M. Mattei

5.1k total citations
178 papers, 2.3k citations indexed

About

M. Mattei is a scholar working on Aerospace Engineering, Nuclear and High Energy Physics and Control and Systems Engineering. According to data from OpenAlex, M. Mattei has authored 178 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Aerospace Engineering, 74 papers in Nuclear and High Energy Physics and 65 papers in Control and Systems Engineering. Recurrent topics in M. Mattei's work include Magnetic confinement fusion research (74 papers), Superconducting Materials and Applications (49 papers) and Fusion materials and technologies (29 papers). M. Mattei is often cited by papers focused on Magnetic confinement fusion research (74 papers), Superconducting Materials and Applications (49 papers) and Fusion materials and technologies (29 papers). M. Mattei collaborates with scholars based in Italy, France and Germany. M. Mattei's co-authors include Egidio D’Amato, Immacolata Notaro, R. Albanese, Francesco Amato, R. Ambrosino, Luciano Blasi, Valerio Scordamaglia, A. Pironti, F. Villone and G. De Tommasi and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and International Journal of Hydrogen Energy.

In The Last Decade

M. Mattei

171 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Mattei Italy 26 895 890 848 503 473 178 2.3k
G. Ambrosino Italy 22 901 1.0× 493 0.6× 418 0.5× 498 1.0× 311 0.7× 109 1.5k
M. Ariola Italy 27 862 1.0× 594 0.7× 3.0k 3.5× 534 1.1× 274 0.6× 150 4.2k
G. De Tommasi Italy 25 1.1k 1.2× 452 0.5× 1.3k 1.6× 624 1.2× 389 0.8× 210 3.0k
D.J.N. Limebeer United Kingdom 31 173 0.2× 434 0.5× 2.5k 2.9× 186 0.4× 36 0.1× 154 3.9k
Luca Zaccarian Italy 39 136 0.2× 547 0.6× 4.9k 5.7× 223 0.4× 45 0.1× 275 5.8k
Min-Jea Tahk South Korea 35 138 0.2× 4.6k 5.2× 1.7k 2.0× 62 0.1× 41 0.1× 268 5.3k
B. Bandyopadhyay India 37 76 0.1× 845 0.9× 4.7k 5.5× 163 0.3× 71 0.2× 312 5.8k
Peter O’Shea Australia 19 37 0.0× 402 0.5× 375 0.4× 158 0.3× 21 0.0× 101 1.3k
Bong Wie United States 35 29 0.0× 3.4k 3.8× 3.2k 3.7× 55 0.1× 83 0.2× 203 5.5k
Wei Kang United States 24 14 0.0× 726 0.8× 1.1k 1.3× 54 0.1× 68 0.1× 115 2.2k

Countries citing papers authored by M. Mattei

Since Specialization
Citations

This map shows the geographic impact of M. Mattei'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 M. Mattei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Mattei more than expected).

Fields of papers citing papers by M. Mattei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Mattei. 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 M. Mattei. The network helps show where M. Mattei may publish in the future.

