László Szeidl

1.6k total citations · 1 hit paper
40 papers, 1.0k citations indexed

About

László Szeidl is a scholar working on Computational Mathematics, Control and Systems Engineering and Nature and Landscape Conservation. According to data from OpenAlex, László Szeidl has authored 40 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mathematics, 6 papers in Control and Systems Engineering and 5 papers in Nature and Landscape Conservation. Recurrent topics in László Szeidl's work include Tensor decomposition and applications (11 papers), Ecology and Vegetation Dynamics Studies (5 papers) and Control Systems and Identification (5 papers). László Szeidl is often cited by papers focused on Tensor decomposition and applications (11 papers), Ecology and Vegetation Dynamics Studies (5 papers) and Control Systems and Identification (5 papers). László Szeidl collaborates with scholars based in Hungary, Italy and Russia. László Szeidl's co-authors include Peter Racsko, Mikhail A. Semenov, Carlo Ricotta, Péter Várlaki, Péter Bárányi, Miklós Telek, András Rövid, János Mika, János Izsák and Yeung Yam and has published in prestigious journals such as Ecological Indicators, Ecological Modelling and Methods in Ecology and Evolution.

In The Last Decade

László Szeidl

34 papers receiving 939 citations

Hit Papers

A serial approach to local stochastic weather models 1991 2026 2002 2014 1991 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A serial approach to local stochastic weather models
    1991 394 citations László Szeidl et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
László Szeidl Hungary 13 392 200 168 144 142 40 1.0k
Hervé Cardot France 23 167 0.4× 33 0.2× 39 0.2× 79 0.5× 20 0.1× 65 2.0k
Dong Chen China 21 528 1.3× 39 0.2× 68 0.4× 352 2.4× 84 0.6× 104 1.9k
Zhi Geng China 20 123 0.3× 61 0.3× 126 0.8× 41 0.3× 59 0.4× 85 1.4k
R. Shrestha United States 14 315 0.8× 36 0.2× 127 0.8× 144 1.0× 157 1.1× 22 952
Andreas Dittrich Germany 18 760 1.9× 64 0.3× 156 0.9× 66 0.5× 103 0.7× 48 1.8k
Theodoros Damoulas United Kingdom 16 232 0.6× 44 0.2× 87 0.5× 451 3.1× 11 0.1× 37 1.3k
Dino Ienco France 22 328 0.8× 17 0.1× 45 0.3× 357 2.5× 47 0.3× 103 2.0k
Zhongyi Sun China 16 708 1.8× 91 0.5× 60 0.4× 243 1.7× 156 1.1× 76 1.4k
Ke Guo China 14 51 0.1× 44 0.2× 86 0.5× 50 0.3× 6 0.0× 46 611
Guoqing Liu China 16 57 0.1× 42 0.2× 27 0.2× 60 0.4× 87 0.6× 114 923

Countries citing papers authored by László Szeidl

Since Specialization
Citations

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

Fields of papers citing papers by László Szeidl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of László Szeidl

This figure shows the co-authorship network connecting the top 25 collaborators of László Szeidl. A scholar is included among the top collaborators of László Szeidl 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 László Szeidl. László Szeidl 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.
Ricotta, Carlo, László Szeidl, & Sandrine Pavoine. (2021). Towards a unifying framework for diversity and dissimilarity coefficients. Ecological Indicators. 129. 107971–107971. 15 indexed citations
2.
Izsák, János, et al.. (2018). Population Dynamic Models Leading to Logarithmic and Yule Distribution. Acta Polytechnica Hungarica. 15(1). 4 indexed citations
3.
Rövid, András, László Szeidl, & Péter Várlaki. (2014). Integral Operators in Relation to the HOSVD‐Based Canonical Form. Asian Journal of Control. 17(2). 459–466. 3 indexed citations
4.
Fodor, Nándor, et al.. (2013). Applications of the MVWG Multivariable Stochastic Weather Generator. The Scientific World JOURNAL. 2013(1). 571367–571367. 7 indexed citations
5.
Rövid, András, et al.. (2013). HOSVD-wavelet based framework for multidimensional data approximation. 9. 29–33. 4 indexed citations
6.
Rövid, András, Péter Várlaki, & László Szeidl. (2011). HOSVD based data representation and LPV model complexity reduction. 164–169. 2 indexed citations
7.
Ricotta, Carlo, László Szeidl, Marco Moretti, & C. Blasi. (2011). A partial ordering approach for functional diversity. Theoretical Population Biology. 80(2). 114–120. 3 indexed citations
8.
Rövid, András, et al.. (2011). HOSVD based image processing techniques. International Conference on Artificial Intelligence. 101(8). 297–302. 10 indexed citations
9.
Rövid, András, et al.. (2010). Indoor real-time 3D reconstruction of crash-tested car cabins. 3. 257–261. 1 indexed citations
10.
Fodor, Nándor, et al.. (2010). MV-WG: a new multi-variable weather generator. Meteorology and Atmospheric Physics. 107(3-4). 91–101. 10 indexed citations
11.
Ricotta, Carlo & László Szeidl. (2009). Diversity partitioning of Rao’s quadratic entropy. Theoretical Population Biology. 76(4). 299–302. 102 indexed citations
12.
Szeidl, László & Péter Várlaki. (2009). HOSVD Based Canonical Form for Polytopic Models of Dynamic Systems. Journal of Advanced Computational Intelligence and Intelligent Informatics. 13(1). 52–60. 52 indexed citations
13.
14.
Szeidl, László, Péter Bárányi, Zoltán Petres, & Péter Várlaki. (2007). Numerical Reconstruction of the HOSVD Based Canonical Form of Polytopic Dynamic Models. 1. 111–116. 35 indexed citations
15.
Ricotta, Carlo & László Szeidl. (2006). Towards a unifying approach to diversity measures: Bridging the gap between the Shannon entropy and Rao's quadratic index. Theoretical Population Biology. 70(3). 237–243. 130 indexed citations
16.
Izsák, János & László Szeidl. (2002). Quadratic diversity: Its maximization can reduce the richness of species. Environmental and Ecological Statistics. 9(4). 423–430. 26 indexed citations
17.
Szeidl, László & В. М. Золотарев. (1998). The central limit theorem without the condition of independence. Journal of Mathematical Sciences. 91(3). 3002–3004.
18.
Michelberger, Pál, et al.. (1987). ASSESSMENT OF STRESS STATISTICS FOR COMMERCIAL VEHICLE FRAMES. Periodica Polytechnica Transportation Engineering. 15(1). 3–14. 1 indexed citations
19.
Keresztes, Attila, et al.. (1982). Mathetical model of the load and stress statistics of vehicle structures. Applied Mathematical Modelling. 6(2). 92–96. 1 indexed citations
20.
Keresztes, Attila, et al.. (1981). PRELIMINARY LOAD ANALYSIS OF COMMERCIAL VEHICLES. Periodica Polytechnica Transportation Engineering. 9(2). 151–163. 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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