Alberto Fachechi

• Contents: My research activity is placed in the wide discipline of statistical mechanics methods for complex systems analysis, in particular concerning spin-glass theory and its application to modern Artificial Intelligence and Machine Learning. Within this framework, I also study data-driven associative memories, i.e. networks that build their memories from examples, addressing how they capture the low-dimensional structure of data and how this affects retrieval, generalization and memorization.
• Methods: The core research interest consists in the development of rigorous mathematical techniques, involving in particular Guerra's interpolating schemes, non-linear PDE theory, probability and statistics and random matrix theory.
• Other interests: My research interests also cover the application of statistical inference tools to real-world (in particular, biological) problems.

Neural Networks; Machine Learning; Deep Learning; Artificial Intelligence; Spin-glass Theory; Statistical Physics; Mathematical Physics; Theoretical Physics.

• Regularization, early-stopping and dreaming: a Hopfield-like setup to address generalization and overfitting
  E. Agliari, F. Alemanno, M. Aquaro, A. Fachechi
  Neural Networks 177, 106389 (2024)
  Total number of citations: 50
• Quantifying heterogeneity to drug response in cancer–stroma kinetics
  F. Alemanno, M. Cavo, D. Delle Cave, A. Fachechi, R. Rizzo, E. D’Amone, G. Gigli, E. Lonardo, A. Barra, L. L Del Mercato
  Proceedings of the National Academy of Sciences 120 (11), e2122352120 (2023)
  Total number of citations: 8
• Outperforming RBM feature-extraction capabilities by “dreaming” mechanism
  A. Fachechi, A. Barra, E. Agliari, F. Alemanno
  IEEE transactions on neural networks and learning systems 35 (1), 1172-1181 (2022)
  Total number of citations: 26
• Neural networks with a redundant representation: Detecting the undetectable
  E. Agliari, F. Alemanno, A. Barra, M. Centonze, A. Fachechi
  Physical review letters 124 (2), 028301 (2020)
  Total number of citations: 57
• Dreaming neural networks: forgetting spurious memories and reinforcing pure ones
  A. Fachechi, E. Agliari, A Barra
  Neural Networks 112, 24-40 (2019)
  Total number of citations: 104
• Virasoro vacuum block at next-to-leading order in the heavy-light limit
  M. Beccaria, A. Fachechi, G. Macorini
  Journal of High Energy Physics 2016 (2), 1-22 (2016)
  Total number of citations: 56

• Since December 2024, I am member of the Department Committee for informatic resources.
• On November 2024, I earned the National Certification for Associate Professor in Mathematical Physics (Abilitazione Scientifica Nazionale per Professore di II fascia, SC: 01/A4), see the final judgement of the MUR committee (in italian).
• Since April 2023, I have been part of the FAIR foundation, a PNRR-funded project aiming at high-quality research in the field of Artificial Intelligence. Specifically, I am a Researcher for the Spoke 5 (WP5.5) with main research line "Quality assessment in Hard Sciences and AI". I am also responsible for communication for the organization of dissemination events within the FAIR group.
• My recent research activity has benefited from the stimulating environment provided by the Alan Turing Institute’s event “Physics-informed Machine Learning”, which took place in London from 16 to 23 January, 2023.
• My work on "Dreaming Neural Networks" has attracted much attention from the general press, see for example this article.
• Since 2018, I have been member of the National Group of Mathematical Physics (GNFM-INdAM), within the community of Mechanics for Discrete Systems.