ITER

“Design and implementation of machine learning-based anomaly detection in the ITER Tokamak Systems Monitor” - Frontiers in Physics
Description of the modular machine-learning anomaly-detection framework developed for ITER’s Tokamak Systems Monitor.
Jun 1, 2026 1 min read Publications
DOI Open access
“Design and implementation of machine learning-based anomaly detection in the ITER Tokamak Systems Monitor” - Frontiers in Physics
Design and implementation of machine learning-based anomaly detection in the ITER Tokamak Systems Monitor
The Tokamak Systems Monitor (TSM) is a software suite under development at ITER that provides operators with an integrated view of the …
Joris Paret, Brian Sammuli, Víctor Costa Pérez, Nathaniel Saura, Laura Hernández Cubo, Daniel Iglesias
Cite DOI Open access DOI PDF
“Machine Learning-Based Anomaly Detection for ITER's Tokamak Systems Monitor: A Gyrotron Case Study” - IEEE Transactions on Plasma Science
Proof of concept for detecting anomalous gyrotron pulses in ITER’s Tokamak Systems Monitor using dimensionality reduction and clustering.
May 8, 2026 1 min read Publications
DOI Open access
“Machine Learning-Based Anomaly Detection for ITER's Tokamak Systems Monitor: A Gyrotron Case Study” - IEEE Transactions on Plasma Science
Machine Learning-Based Anomaly Detection for ITER's Tokamak Systems Monitor: A Gyrotron Case Study
The ITER Tokamak Systems Monitor will provide operators with timely assessments of machine health, component lifetime, and early …
Joris Paret, Daniel Iglesias, Daniel Sabio Ruiz, Dilin Meloni, Andrea Antonione, Ruggero Bertazzoni, Giuseppe Carannante, Martino Ferrari, María Ortiz de Zúñiga, Mario Cavinato, Francisco Sánchez Arcos, Alfredo Portone
Cite DOI Open access DOI PDF
Preliminary machine learning-based calibration strategy for the ITER Tokamak Systems Monitor
A machine learning-based calibration strategy for the ITER Tokamak Systems Monitor (TSM) is presented, focusing on the optimization of …
Joris Paret, Daniel Iglesias, Hyogeon Bak, Matthew Clough, George Vayakis, Michael Walsh
Cite DOI Open access DOI PDF
Contribution to the 31st IEEE Symposium on Fusion Engineering
Participation to the 31st IEEE Symposium on Fusion Engineering (SOFE 2025) in Boston, presenting a scientific poster on machine learning-based anomaly detection for the ITER Tokamak Systems Monitor (TSM), using gyrotron pulse data from the European industrial prototype for ITER.
Jul 3, 2025 2 min read Conferences
SOFE 2025
Contribution to the 31st IEEE Symposium on Fusion Engineering
Contribution to the 33rd Symposium on Fusion Technology
Participation to the 33rd Symposium on Fusion Technology (SOFT 2024) in Dublin, presenting a scientific poster on a machine learning-based calibration strategy for the ITER Tokamak Systems Monitor (TSM) software suite.
Sep 22, 2024 2 min read Conferences
SOFT 2024
Contribution to the 33rd Symposium on Fusion Technology