E. Aymerich

653 total citations
12 papers, 91 citations indexed

About

E. Aymerich is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics and Control and Systems Engineering. According to data from OpenAlex, E. Aymerich has authored 12 papers receiving a total of 91 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Nuclear and High Energy Physics and 3 papers in Control and Systems Engineering. Recurrent topics in E. Aymerich's work include Magnetic confinement fusion research (5 papers), Anomaly Detection Techniques and Applications (4 papers) and Nuclear reactor physics and engineering (3 papers). E. Aymerich is often cited by papers focused on Magnetic confinement fusion research (5 papers), Anomaly Detection Techniques and Applications (4 papers) and Nuclear reactor physics and engineering (3 papers). E. Aymerich collaborates with scholars based in Italy, United Kingdom and Switzerland. E. Aymerich's co-authors include Alessandra Fanni, B. Cannas, G. Sias, F. Pisano, Sara Carcangiu, C. Sozzi, C. Stuart, P. Carvalho, Jet Contributors and the JET EFDA Contributors and has published in prestigious journals such as Applied Sciences, Nuclear Fusion and Fusion Engineering and Design.

In The Last Decade

E. Aymerich

11 papers receiving 85 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
E. Aymerich Italy	5	54	29	27	13	12	12	91
C. Stuart United Kingdom	6	81 1.5×	21 0.7×	25 0.9×	14 1.1×	5 0.4×	11	105
Liang Zheng China	10	262 4.9×	35 1.2×	12 0.4×	4 0.3×	5 0.4×	39	311
Ekaterina Govorkova United States	6	52 1.0×	46 1.6×	3 0.1×	4 0.3×	3 0.3×	9	99
D. Bortolato Italy	7	50 0.9×	12 0.4×	6 0.2×	18 1.4×	7 0.6×	25	267
H. Peek Netherlands	7	60 1.1×	8 0.3×	17 0.6×	39 3.0×	6 0.5×	17	169
P. Adamson United States	7	37 0.7×	4 0.1×	24 0.9×	6 0.5×	2 0.2×	20	87
J. Kieseler Switzerland	6	115 2.1×	42 1.4×	7 0.3×	12 0.9×	2 0.2×	15	159
Felipe Rudge Barbosa Brazil	7	29 0.5×	8 0.3×	13 0.5×	12 0.9×	22 1.8×	61	219
F. Ratnikov Russia	6	61 1.1×	18 0.6×	5 0.2×	12 0.9×	2 0.2×	28	90
T. K. Aarrestad Switzerland	6	83 1.5×	59 2.0×	6 0.2×	9 0.7×	1 0.1×	8	148

Countries citing papers authored by E. Aymerich

Since Specialization

Citations

This map shows the geographic impact of E. Aymerich's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by E. Aymerich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. Aymerich more than expected).

Fields of papers citing papers by E. Aymerich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Aymerich. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by E. Aymerich. The network helps show where E. Aymerich may publish in the future.

Co-authorship network of co-authors of E. Aymerich

This figure shows the co-authorship network connecting the top 25 collaborators of E. Aymerich. A scholar is included among the top collaborators of E. Aymerich based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with E. Aymerich. E. Aymerich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Aymerich, E., Augusto Montisci, R. Delogu, et al.. (2025). Automatic estimation of heat loads distribution on STRIKE through multi-layer perceptrons. Fusion Engineering and Design. 219. 115306–115306.

Aymerich, E., et al.. (2024). A self-organised partition of the high dimensional plasma parameter space for plasma disruption prediction. Nuclear Fusion. 64(10). 106063–106063. 1 indexed citations

Aymerich, E., E. Alessi, B. Cannas, et al.. (2024). eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices. Frontiers in Physics. 12. 3 indexed citations

Aymerich, E., et al.. (2024). MHD spectrogram contribution to disruption prediction using Convolutional Neural Networks. Fusion Engineering and Design. 204. 114472–114472. 3 indexed citations

Aymerich, E., B. Cannas, F. Pisano, et al.. (2023). Performance Comparison of Machine Learning Disruption Predictors at JET. Applied Sciences. 13(3). 2006–2006. 10 indexed citations

Aymerich, E., et al.. (2023). CNN disruption predictor at JET: Early versus late data fusion approach. Fusion Engineering and Design. 193. 113668–113668. 6 indexed citations

Aymerich, E., F. Pisano, B. Cannas, et al.. (2023). Physics Informed Neural Networks towards the real-time calculation of heat fluxes at W7-X. Nuclear Materials and Energy. 34. 101401–101401. 9 indexed citations

Aymerich, E., G. Sias, F. Pisano, et al.. (2022). Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles. Nuclear Fusion. 62(6). 66005–66005. 33 indexed citations

Aymerich, E., Alessandra Fanni, G. Sias, et al.. (2020). A statistical approach for the automatic identification of the start of the chain of events leading to the disruptions at JET. Nuclear Fusion. 61(3). 36013–36013. 22 indexed citations

10.

Aymerich, E., et al.. (2020). Extraction of the plasma current contribution from the numerically integrated magnetic signals in ISTTOK. Journal of Instrumentation. 15(2). C02020–C02020. 1 indexed citations

11.

Aymerich, E., et al.. (2018). Virtual Reality Experience for Interior Design Engineering Applications. UNICA IRIS Institutional Research Information System (University of Cagliari). 1–4. 2 indexed citations

12.

Aymerich, E., et al.. (2018). Analysis of Synthetic Light Field Data Compression Performances. UNICA IRIS Institutional Research Information System (University of Cagliari). 64. 1–4. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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