Eva Riccomagno

1.0k total citations
44 papers, 532 citations indexed

About

Eva Riccomagno is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Eva Riccomagno has authored 44 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 9 papers in Management Science and Operations Research and 7 papers in Artificial Intelligence. Recurrent topics in Eva Riccomagno's work include Polynomial and algebraic computation (9 papers), Optimal Experimental Design Methods (7 papers) and Bayesian Modeling and Causal Inference (5 papers). Eva Riccomagno is often cited by papers focused on Polynomial and algebraic computation (9 papers), Optimal Experimental Design Methods (7 papers) and Bayesian Modeling and Causal Inference (5 papers). Eva Riccomagno collaborates with scholars based in Italy, United Kingdom and Germany. Eva Riccomagno's co-authors include Henry P. Wynn, Ron Bates, R. Buck, Michael J. Chappell, Giovanni Pistone, Jim Q. Smith, Rainer Schwabe, Lisa J. White, Gherardo Varando and Marco Bibuli and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

Eva Riccomagno

40 papers receiving 489 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eva Riccomagno Italy 12 207 175 113 87 56 44 532
Andrey Pepelyshev Germany 19 393 1.9× 482 2.8× 71 0.6× 197 2.3× 49 0.9× 68 790
Svetoslav Markov Bulgaria 14 182 0.9× 106 0.6× 120 1.1× 48 0.6× 105 1.9× 80 829
Leonid G. Khachiyan United States 8 203 1.0× 44 0.3× 104 0.9× 25 0.3× 47 0.8× 8 506
Mingyao Ai China 13 218 1.1× 323 1.8× 98 0.9× 68 0.8× 14 0.3× 64 558
Simon Mak United States 10 97 0.5× 63 0.4× 104 0.9× 81 0.9× 24 0.4× 31 328
Javier Yáñez Spain 16 135 0.7× 192 1.1× 180 1.6× 29 0.3× 39 0.7× 48 607
Pham Dinh Tao France 10 213 1.0× 58 0.3× 82 0.7× 13 0.1× 69 1.2× 17 686
Gerardo Rubino France 9 59 0.3× 115 0.7× 44 0.4× 108 1.2× 27 0.5× 18 474
Shao-Po Wu United States 4 99 0.5× 32 0.2× 59 0.5× 38 0.4× 153 2.7× 5 595
Nikolay Kyurkchiev Bulgaria 11 100 0.5× 47 0.3× 99 0.9× 40 0.5× 19 0.3× 113 634

Countries citing papers authored by Eva Riccomagno

Since Specialization
Citations

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

Fields of papers citing papers by Eva Riccomagno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eva Riccomagno

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Riccomagno. A scholar is included among the top collaborators of Eva Riccomagno 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 Eva Riccomagno. Eva Riccomagno 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.
Béjaoui, Béchir, Ennio Ottaviani, Sihem Benabdallah, et al.. (2024). Performance of different modeling techniques in testing the impact of environmental variables on eel landing in Ichkeul Lake, a RAMSAR Wetland and UNESCO biosphere reserve. Regional Studies in Marine Science. 77. 103587–103587. 1 indexed citations
2.
Ugolini, Alessandro, et al.. (2023). Probabilistic graphical modelling of early childhood caries development. PLoS ONE. 18(10). e0293221–e0293221. 2 indexed citations
3.
Rapallo, Fabio, et al.. (2022). Generation of all randomizations using circuits. Annals of the Institute of Statistical Mathematics. 75(4). 683–704. 1 indexed citations
4.
Riccomagno, Eva, et al.. (2022). The R Package stagedtrees for Structural Learning of Stratified Staged Trees. Journal of Statistical Software. 102(6). 18 indexed citations
5.
Barani, Simone, Eva Riccomagno, Daniele Spallarossa, et al.. (2018). Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability. Scientific Reports. 8(1). 5326–5326. 14 indexed citations
6.
Bigatti, Anna Maria, et al.. (2018). Discovery of statistical equivalence classes using computer algebra. International Journal of Approximate Reasoning. 95. 167–184. 11 indexed citations
7.
Riccomagno, Eva, et al.. (2017). Optimization of Anodic Porous Alumina Fabricated from Commercial Aluminum Food Foils: A Statistical Approach. Materials. 10(4). 417–417. 5 indexed citations
8.
Riccomagno, Eva, et al.. (2017). Passive and Active Observation: Experimental Design Issues in Big Data. arXiv (Cornell University). 1 indexed citations
9.
Riccomagno, Eva, et al.. (2015). A topological study of repetitive co-activation networks inin vitrocortical assemblies. Physical Biology. 12(1). 16007–16007. 12 indexed citations
10.
Riccomagno, Eva, et al.. (2015). The precision space of interpolatory cubature formulæ. CINECA IRIS Institutial Research Information System (University of Genoa). 6(1).
11.
Kuhnt, Sonja, et al.. (2015). Numerical algebraic fan of a design for statistical model building. Statistica Sinica. 1 indexed citations
12.
Kuhnt, Sonja, et al.. (2014). Modeling of a Thermal Spraying Process by Gaussian Chain Graphs. Quality Technology & Quantitative Management. 11(1). 85–98. 6 indexed citations
13.
Smith, Jim Q., et al.. (2010). Causal analysis with Chain Event Graphs. Artificial Intelligence. 174(12-13). 889–909. 34 indexed citations
14.
Lee, Jon, et al.. (2008). Nonlinear Matroid Optimization and Experimental Design. SIAM Journal on Discrete Mathematics. 22(3). 901–919. 17 indexed citations
15.
Notari, Roberto, et al.. (2007). On the description and identifiability analysis of experiments with mixtures. Statistica Sinica. 17(4). 1417–1440. 2 indexed citations
16.
Riccomagno, Eva, et al.. (2004). Structural identifiability analysis of some highly structured families of statespace models using differential algebra. Journal of Mathematical Biology. 49(5). 433–454. 17 indexed citations
17.
18.
Riccomagno, Eva, et al.. (2001). Differential algebra methods for the study of the structural identifiability of rational function state-space models in the biosciences. Mathematical Biosciences. 174(1). 1–26. 79 indexed citations
19.
Pistone, Giovanni, et al.. (1999). The fan of an experimental design. CINECA IRIS Institutial research information system (University of Pisa). 99038. 7 indexed citations
20.
Riccomagno, Eva, et al.. (1998). An Algebraic Computational Approach to the Identifiability of Fourier Models. Journal of Symbolic Computation. 26(2). 245–260. 5 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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