Publications in Peer-Reviewed Journals Using TokaLab

1. N. Rutigliano et al., Physics-informed neural networks for the modelling of interferometer-polarimetry in tokamak multi-diagnostic equilibrium reconstruction, Plasma Physics and Controlled Fusion, Volume 67, 2025. Link to article

Works Presented at Scientific Conferences, Workshops, and Summer Schools

1. S. Kaldas et al.
   Developing Unsupervised Deep Learning Models for Real-Time Multi-Diagnostic Improved Processing in Tokamaks
   Presented at:
   • PhDiaFusion2025 – 6th Summer School of Plasma Diagnostics, Towards a Fusion Reactor: Synergy Between Public and Private Initiatives, 9–13 June 2025, Niepołomice Royal Castle, Poland
   • Joint EPS-SIF International School on Energy, Nuclear Energy and Its Challenging New Technologies, 23–28 June 2025, Villa Monastero, Varenna, Lake Como, Italy

2. T. Sajid et al.
   Divertor Tokamak Test Density Field Reconstruction Through Supervised Deep Learning Neural Network Architecture
   Poster Presentation, 14th ITER International Summer School, Aix-en-Provence, 2025

3. I. Wyss et al.
   Design Optimization of a Bolometer System for an ITER-Like Geometry
   Poster Presentation, 14th ITER International Summer School, Aix-en-Provence, 2025

4. N. Rutigliano et al.
   Multi-Diagnostic Plasma Equilibrium Reconstructions with Physics-Informed Neural Networks (PINNs) for Tokamak Applications
   ITER International School, 30 June – 4 July 2025

5. N. Rutigliano et al.
   A Multi-Diagnostics Plasma Equilibrium Reconstructor Through Physics-Informed Neural Networks (PINNs) for Nuclear Fusion Applications
   51st EPS Conference on Plasma Physics, 7–11 July 2025