Pietro Rotondo

Pietro Rotondo is an Assistant Professor (Ricercatore a tempo determinato) at the University of Parma, Italy, within the Department of Mathematical, Physical and Computer Sciences. He is actively involved in lecturing the course Principles of Physics to first-year students of the Earth Sciences bachelor programme for the academic years 2023/2024 and 2024/2025.

Education & Academic Background: While explicit educational history is not detailed in the text, his faculty rank and research output indicate advanced training in theoretical physics and statistical mechanics, likely culminating in a PhD.

Research Interests:

• Statistical mechanics of deep learning and artificial neural networks
• Bayesian inference in high-dimensional, disordered systems
• Phase transitions and replica methods in complex systems
• Quantum many-body physics and cavity quantum electrodynamics
• Renormalization group approaches to finite-width neural networks

His interdisciplinary work bridges rigorous physics techniques with modern machine-learning challenges, aiming to uncover universal laws governing learning and generalization in artificial systems.

Recent Publication Trends: Over the past five years, Rotondo has concentrated on developing analytical frameworks that describe how deep neural networks learn and generalize, particularly beyond the infinite-width limit. Recurring themes include Bayesian effective actions, kernel renormalization, and the statistical mechanics of structured data.

Scientific Awards & Honors:

• No specific awards are mentioned in the provided text.

Supervision & Funding: The text does not list current PhD or Master’s students, nor does it detail specific grants or funded projects.

Laboratories & Teams: No named laboratories, centers, or research groups are explicitly cited in the scraped material.