Simone Pezzuto

Assistant Professor

University of Trento

Italy

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Simone Pezzuto is an Assistant Professor at the University of Trento, Italy. His research focuses on cardiac electrophysiology, with recent articles exploring topics such as electroanatomic mapping, digital twins of the cardiac system, and advanced modeling techniques for atrial fibrillation. He employs innovative methods like physics-informed neural networks and ensemble learning to enhance understanding of cardiac function and pathology.

Articles (20)

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2026

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2025

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2021

Collaborators (10)

Marcus Grote

University of Basel

SWITZERLAND

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Paris Perdikaris

University of Pennsylvania

UNITED STATES

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Pietro Bonizzi

University of Maastricht

NETHERLANDS

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Gundolf Haase

Univ.-Prof.

Graz University of Technology

AUSTRIA

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Gernot Plank

Medical University of Graz

AUSTRIA

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Sander Verheule

Associate Professor

University of Maastricht

NETHERLANDS

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Frits W. Prinzen

NETHERLANDS

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Alexander Effland

University of Bonn

GERMANY

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Edward Vigmond

University of Bordeaux

FRANCE

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Ulrich Schotten

Prof., Head of Dept.

University of Maastricht

NETHERLANDS

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Simone Pezzuto

Research Interests

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Articles (20)

Recovering intrinsic conduction velocity and action potential duration from electroanatomic mapping data using curvature

High-density and high-coverage composite atrial activation maps

Accurate and efficient cardiac digital twin from surface ECGs: Insights into identifiability of ventricular conduction system

Simulation-free prediction of atrial fibrillation inducibility with the fibrotic kernel signature

Ensemble learning of the atrial fibre orientation with physics‐informed neural networks

Probabilistic learning of the Purkinje network from the electrocardiogram

Reconstruction of the local contractility of the cardiac muscle from deficient apparent kinematics

Digital Twinning of Cardiac Electrophysiology Models From the Surface ECG: A Geodesic Backpropagation Approach

A novel sequential endocardial mapping strategy for locating atrial fibrillation sources based on repetitive conduction patterns: An in-silico study

Boundary integral formulation of the cell-by-cell model of cardiac electrophysiology

Δ-PINNs: Physics-informed neural networks on complex geometries

Explicit stabilized multirate methods for the monodomain model in cardiac electrophysiology

Synchronization of repolarization after cardiac resynchronization therapy: A combined clinical and modeling study

Space–time shape uncertainties in the forward and inverse problem of electrocardiography

GEASI: Geodesic‐based earliest activation sites identification in cardiac models

Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling

Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fibre structure and anisotropic conduction in a patient-specific model

Synergistic antiarrhythmic effect of inward rectifier current inhibition and pulmonary vein isolation in a 3D computer model for atrial fibrillation

Short P‐Wave Duration is a Marker of Higher Rate of Atrial Fibrillation Recurrences after Pulmonary Vein Isolation: New Insights into the Pathophysiological Mechanisms Through Computer Simulations

Left Atrial Appendage Electrical Isolation Reduces Atrial Fibrillation Recurrences

Collaborators (10)

Marcus Grote

Paris Perdikaris

Pietro Bonizzi

Gundolf Haase

Gernot Plank

Sander Verheule

Frits W. Prinzen

Alexander Effland

Edward Vigmond

Ulrich Schotten

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