Martín Pedemonte

612 citations
38 papers · 380 · h-index 9

Impact in

Papers in

Martín Pedemonte

34 papers receiving 361 citations

Peers

Martín Pedemonte
Comparison fields: 5 of 73
  • Industrial and Manufacturing Engineering 71
  • Artificial Intelligence 156
  • Computational Theory and Mathematics 61
  • Software 13
  • Hardware and Architecture 22
Replace Aleksander Byrski with:
Aleksander Byrski Poland
Jácint Szabó Hungary
Jongho Nang South Korea
Esther Villar-Rodríguez Spain
Tung Khac Truong Vietnam
Chengtian Ouyang China
John Galletly United Kingdom
Aziz Ouaarab Morocco
A. J. Umbarkar India
José M. Troya Spain
Martín Pedemonte relative to Aleksander Byrski Poland Aleksander Byrski's profile →
Citations per field
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Citations per year

Countries citing papers authored by Martín Pedemonte

Since Specialization
Citations

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

Fields of papers citing papers by Martín Pedemonte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Martín Pedemonte, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Martín Pedemonte Line = papers co-authored together Martín Pedemonte links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011145
2 201540
3 202221
4 202018
5 201017
6 201114
7 201314
8 201012
9 201112
10 20208
11 20128
12 20147
13 20167
14 20187
15 20196
16 20246
17 20145
18 20165
19 20114
20 20234

About Martín Pedemonte

Martín Pedemonte is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Hardware and Architecture, Control and Systems Engineering and Computer Networks and Communications, having authored 38 papers that have together received 380 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (12 papers), Evolutionary Algorithms and Applications (10 papers), Parallel Computing and Optimization Techniques (6 papers), Advanced Multi-Objective Optimization Algorithms (5 papers), Advanced Control Systems Optimization (4 papers), Matrix Theory and Algorithms (4 papers), Distributed and Parallel Computing Systems (4 papers) and Vehicle Routing Optimization Methods (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (71 citations), Artificial Intelligence (156 citations), Computational Theory and Mathematics (61 citations), Software (13 citations) and Hardware and Architecture (22 citations). Martín Pedemonte has collaborated with scholars based in Uruguay, Spain and United States. Frequent co-authors include Héctor Cancela, Sergio Nesmachnow, Pablo Ezzatti, Francisco Luna, Ana I. Torres, Enrique Alba, A. Calvo Hernández, A. Medina, Pedro Curto-Risso and P. Chilibroste. Their work appears in journals such as Agricultural Systems, Applied Soft Computing, IEEE Access, Computers & Chemical Engineering and Current Opinion in Green and Sustainable Chemistry.

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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