Senén Barro

6.4k citations
136 papers · 4.4k · 2 hit papers · h-index 30

Impact in

Papers in

Senén Barro

130 papers receiving 4.2k citations

Senén Barro's Hit Papers

AI literacy in K-12: a systematic literature review 2023 · 298 citations
2980+4+8Years since publication50010001.5k

Peers

Senén Barro
Comparison fields: 5 of 202
  • Artificial Intelligence 1.6k
  • Computer Science Applications 259
  • Health Informatics 59
  • Signal Processing 342
  • Cardiology and Cardiovascular Medicine 452
Replace S. S. Iyengar with:
S. S. Iyengar United States
Manuel Graña Spain
Jesse Davis Belgium
Jennifer Dy United States
John Yearwood Australia
Yike Guo United Kingdom
Aidong Zhang United States
Aytuğ Onan Türkiye
Simon Fong Macao
Dale Schuurmans Canada
Senén Barro relative to S. S. Iyengar United States S. S. Iyengar's profile →
Citations per field
00.5×3.4×
S. S. Iyengar · 1×
Citations per year

Countries citing papers authored by Senén Barro

Since Specialization
Citations

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

Fields of papers citing papers by Senén Barro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Senén Barro, 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 Senén Barro Line = papers co-authored together Senén Barro links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 136 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Do we need hundreds of classifiers to solve real world classification problems
Hit paper breakdown →
20141731
2
AI literacy in K-12: a systematic literature review
Hit paper breakdown →
2023298
3 2018252
4 1989129
5 199493
6 200290
7 200080
8 199777
9 202274
10 199464
11 201864
12
People and machines: Partners in innovation
201962
13 201461
14 200654
15 199852
16 201552
17 200950
18 199947
19 201343
20 202143

About Senén Barro

Senén Barro is a scholar working on Artificial Intelligence, Computer Networks and Communications, Cardiology and Cardiovascular Medicine, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 136 papers that have together received 4.4k indexed citations. Recurring topics across this work include Constraint Satisfaction and Optimization (17 papers), ECG Monitoring and Analysis (17 papers), AI-based Problem Solving and Planning (16 papers), Fuzzy Logic and Control Systems (15 papers), Rough Sets and Fuzzy Logic (14 papers), Neural Networks and Applications (14 papers), Data Management and Algorithms (11 papers) and Semantic Web and Ontologies (11 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computer Science Applications (259 citations), Health Informatics (59 citations), Signal Processing (342 citations) and Cardiology and Cardiovascular Medicine (452 citations). Senén Barro has collaborated with scholars based in Spain, Chile and Portugal. Frequent co-authors include Manuel Fernández-Delgado, Eva Cernadas, Alberto Bugarín, Roberto Iglesias, José Mira, R. Ruı́z, Carlos V. Regueiro, J. Presedo, Manisha Sirsat and Xosé A. Vila. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Neural Computing and Applications, Artificial Intelligence in Medicine and Neural Networks.

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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