William Spataro

1.7k total citations
73 papers, 1.1k citations indexed

About

William Spataro is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Computational Mechanics. According to data from OpenAlex, William Spataro has authored 73 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Computational Theory and Mathematics, 26 papers in Computer Networks and Communications and 17 papers in Computational Mechanics. Recurrent topics in William Spataro's work include Cellular Automata and Applications (49 papers), Advanced Data Storage Technologies (21 papers) and Lattice Boltzmann Simulation Studies (14 papers). William Spataro is often cited by papers focused on Cellular Automata and Applications (49 papers), Advanced Data Storage Technologies (21 papers) and Lattice Boltzmann Simulation Studies (14 papers). William Spataro collaborates with scholars based in Italy, United Kingdom and Greece. William Spataro's co-authors include Rocco Rongo, Salvatore Di Gregorio, Donato D’Ambrosio, Gino Mirocle Crisci, Giuseppe A. Trunfio, Giulio Iovine, Maria Vittoria Avolio, Valeria Lupiano, Domenico Talia and Giandomenico Spezzano and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Geomorphology and Geological Society London Special Publications.

In The Last Decade

William Spataro

68 papers receiving 998 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William Spataro Italy 19 457 324 272 196 175 73 1.1k
Salvatore Di Gregorio Italy 22 496 1.1× 485 1.5× 250 0.9× 189 1.0× 303 1.7× 72 1.4k
Rocco Rongo Italy 17 323 0.7× 244 0.8× 193 0.7× 129 0.7× 133 0.8× 51 783
Donato D’Ambrosio Italy 16 288 0.6× 252 0.8× 157 0.6× 151 0.8× 170 1.0× 49 784
David Michéa France 11 50 0.1× 82 0.3× 65 0.2× 161 0.8× 50 0.3× 20 789
B. S. Daya Sagar India 15 51 0.1× 104 0.3× 71 0.3× 20 0.1× 81 0.5× 83 804
Guillaume Caumon France 26 57 0.1× 47 0.1× 59 0.2× 117 0.6× 23 0.1× 116 2.2k
Jérôme Leroux France 10 133 0.3× 206 0.6× 22 0.1× 19 0.1× 73 0.4× 34 1.2k
Ian Briggs United States 7 128 0.3× 28 0.1× 34 0.1× 49 0.3× 22 0.1× 14 982
Martin Isenburg United States 26 61 0.1× 14 0.0× 326 1.2× 738 3.8× 128 0.7× 57 2.4k
Ana Cortés Spain 16 29 0.1× 157 0.5× 138 0.5× 26 0.1× 397 2.3× 84 767

Countries citing papers authored by William Spataro

Since Specialization
Citations

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

Fields of papers citing papers by William Spataro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Spataro

This figure shows the co-authorship network connecting the top 25 collaborators of William Spataro. A scholar is included among the top collaborators of William Spataro 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 William Spataro. William Spataro 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.
Colao, Vittorio, et al.. (2025). An optimizer derived from Halpern’s method for enhanced neural network convergence and reduced carbon emissions. Journal of Intelligent Information Systems. 64(1). 77–96.
2.
Giordano, Andrea, et al.. (2023). Tailoring load balancing of cellular automata parallel execution to the case of a two-dimensional partitioned domain. The Journal of Supercomputing. 79(8). 9273–9287. 1 indexed citations
3.
Spataro, William, et al.. (2022). Towards efficient GPGPU Cellular Automata model implementation using persistent active cells. Journal of Computational Science. 59. 101538–101538. 5 indexed citations
4.
Spataro, William, et al.. (2018). A first multi-GPU/multi-node implementation of the open computing abstraction layer. Journal of Computational Science. 32. 115–124. 11 indexed citations
5.
Spataro, William, et al.. (2015). CUDA Dynamic Active Thread List Strategy to Accelerate Debris Flow Simulations. 316–320. 4 indexed citations
6.
D’Ambrosio, Donato, et al.. (2013). Non-uniform grid-based susceptibility evaluations: an application to flow-type phenomena at Mount Etna. Bollettino Della Societa Geologica Italiana. 1 indexed citations
7.
Spataro, William, et al.. (2010). A Multithread Scientific Library for Complex Systems.. 47–54. 1 indexed citations
8.
Avolio, Maria Vittoria, Salvatore Di Gregorio, Valeria Lupiano, Paolo Mazzanti, & William Spataro. (2010). Application Context of the SCIDDICA Model Family for Simulations of Flow-Like Landslides.. 40–46. 2 indexed citations
9.
Sirakoulis, Georgios Ch., Ioannis G. Karafyllidis, & William Spataro. (2009). A Computational Intelligent Oxidation Process Model and Its VLSI Implementation.. 462. 329–335. 3 indexed citations
10.
D’Ambrosio, Donato, et al.. (2009). A Dynamically Load Balanced Cellular Automata Library for Scientific Computing.. 69(6). 322–328. 2 indexed citations
11.
Rongo, Rocco, William Spataro, Donato D’Ambrosio, et al.. (2008). Lava Flow Hazard Evaluation Through Cellular Automata and Genetic Algorithms: an Application to Mt Etna Volcano. Fundamenta Informaticae. 87(2). 247–267. 26 indexed citations
12.
D’Ambrosio, Donato, et al.. (2008). An Example of Web Application for Scientific Simulation. Summer Computer Simulation Conference.
13.
D’Ambrosio, Donato, et al.. (2008). Modeling Complex Natural Phenomena with the libAuToti Cellular Automata Library: An example of Application to Lava Flows Simulation.. Parallel and Distributed Processing Techniques and Applications. 277–283. 8 indexed citations
14.
Spataro, William, Donato D’Ambrosio, Maria Vittoria Avolio, Rocco Rongo, & Salvatore Di Gregorio. (2008). Complex Systems Modeling with Cellular Automata and Genetic Algorithms: An Application to Lava Flows.. 35(31). 44–50. 3 indexed citations
15.
D’Ambrosio, Donato, Giulio Iovine, William Spataro, & Hideaki Miyamoto. (2006). A macroscopic collisional model for debris-flows simulation. Environmental Modelling & Software. 22(10). 1417–1436. 43 indexed citations
16.
D’Ambrosio, Donato, William Spataro, Salvatore Di Gregorio, Gino Mirocle Crisci, & Rocco Rongo. (2005). Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows. 28(2). 115. 5 indexed citations
17.
Gregorio, Salvatore Di, et al.. (1997). SCIDDICA-3: a cellular automata model for landslide simulation. IOS Press eBooks. 324–330. 7 indexed citations
18.
Gregorio, Salvatore Di, Rocco Rongo, Roberto Serra, et al.. (1996). Parallel Simulation of Soil Contamination by Cellular Automata.. 295–297.
19.
Gregorio, Salvatore Di, Demetrio Carmine Festa, Rocco Rongo, et al.. (1995). A Microscopic Freeway Traffic Simulator on a Highly Parallel System.. 69–76. 7 indexed citations
20.
Gregorio, Salvatore Di, et al.. (1970). A Parallel Cellular Simulator For Bioremediation Of Contaminated Soils. WIT Transactions on Ecology and the Environment. 16. 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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