Since my grandmother told me that the universe was made by tiny particles, I have been fallen in love with the deepest understanding of how nature works. Physics was my first love, in particular the theoretical aspects of particles, space, and time. I took my bachelor’s, master’s degree, and Ph.D. digging up the mysteries of the universe.
In one sense, I was interested in the language of nature. It sounds funny that now I am into another language, the human language. Currently, I am working and researching in the field of Artificial Intelligence. In particular, I am using deep learning to solve Natural Language Processing (NLP) problems. More in general, I am interested in AI research and in AI applications to science and social good. I am also committed to education and science communication.
- Freelance Research Scientist in AI working on projects which have a positive impact. Currently
- NLP for prevention and control of industrial pollution (Pi School, EU Joint Research Centre);
- Deep Learning for food & wine (VINHOOD) and for historical text data understanding.
- Machine Learning Instructor @ MHPC (SISSA/ICTP, Trieste), @ Experis Academy, @ Codingwaves ;
- Scientific Advisor @ AINDO and APICAL (high-tech startups).
- (2018-2020) Senior Deep Learning Scientist @ Harman, a Samsung Company (Bixby Vocal Assistant Project);
- (2017) Research Grant (Postdoc), Deep Learning for Nanoscience @ Italian Centre for Research (CNR).
- Ph.D. in Statistical Physics @ SISSA (2016, Group Page)
Thesis: On entanglement negativity in 1+1 and 2+1 dimensional quantum systems
Details: I pursued research in fundamental physical quantities such as entanglement entropy, mutual information, and entanglement negativity. These quantities have relevant roles in many-body physics, quantum information theory and holographic theories, such as ADS/CFT. Besides an analytical component, my work had a strong numerical approach which materialized in several publications on relevant scientific journals (Google Scholar).
- Master in High-Performance Computing (CNR-IOM fellowship, 2017)
Project: Deep Learning for Nanoscience Scanning Electron Microscope Image Recognition
- Master Degree in Theoretical Particle Physics, Padua University (2011)
Thesis: Supersymmetric Sigma Models in two-dimension and their integrability (PI: Prof. D. Sorokin)
- Bachelor Degree in Physics, Padua University (2008)
Thesis: Feynman Path Integral and Stochastic Processes (PI: Prof. P. Marchetti)