L. Anderlini

35.0k total citations
27 papers, 130 citations indexed

About

L. Anderlini is a scholar working on Nuclear and High Energy Physics, Radiation and Artificial Intelligence. According to data from OpenAlex, L. Anderlini has authored 27 papers receiving a total of 130 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Nuclear and High Energy Physics, 5 papers in Radiation and 5 papers in Artificial Intelligence. Recurrent topics in L. Anderlini's work include Particle Detector Development and Performance (19 papers), Particle physics theoretical and experimental studies (16 papers) and High-Energy Particle Collisions Research (5 papers). L. Anderlini is often cited by papers focused on Particle Detector Development and Performance (19 papers), Particle physics theoretical and experimental studies (16 papers) and High-Energy Particle Collisions Research (5 papers). L. Anderlini collaborates with scholars based in Italy, Russia and Switzerland. L. Anderlini's co-authors include A. Cerri, Jure Zupan, Wolfgang Altmannshofer, S. Akar, S. Malvezzi, B. C. Allanach, Jorge Martin Camalich, V. V. Gligorov, J. Alimena and M. Aresti and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Geophysical Journal International.

In The Last Decade

L. Anderlini

24 papers receiving 128 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. Anderlini Italy 5 114 27 22 13 8 27 130
L. Fanò Italy 7 73 0.6× 19 0.7× 31 1.4× 12 0.9× 5 0.6× 27 126
D. Epifanov Russia 7 97 0.9× 28 1.0× 7 0.3× 6 0.5× 7 0.9× 17 113
X. C. Lou China 6 90 0.8× 22 0.8× 23 1.0× 4 0.3× 3 0.4× 23 109
L. Silvestris Italy 5 121 1.1× 53 2.0× 36 1.6× 7 0.5× 6 0.8× 11 158
Jingkai Xia China 6 49 0.4× 36 1.3× 28 1.3× 4 0.3× 4 0.5× 21 100
Y. Usov Russia 6 108 0.9× 69 2.6× 8 0.4× 7 0.5× 5 0.6× 35 134
Steffen Hauf Germany 5 32 0.3× 50 1.9× 16 0.7× 9 0.7× 3 0.4× 23 71
R. F. Schwitters United States 7 64 0.6× 40 1.5× 15 0.7× 6 0.5× 5 0.6× 16 103
B. Schwingenheuer Germany 6 84 0.7× 36 1.3× 7 0.3× 4 0.3× 4 0.5× 16 100
P. Martinengo Switzerland 6 72 0.6× 55 2.0× 35 1.6× 3 0.2× 4 0.5× 10 81

Countries citing papers authored by L. Anderlini

Since Specialization
Citations

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

Fields of papers citing papers by L. Anderlini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. Anderlini

This figure shows the co-authorship network connecting the top 25 collaborators of L. Anderlini. A scholar is included among the top collaborators of L. Anderlini 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 L. Anderlini. L. Anderlini 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.
Anderlini, L., et al.. (2025). Interseismic coupling degree of Serre and Cittanova faults surface in Southern Calabria, (Italy): new constraints from geodetic data observations. Geophysical Journal International. 241(2). 954–970. 1 indexed citations
2.
Loi, A., M. J. Addison, L. Anderlini, et al.. (2024). A prototype 4D-tracking demonstrator based on the TimeSPOT developments. Journal of Instrumentation. 19(2). C02069–C02069.
3.
Anderlini, L., M. Barbetti, Д. Деркач, et al.. (2023). Towards Reliable Neural Generative Modeling of Detectors. Journal of Physics Conference Series. 2438(1). 12130–12130. 2 indexed citations
4.
Mariani, S., L. Anderlini, P. Di Nezza, et al.. (2023). A neural-network-defined Gaussian mixture model for particle identification applied to the LHCb fixed-target programme. Journal of Physics Conference Series. 2438(1). 12107–12107. 1 indexed citations
5.
Anderlini, L., et al.. (2023). Generative models uncertainty estimation. Journal of Physics Conference Series. 2438(1). 12088–12088. 2 indexed citations
6.
Anderlini, L., M. Barbetti, G. Corti, et al.. (2022). Lamarr: the ultra-fast simulation option for the LHCb experiment. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022). 233–233. 1 indexed citations
7.
Anderlini, L., Marco Bellini, V. Cindro, et al.. (2022). A Study of the Radiation Tolerance and Timing Properties of 3D Diamond Detectors. Sensors. 22(22). 8722–8722. 3 indexed citations
8.
Anderlini, L., Marco Bellini, C. Corsi, et al.. (2022). A 4D diamond detector for HL-LHC and beyond. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1040. 167230–167230. 2 indexed citations
9.
Anderlini, L., Marco Bellini, C. Corsi, et al.. (2022). Construction and characterisation of high time resolution 3D diamond pixel detectors. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1046. 167692–167692. 1 indexed citations
10.
Ratnikov, F., A. Maevskiy, Д. Деркач, et al.. (2022). A full detector description using neural network driven simulation. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1046. 167591–167591. 1 indexed citations
11.
Anderlini, L., et al.. (2022). Machine learning approaches to the QCD transition. Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021). 2 indexed citations
12.
Lai, A., L. Anderlini, M. Aresti, et al.. (2020). First results of the TIMESPOT project on developments on fast sensors for future vertex detectors. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 981. 164491–164491. 24 indexed citations
13.
Anderlini, L., F. Archilli, A. Cardini, et al.. (2020). Muon identification for LHCb Run 3. Journal of Instrumentation. 15(12). T12005–T12005. 2 indexed citations
14.
Anderlini, L., M. Anelli, F. Archilli, et al.. (2019). Long-term operation of the multi-wire-proportional-chambers of the LHCb muon system. Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona). 6 indexed citations
15.
Cerri, A., V. V. Gligorov, S. Malvezzi, et al.. (2018). Report from Working Group 4. 7. 867–1158. 46 indexed citations
16.
Beteta, C. Abellán, B. Adeva, M. Adinolfi, et al.. (2018). LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 14 indexed citations
17.
Anderlini, L.. (2017). Physics programme in fixed-target mode with the LHCb experiment at CERN. CERN Document Server (European Organization for Nuclear Research). 152–152. 1 indexed citations
18.
Anderlini, L., A. Contu, Y. Zhang, et al.. (2016). The PIDCalib package. CERN Bulletin. 8 indexed citations
19.
Anderlini, L., et al.. (2016). Computing strategy for PID calibration samples for LHCb Run 2. CERN Bulletin.
20.
Lupton, O., V. V. Gligorov, L. Anderlini, & B. Sciascia. (2016). Calibration samples for particle identification at LHCb in Run 2. CERN Bulletin. 2 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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