Marco Protasi

2.0k total citations · 1 hit paper
29 papers, 979 citations indexed

About

Marco Protasi is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Marco Protasi has authored 29 papers receiving a total of 979 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computational Theory and Mathematics, 15 papers in Artificial Intelligence and 8 papers in Computer Networks and Communications. Recurrent topics in Marco Protasi's work include Complexity and Algorithms in Graphs (11 papers), Advanced Graph Theory Research (7 papers) and Neural Networks and Applications (6 papers). Marco Protasi is often cited by papers focused on Complexity and Algorithms in Graphs (11 papers), Advanced Graph Theory Research (7 papers) and Neural Networks and Applications (6 papers). Marco Protasi collaborates with scholars based in Italy, Sweden and Czechia. Marco Protasi's co-authors include Giorgio Ausiello, Pierluigi Crescenzi, Alberto Marchetti-Spaccamela, Roberto Battiti, Giorgio Gambosi, Viggo Kann, Aurora D’Atri, Maurizio Talamo, Luděk Kučera and Marco Gori and has published in prestigious journals such as Theoretical Computer Science, Journal of Computer and System Sciences and Lecture notes in computer science.

In The Last Decade

Marco Protasi

27 papers receiving 891 citations

Hit Papers

Complexity and Approximation 1999 2026 2008 2017 1999 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Protasi Italy 8 500 373 300 175 84 29 979
Giorgio Gambosi Italy 13 322 0.6× 362 1.0× 226 0.8× 144 0.8× 59 0.7× 58 878
Kazuhisa Makino Japan 18 587 1.2× 329 0.9× 362 1.2× 109 0.6× 71 0.8× 146 1.1k
Elias Dahlhaus Germany 13 618 1.2× 287 0.8× 157 0.5× 114 0.7× 85 1.0× 45 937
Michael D. Grigoriadis United States 12 410 0.8× 295 0.8× 144 0.5× 207 1.2× 83 1.0× 27 831
Catherine C. McGeoch United States 16 254 0.5× 247 0.7× 478 1.6× 115 0.7× 28 0.3× 38 878
Friedhelm Meyer auf der Heide Germany 20 406 0.8× 725 1.9× 377 1.3× 83 0.5× 151 1.8× 116 1.3k
Fabrizio Grandoni Switzerland 19 870 1.7× 674 1.8× 222 0.7× 119 0.7× 93 1.1× 84 1.4k
Y. Bartal Israel 13 354 0.7× 654 1.8× 179 0.6× 107 0.6× 93 1.1× 24 938
Hadas Shachnai Israel 20 323 0.6× 827 2.2× 138 0.5× 279 1.6× 74 0.9× 85 1.2k
L. E. Trotter United States 12 704 1.4× 279 0.7× 139 0.5× 535 3.1× 132 1.6× 30 1.4k

Countries citing papers authored by Marco Protasi

Since Specialization
Citations

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

Fields of papers citing papers by Marco Protasi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Protasi

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Protasi. A scholar is included among the top collaborators of Marco Protasi 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 Marco Protasi. Marco Protasi 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.
Frasconi, Paolo, et al.. (2002). Suspiciousness of loading problems. Proceedings of International Conference on Neural Networks (ICNN'97). 2. 1240–1245. 4 indexed citations
3.
Battiti, Roberto & Marco Protasi. (1999). Reactive local search techniques for the maximum k-conjunctive constraint satisfaction problem (MAX-k-CCSP). Discrete Applied Mathematics. 96-97. 3–27. 2 indexed citations
4.
Battiti, Roberto & Marco Protasi. (1997). Solving MAX-SAT with nonoblivious functions and history-based heuristics. 649–667. 1 indexed citations
5.
Bianchini, Monica, et al.. (1997). Solving Linear Systems by a Neural Network Canonical Form of Efficient Gradient Descent. International Conference on Neural Information Processing. 1. 531–534. 2 indexed citations
6.
Gambosi, Giorgio, Marco Protasi, & Maurizio Talamo. (1997). Preserving approximation in the Min—Weighted Set Cover Problem. Discrete Applied Mathematics. 73(1). 13–22. 6 indexed citations
7.
Battiti, Roberto & Marco Protasi. (1997). Reactive Local Search for Maximum Clique.. Institutional Research Information System (Università degli Studi di Trento). 74–83. 2 indexed citations
8.
Protasi, Marco, et al.. (1996). Exploring and comparing the best "direct methods" for the efficient training of MLP-networks. IEEE Transactions on Neural Networks. 7(6). 1497–1502. 7 indexed citations
9.
Ausiello, Giorgio, Pierluigi Crescenzi, & Marco Protasi. (1995). Approximate solution of NP optimization problems. Theoretical Computer Science. 150(1). 1–55. 56 indexed citations
10.
Kučera, Luděk, Alberto Marchetti-Spaccamela, & Marco Protasi. (1994). On Learning Monotone DNF Formulae under Uniform Distributions. Information and Computation. 110(1). 84–95. 13 indexed citations
11.
Protasi, Marco, et al.. (1993). <title>Off-line and on-line backpropagation methods with various levels of redundancy</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1966. 296–302.
12.
Gambosi, Giorgio, Marco Protasi, & Maurizio Talamo. (1993). An efficient implicit data structure for relation testing and searching in partially ordered sets. BIT Numerical Mathematics. 33(1). 29–45. 3 indexed citations
13.
Ausiello, Giorgio & Marco Protasi. (1990). LIMITING POLYNOMIAL APPROXIMATION OF COMPLEXITY CLASSES. International Journal of Foundations of Computer Science. 1(2). 111–122.
14.
Protasi, Marco & Maurizio Talamo. (1989). On the number of arithmetical operations for finding Fibonacci numbers. Theoretical Computer Science. 64(1). 119–124. 3 indexed citations
15.
Marchetti-Spaccamela, Alberto & Marco Protasi. (1983). The largest tree in a random graph. Theoretical Computer Science. 23(3). 273–286. 5 indexed citations
16.
Ausiello, Giorgio & Marco Protasi. (1983). Proceedings of the 8th Colloquium on Trees in Algebra and Programming. 6 indexed citations
17.
Ausiello, Giorgio, Alessandro D’Atri, & Marco Protasi. (1981). Lattice Theoretic Ordering Properties for NP-Complete Optimization Problems. Fundamenta Informaticae. 4(1). 83–94. 5 indexed citations
18.
Marchetti-Spaccamela, Alberto, et al.. (1980). Toward a unified approach for the classification of NP-complete optimization problems. Theoretical Computer Science. 12(1). 83–96. 30 indexed citations
19.
Ausiello, Giorgio, Aurora D’Atri, & Marco Protasi. (1980). Structure preserving reductions among convex optimization problems. Journal of Computer and System Sciences. 21(1). 136–153. 128 indexed citations
20.
Ausiello, Giorgio, Alberto Marchetti-Spaccamela, & Marco Protasi. (1979). Combinatorial problems over power sets. CALCOLO. 16(4). 539–557. 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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