Phd in MATHEMATICS

email: agliari@mat.uniroma1.it
phone: 349 4773746
building: CU006
room: 101

Education and Qualification
2007: Ph.D. diploma in Physics at Department of Physics, University of Parma (Italy)
2004: Master Degree in Physics at Department of Physics, University of Parma (Italy)
2022: National Scientific Qualification in Mathematical Physics (01/A4) as Full Professor
2018: National Scientific Qualification in Theoretical Physics of Fundamental Interactions (02/A2) as Associate Professor
2013: National Scientific Qualification in Theoretical Physics of Matter (02/B2) as Associate Professor

Main Academic Appointments
2022-present: Associate Professor in Mathematical Physics at Mathematics Department, Sapienza University of Rome (Italy)
2019-2022: Assistant Professor (RTD-B) at Mathematics Department, Sapienza University of Rome (Italy)
2015-2019: Researcher (RTD-A) at Mathematics Department, Sapienza University of Rome (Italy)
2014: Research fellowship at Physics Department, Sapienza University of Rome (Italy)
2010-2013: Researcher (RTD) and local Coordinator for the FIRB project “Dynamics and statistical mechanics of lymphocyte networks below the percolation threshold”, at Physics Department, University of Parma (Italy)
2010: Fellowship from “Fondazione Angelo della Riccia”, at Laboratoire de Physique Théorique de la Matière Condensée, Université Pierre et Marie Curie, Paris (France)
2008: Fellowship from “Fondazione Angelo della Riccia”, at Albert-Ludwigs-Universität, Freiburg (Germany)

Main Teaching and Academic Duties (since 2020)
2019/20-2023/24: “Mathematical models for Neural Networks” at University Sapienza of Rome (Italy) - Lecturer
2019/20-2023/24: “Calculus and Biostatistics” at University Sapienza of Rome (Italy) - (Co)-Lecturer
Since 2022: Member of the PhD Board for the PhD course in Mathematics, Sapienza University of Rome
Since 2018: Member of the Committee for Placement for the courses “Mathematics” and “Mathematics for Applications”, Sapienza University of Rome and for the Faculty of “Sciences”, Sapienza University of Rome

Grants as PI (since 2020)
2022: PNRR grant PE1 spoke 5 - “Foundations of High-Quality AI” (prot. PE1221852F8F23A5) - research line “Theory of information-processing in (deep) Neural Networks”
2022: Award grants for researchers from Fondo sociale Europe plus (FSE+)
2021: Fondi Ateneo Sapienza to lead investigations on “Rigorous approaches to the study of collective behaviors” (prot. RM12117A8590B3FA)
2020: Fondi Ateneo Sapienza to lead investigations on “Mathematical methods and models for complex systems” (prot. RM120172B8066CB0)

Editorial Board (since 2020)
Since 2022: Main Editor for Physica A: Statistical Mechanics and its Applications
2019-2023: Member of the Divisional Associate Editor for Physical Review Letters
2017-2022: Member of the Advisory Panel for the Journal of Physics A: Mathematical and Theoretical

Invited seminars and colloquia (since 2020)
28 May: Invited seminar “Complexity and Machine Learning”, Department of Mathematics, Goethe-Universität Frankfurt (Germany)
16 May 2024: Invited Colloquium “Machine Learning: from mammal's brain to statistical mechanics”, Frascati National Laboratories (”Spring School 'Bruno Touschek' in Nuclear, Subnuclear and Astroparticle Physics”), (Italy)
4 December 2023: Invited Colloquium “A statistical-mechanics approach to (shallow) neural networks”, School of Physical and Mathematical Sciences, Nanyang Technology University (Singapore)
3 May 2023: Invited seminar “Mathematical methods for Boltzmann machines”, University of Salento (Italy)
12 January 2023: Invited seminar “Dense neural networks that learn, store and retrieve”, Istituto Superiore di Sanità (Italian National Institute of Health), Roma (Itay)
25 January 2022: Invited seminar “The emergence of concepts in shallow neural-networks”, Mathematical Institute, University of Oxford (UK)
19 November 2021: Invited seminar “Some rigorous results on Boltzmann machines”, University of South Wales, Pontypridd (UK)
10 May 2021: Invited seminar “From Memory to Learning and backward”, University of Salento (Italy)
25 November 2020: Invited seminar “Complexity in neural networks: the good with the bad”, Institute for Cross-Disciplinary Physics & Complex Systems, Palma de Mallorca (Spain)
1 July 2020: Invited seminar “Machine Learning from a Mathematical perspective”, ISMAR-CNR, Roma (Italy)

