• Read the full thesis here: arXiv.2508.07423

• The PhD defense is scheduled for the 5th of September, 2025 and you can find the page of the defense (viva) here.

If you have any thoughts, questions, or feedback, feel free to reach out.