Michela Gelfusa

Professor

Università degli Studi di Roma La Sapienza

Italy

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About

Professor Michela Gelfusa is a faculty member at the Università degli Studi di Roma Tor Vergata, Italy. Her research focuses on the application of advanced computational techniques in plasma physics, specifically in the context of tokamak diagnostics and disruptions. Recent articles include investigations into Bayesian ensemble algorithms, physics-informed neural networks, and anomaly detection in tokamak plasmas.

Articles (18)

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2025

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2025

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2022

Collaborators (16)

Laurent Chôné

University of Helsinki

FINLAND

Michela Gelfusa

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Articles (18)

On the potential and limitations of Bayesian ensemble algorithms for the decomposition of time series generated by tokamak diagnostics

Symbolic dynamics for disruption prediction in case of data scarcity and diagnostic limitations

Physics-informed neural networks for the modelling of interferometer-polarimetry in tokamak multi-diagnostic equilibrium reconstructions

Time-resolved, physics-informed neural networks for tokamak total emission reconstruction and modelling

A hybrid physics/data-driven logic to detect, classify, and predict anomalies and disruptions in tokamak plasmas

Thermo-Hydraulic Design of the First Wall of the DTT Facility

A systematic investigation of radiation collapse for disruption avoidance and prevention on JET tokamak

Correction of JET bolometric maximum likelihood tomography for local gas puffing

New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing

On the Potential of Relational Databases for the Detection of Clusters of Infection and Antibiotic Resistance Patterns

Neutronics Assessment of the Spatial Distributions of the Nuclear Loads on the DEMO Divertor ITER-like Targets: Comparison between the WCLL and HCPB Blanket

Maximum likelihood bolometry for ASDEX upgrade experiments

On the potential of physics-informed neural networks to solve inverse problems in tokamaks

Conditional recurrence plots for the investigation of sawteeth pacing with RF modulation

Proposal of a testing procedure to qualify ITER window assemblies and absorbing coatings exposed to high microwave stray radiation

Disruption prediction with artificial intelligence techniques in tokamak plasmas

Dealing with artefacts in JET iterative bolometric tomography using masks

Development of robust indicators for the identification of electron temperature profile anomalies and application to JET

Collaborators (16)

Laurent Chôné

Andrea Malizia

Henri Kumpulainen

Renato GATTO

Andrea Gaetano Chiariello

Ruben Otin

Karol Malinowski

Mirko Salewski

Jerzy Wojciech Mietelski

Sebastián Dormido-Canto

Marwa Ben Yaala

Bohdan Bieg

Raffaele Fresa

Pasqualino Gaudio

Paulo Rodrigues

Gianluca Verona Rinati

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