Invited contributions in workshops (since 2020)
22-24 May 2024: “From Machine-Learning Theory to Driven Complex Systems and back” CECAM-HQ-EPFL, Lausanne (Switzerland) invited talk “Information processing from classical-conditioning to contrastive-divergence”
15 February 2024: “FAIR-Meeting Spoke 5” Department of Computer, Control and Management Engineering (DIAG), Sapienza University of Roma (Italy) invited talk “Associative neural networks beyond retrieval: learning and generalization on structured data sets”
31 January 2024: “Dialogs on Neuronal Networks: Theoretical and Biological Perspectives” Istituto Superiore di Sanità, Roma (Italy) invited talk “Biological inspired Machine Learning”
15 September 2023: “RoMaDS: A day on Statistical Physics for Machine Learning”, Department fo Mathematics, University of Roma Tor Vergata (Italy) invited talk “The early bird regularises better”
11-16 June 2023: “Mathematical Physics of Complex Systems”, Palazzone di Cortona (Italy) invited talk “The early bird regularises better”
30 May 2023: “Hard sciences for machine learning”, Auditorium dell’Area della Ricerca del CNR, Pisa (Italy) invited talk “The emergence of concepts in shallow neural-networks”
26-31 March 2023: “DPG-Frühjahrstagung (DPG Spring Meeting) - DPG Focus Session: Physics meets ML”, Technical University of Dresden (Germany) invited talk “The emergence of concepts in shallow neural-networks”
2 December 2022: “Guerra80: Interpolating maxima of rugged landscapes”, Sapienza University of Rome (Italy) invited talk “Recurrent neural networks that generalize from examples and improve by dreaming”
24 October 2022: “From Dispersive Hydrodynamics to Forecasting, Machine Learning and Back”, Isaac Newton Institute, Cambridge (UK) invited talk “A Crossroad between Statistical Mechanics, PDE-Theory, Neural networks and Machine learning”
13-14 June 2022: “Random graphs and Networks Workshop”, Mathematics Department of the University of South Wales (UK) invited talk “Complex (neural) networks for complex tasks”
5 August 2021: Invited talk at the Sci-ML webinar series “Learning from Storing”, Carnegie Mellon University, Pittsburgh (US)
22 July 2021: Invited panelist at the workshop “Physical Review Referee Orientation Session”, organised by the American Physical Society
15-18 March 2021: “Machine Learning and Statistical Physics”, Lagrange Mathematics and Computation Research Center , Paris (France), invited talk “Learning from Storing”
24-26 February 2020: “International Max-Planck Research School - Physics of Biological and Complex Systems”, Göttingen (Germany), invited talk “Complexity in neural networks: the good with the bad”

Scientific Committees, Reviewer activity (since 2020)
Reviewer for the following project founding institutions:
2023: Serrapilheira Institute (Brazil)
2023: External jury member for the “Machine Learning track” at the Radboud science faculty (The Netherlands)
2021: Agencia Nacional de Investigación y Desarrollo (Gobierno de Chile)
2021: University of Insubria
2020: Polish National Science Center
2020: Alexander von Humboldt Foundation
2020: IMéRA: Institut d'études avancées d’Aix-Marseille (Foundation of Université d’Aix-Marseille)
2020: Swiss National Science Foundation
Member of the following evaluation committees:
2024: Member of the Assessment Committee for the upgrade from Tenure Track position (RTD-B) to Associate Professor in Mathematical Physics at University of L’Aquila (Italy)
2024: Member of the Selection Committee for a tenure-track position on “Statistical Physics and Machine Learning” at Ecole Normale Supérieure, Paris (France)
2024: Member of the Selection Committee for an Assistant/Associate Professor level in Theoretical Biophysics at Radboud University, Nijmegen (The Netherlands)
2024: Member of the Selection Committee for a Tenure Track position (RTT) in Mathematical Physics at University of Modena and Reggio Emilia (Italy)
2024: Member of the Assessment Committee for the PhD programme in Mathematics at University of Bologna (Italy)
2023: Member of the Selection Committee for a Teaching assignment in the Faculty of Science at the University Sapienza of Roma (Italy)
2023: Member of the Assessment Committee for the PhD programme in Physics at University Tor Vergata, Roma (Italy)
2022-2023: Member of the monitoring panel for the AI National Ph.D. program
2022: Member of the Selection Committee for a one-year Fellowship in the field of Mathematical Physics and Probability and Mathematical Statistics at the University Sapienza of Roma (Italy)
2022: Member of the Selection Committee for Tutoring fellowships in the Faculty of Science at the University Sapienza of Roma (Italy) [twice]
2021: Member of the Selection Committee for a one-year Fellowship in the field of Mathematical Physics and Probability and Mathematical Statistics at the University Sapienza of Roma (Italy)
2020: Member of the Selection Committee for a two-year Fellowship in the field of Mathematical and its applications at the University Sapienza of Roma (Italy)
2020: Member of the Assessment Committee for the PhD programme in Physics at the Laboratories de Physique de l’École Normale Supérieure, Paris (France)

Summary of Scientific Achievements
Production_ Publications (ISI): 132 Scientific Book Chapters: 3 Referred Proceedings: 8
Impact_ Total Citations 2856 h-index: 30 Source: GoogleScholar
Spreading_ Invited Seminars: 69 Invited lecturer for PhD programs: 3 Organized Intl. Workshops: 7

