Welcome!

Thank you for visiting my personal website! Here you will find a collection of my interests in science and beyond. I am currently navigating my third year as a PhD student at the Department of Physics of the University of Padova, within the LIPh lab under the supervision of Samir Suweis. My research activity involves the application of statistical physics tools such as Langevin models, disordered systems theory and machine learning to decipher large 'omic' data. Specifically, I am focusing on gut microbiomes, with the aim of uncovering the key factors influencing gastrointestinal dynamics, determinants of health and disease. I am also developing novel bioinformatics tools to generate novel multi-'omic and biologically consistent data. Beyond academia, my passion lies in connecting with people from diverse backgrounds. Coming from a quiet town in the Veronese countryside, my innate curiosity drives an overwhelming interest in the tapestry of the world. Engaging with people of different experiences not only broadens my understanding, but also brings unique perspectives to collaborative endeavours. The prospect of joining forces to explore the limitless possibilities together keeps me hopeful that there is always room for improvement. In my spare time, I take great pleasure in delving into readings from various disciplines such as economics, anthropology, history and politics. In the broader context of human knowledge, science is even more surprising than scientists think.

Research

  • Microbial Communities
  • Disordered systems
  • Bioinformatics
  • Machine Learning

In my research, I aim to seamlessly integrate theory and data to address key challenges in biology and statistical physics. Drawing on a background in physics and proficiency in computational methods, my goal is to extract valuable insights by combining theoretical frameworks with real-world data. What captivates me about this journey is the mutual influence between these disciplines – problems in one often spark solutions in the other. Recognizing the intricate relationship between theory and data, it's clear that big data, without a robust theoretical foundation, risks becoming mere storage without meaningful interpretation. Similarly, while elegant mathematical theories have the potential to inspire novel predictions, their refinement and validation benefit significantly from empirical observation and real-world data. The collaborative feedback loop between theory and data is at the heart of my approach. It goes beyond theory guiding understanding or data providing grounding; instead, it fosters a dynamic and enriching scientific environment. This collaborative stance facilitates a thorough exploration of complex biological systems and fundamental principles in statistical physics, ensuring a comprehensive understanding.

Publications

  • Emergent Patterns and Ecological Modelling of Gut Microbiomes in Health and Disease

    The Human Gut Microbiome (HGM) harbors a huge diversity in terms of species. Recent work has shown the existence of macroecological laws describing the variation ...

Projects

  • MetaGym

    Snakemake pipeline to perform analysis of shotgun metagenomic data

  • DIVA-MAGs

    Analysis and visualization of DIstribution of VAriants across MAGs

  • MME

    Maximum matching enritchment detection for biological networks

CV

Sept 2021 - Current

PhD scholarship
University of Padova, Padova, IT.

May 2021 - July 2021

Pre-PhD scholarship
IFOM Institute, Milan, IT.

2018 - 2021

Master of Physics of Complex Systems
University of Turin, Turin, IT.
Grade: 110L/110

Sep 2014 - Sep 2018

Bachelor's Degree in Physics
University of Padova, Padova, IT.
Grade: 84/110