Co-authorship network of co-authors of M. Mattei

This figure shows the co-authorship network connecting the top 25 collaborators of M. Mattei. A scholar is included among the top collaborators of M. Mattei 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 M. Mattei. M. Mattei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mele, Adriano, C. Galperti, M. Mattei, et al.. (2025). Implementation of an ITER-relevant QP-based current limit avoidance algorithm in the TCV tokamak. Plasma Physics and Controlled Fusion. 67(5). 55017–55017.
2.
Felici, F., M. Mattei, A. Merle, et al.. (2024). Automated shot-to-shot optimization of the plasma start-up scenario in the TCV tokamak. Nuclear Fusion. 64(9). 96032–96032. 3 indexed citations
3.
Mattei, M., et al.. (2023). A data-driven Vertical Stabilization system for the ITER tokamak based on Dynamic Mode Decomposition. Journal of the Franklin Institute. 361(2). 816–833. 1 indexed citations
4.
Sauter, O., E. Fable, F. Felici, et al.. (2023). Scenario optimization for the tokamak ramp-down phase in RAPTOR: Part B. safe termination of DEMO plasmas. Plasma Physics and Controlled Fusion. 66(2). 25007–25007. 6 indexed citations
5.
D’Amato, Egidio, et al.. (2023). Distributed Navigation in Emergency Scenarios: A Case Study on Post-Avalanche Search and Rescue Using Drones. Applied Sciences. 13(20). 11186–11186. 9 indexed citations
6.
Huang, Yao, Adriano Mele, Zhengping Luo, et al.. (2022). Implementation of a Kalman filter-based eddy current estimator for the P-EFIT magnetic equilibrium reconstruction code. Nuclear Fusion. 62(8). 86010–86010. 5 indexed citations
7.
Notaro, Immacolata, Egidio D’Amato, Luciano Blasi, et al.. (2022). Trajectory control algorithms for the de-orbiting and Re-entry of the MISTRAL satellite. Acta Astronautica. 203. 392–406. 6 indexed citations
8.
Blasi, Luciano, Egidio D’Amato, M. Mattei, & Immacolata Notaro. (2022). UAV Path Planning in 3-D Constrained Environments Based on Layered Essential Visibility Graphs. IEEE Transactions on Aerospace and Electronic Systems. 59(3). 2359–2375. 24 indexed citations
9.
D’Amato, Egidio, et al.. (2022). Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs. Drones. 6(1). 18–18. 18 indexed citations
10.
Ambrosino, R., M. Ariola, C. Bachmann, et al.. (2021). Sweeping control performance on DEMO device. Fusion Engineering and Design. 171. 112640–112640. 7 indexed citations
11.
Blasi, Luciano, et al.. (2021). Modeling and Control of a Modular Iron Bird. Aerospace. 8(2). 39–39. 7 indexed citations
12.
D’Amato, Egidio, et al.. (2020). Scalable Distributed State Estimation in UTM Context. Sensors. 20(9). 2682–2682. 3 indexed citations
13.
Blasi, Luciano, Egidio D’Amato, M. Mattei, & Immacolata Notaro. (2020). Path Planning and Real-Time Collision Avoidance Based on the Essential Visibility Graph. Applied Sciences. 10(16). 5613–5613. 30 indexed citations
14.
D’Amato, Egidio, et al.. (2020). Decentralized Mesh-Based Model Predictive Control for Swarms of UAVs. Sensors. 20(15). 4324–4324. 31 indexed citations
15.
Cinque, Marcello, G. De Tommasi, P.C. de Vries, et al.. (2019). Management of the ITER PCS Design Using a System-Engineering Approach. IEEE Transactions on Plasma Science. 48(6). 1768–1778. 11 indexed citations
16.
D’Amato, Egidio, Immacolata Notaro, Luciano Blasi, & M. Mattei. (2019). Smooth Path planning for Fixed-Wing Aircraft in 3D Environment Using a Layered Essential Visibility Graph. CINECA IRIS Institutial research information system (Parthenope University of Naples). 9–18. 8 indexed citations
17.
Utoh, Hiroyasu, N. Asakura, Y. Sakamoto, et al.. (2018). Studies of the plasma vertical instability and its stabilized concepts in JA and EU broader approach, DEMO design activity. Fusion Engineering and Design. 136. 874–877. 4 indexed citations
18.
D’Amato, Egidio, Immacolata Notaro, M. Mattei, & Gaetano Tartaglione. (2015). Attitude and position estimation for an UAV swarm using consensus Kalman filtering. CINECA IRIS Institutial research information system (Parthenope University of Naples). 519–524. 19 indexed citations
19.
Belo, P., F. Romanelli, F. I. Parra, et al.. (2015). Coupled core/SOL modelling of fuelling requirements during the current ramp-up of ITER L-mode plasmas. CINECA IRIS Institutial research information system (Parthenope University of Naples). 1 indexed citations
20.
Villone, F., E. de la Luna, R. Albanese, et al.. (2007). Development of 20s long hybrid scenarios on JET. CINECA IRIS Institutial research information system (Parthenope University of Naples). 3 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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