Publications (since 2020)
E. A., F. Alemanno, Aquaro, A. Fachechi, Regularization, early stopping and dreaming, Neur. Netw. 177, 106389 (2024).
E. A., A. Fachechi, D. Luongo, Algebraic properties for Hebbian-like kernels, Appl. Math. Comp. 474, 128689 (2024).
M. Aquaro, F. Alemanno, I. Kanter, F. Durante, A. Barra, E. Agliari, Hebbian dreaming for small datasets, Neur. Netw. 173, 106174 (2024).
E. A., A. Alessandrelli, A. Barra, F. Ricci-Tersenghi, Parallel learning by multitasking neural networks, J. Stat. 113401 (2023).
E. A., F. Alemanno, Aquaro, A. Barra, Ultrametric identities in glassy models of Natural Evolution, J. Phys. A 56, 385001 (2023).
E. A., L. Albanese, F. Alemanno, A. Alessandrelli, A. Barra, F. Giannotti, D. Lotito, and D. Pedreschi. Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning, Physica A 627, 129143 (2023).
E. A., L. Albanese, F. Alemanno, A. Alessandrelli, A. Barra, F. Giannotti, D. Lotito, and D. Pedreschi, Dense Hebbian neural networks: a replica symmetric picture of supervised learning, Physica A 626, 129076 (2023).
E. A., F. Alemanno, Aquaro, A. Barra, C. Marullo, From Pavlov Condition to Hebb Learning, Neural Comput. 35, 930 (2023)
F. Alemanno, M. Aquaro, I. Kanter, A. Barra, E.A., Supervised Hebbian learning, Europhys. Lett. Perspective 141, 11001 (2023)
100. E.A., A. Fachechi, C. Marullo, Non-linear PDEs approach to statistical mechanics of dense associative memories, J. Math. Phys. (2022)
A. Fachechi, F. Alemanno, A. Barra, E.A., Outperforming RBM Feature-Extraction Capabilities by “Dreaming” Mechanism, IEEE Trans. Neur. Netw. (2022)
E.A., F. Alemanno, A. Barra, G. De Marzo, Unsupervised learning: the emergence of a concepts in associative neural networks, Neur. Netw. 148, 232 (2022)
E.A., F.E. Leonelli, C. Marullo, Storing, learning and retrieving biased patterns, Apps. Math. Comp. 415, 126716 (2021)
E.A., G. Sebastiani, Learning and retrieval operational modes for three-layer restricted Boltzmann Machines, J. Stat. Phys. 185, 10 (2021)
E.A., F. Alemanno, L. Albanese, A. Fachechi, A transport equation approach for deep neural networks with quenched random weights, J. Phys. A 54, 505004 (2021)
F.E. Leonelli, E.A., L. Albanese, A. Barra, On the effective initialisation for restricted Boltzmann machines via duality with Hopfield model, Neur. Net. 143, 314-326 (2021)
C. Marullo, E.A., Boltzmann machines as generalised Hopfield networks: a review on recent results and outlooks, Entropy 23, 34 (2021)
E.A., A. Barra, P. Sollich, L. Zdeborová, Machine learning and statistical physics: preface, J. Phys. A 53, 500401(2020)
E.A., G. De Marzo, Tolerance versus synaptic noise in dense associative memories, Europ. Phys. J. Plus 135, 883 (2020)
E.A., A. Fachechi, C. Marullo, The relativistic Hopfield model with correlated patterns, J. Math. Phys. (2020)
E.A., L. Albanese, A. Barra, G. Ottaviani, Replica symmetry breaking in neural networks: a few steps toward rigorous results, J. Phys. A 53, 415005 (2020)
E.A., F. Alemanno, A. Barra, A.O. Barra, A. Fachechi, L. Moretti, L. Franceschi-Vento, Analysis of temporal correlation in heart rate variability through maximum entropy principle in a minimal pairwise glassy model, Sci. Rep. 10, 15353 (2020)
E.A., A. Barra, A.O. Barra, A. Fachechi, L. Moretti, L. Franceschi-Vento, Detecting heart pathologies via machine learning on clinical markers, Sci. Rep. 10, 8845 (2020)
E.A., F. Alemanno, A. Barra, A. Fachechi, Generalized Guerra’s interpolazione techniques for dense associative networks, Neur. Net. 128, 254 (2020)
E.A., P. Saez, A. Barra, M. Piel, P. Vargas, M. Castellana, A statistical inference approach to reconstruct intercellular interactions in cell migration experiments, Science Adv. 6, eaay2103 (2020)
E.A., F. Alemanno, A. Barra, M. Centonze, A. Fachechi, Neural networks with Redundant Representation: Detecting the Undetectable, Phys. Rev. Lett. 124, 028301 (2020)