Mattia Tarabolo

Ph.D. candidate in Fisica , 38th cycle (2022-2025)
Department of Applied Science and Technology (DISAT)

Docente esterno e/o collaboratore didattico
Ateneo (ATENEO)

Profile

PhD

Tutors

Research interests

Artificial neural networks
Bayesian inference
Bayesian networks
Belief propagation
Complex networks
Complex systems
Epidemic inference
Machine learning
Message passing algorithms
Out-of-equilibrium dynamics
Physics of complex systems
Random matrices
Statistical physics

Biography

I am a PhD student in Physics of Complex Systems. I am interested in the applications of statistical physics to optimization and inference problems. I am currently working on the development of message passing methods for bayesian inference of epidemics, as well as on the study of random matrices through message passing algorithms and on the applications of statistical physics to machine learning algorithms.

Research topics

  • Applications of statistical physics to machine learning algorithms
  • Development of bayesian inference methods through message passing algorithms for epidemiologic inference
  • Study of random matrices through message passing algorithms

Skills

ERC sectors

PE2_18 - Equilibrium and non-equilibrium statistical mechanics: steady states and dynamics
PE2_16 - Non-linear physics
PE3_16 - Physics of biological systems
PE1_13 - Probability
PE3_15 - Statistical physics: phase transitions, condensed matter systems, models of complex systems, interdisciplinary applications
PE3_13 - Structure and dynamics of disordered systems, e.g. soft matter (gels, colloids, liquid crystals), granular matter, liquids, glasses, defects

Research

Other activities and projects related to research

I am a PhD student in Physics of Complex Systems. I am interested in the applications of statistical physics to optimization and inference problems. I am currently working on the development of message passing methods for bayesian inference of epidemics, as well as on the study of random matrices through message passing algorithms and on the applications of statistical physics to machine learning algorithms.