Isel Grau

789 citations
38 papers · 413 · h-index 11

Impact in

Papers in

    • Cognitive Science and Mapping 16
    • Cognitive Computing and Networks 8
    • Neural Networks and Applications 7
    • Metaheuristic Optimization Algorithms Research 4
    • Explainable Artificial Intelligence (XAI) 3

Isel Grau

38 papers receiving 395 citations

Peers

Isel Grau
Comparison fields: 5 of 77
  • Artificial Intelligence 309
  • Management Science and Operations Research 98
  • Computational Theory and Mathematics 52
  • Health Informatics 2
  • Information Systems 29
Replace Jean Lieber with:
Jean Lieber France
Hossein Amirkhani Iran
Yuehan Wang China
Hossein Esfandiari United States
Loizos Michael Cyprus
Jamie Taylor United Kingdom
P. Rajarajeswari India
Sérgio Canuto Brazil
Farzan Soleymani Canada
Isel Grau relative to Jean Lieber France Jean Lieber's profile →
Citations per field
00.5×9.2×
Jean Lieber · 1×
Citations per year

Countries citing papers authored by Isel Grau

Since Specialization
Citations

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

Fields of papers citing papers by Isel Grau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Isel Grau, 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 Isel Grau Line = papers co-authored together Isel Grau 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 201861
2 201357
3 201536
4 201731
5 202222
6 201221
7 202220
8 201720
9 202019
10 201513
11 201511
12 202210
13 20208
14 20248
15 20228
16 20147
17 20137
18 20137
19 20205
20 20215

About Isel Grau

Isel Grau is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Management Science and Operations Research and Automotive Engineering, having authored 38 papers that have together received 413 indexed citations. Recurring topics across this work include Cognitive Science and Mapping (16 papers), Cognitive Computing and Networks (8 papers), Neural Networks and Applications (7 papers), Rough Sets and Fuzzy Logic (5 papers), Multi-Criteria Decision Making (4 papers), Metaheuristic Optimization Algorithms Research (4 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (309 citations), Management Science and Operations Research (98 citations), Computational Theory and Mathematics (52 citations), Health Informatics (2 citations) and Information Systems (29 citations). Isel Grau has collaborated with scholars based in Belgium, Cuba and Netherlands. Frequent co-authors include Gonzalo Nápoles, Rafael Bello, Koen Vanhoof, Maikel León, Ricardo Grau, Yamisleydi Salgueiro, Elpiniki I. Papageorgiou, Rafael Falcón, Ann Nowé and Witold Pedrycz. Their work appears in journals such as Knowledge-Based Systems, Neurocomputing, IEEE Transactions on Cybernetics, Neural Networks and Expert Systems with Applications.

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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