Daniel Burbano

554 citations
30 papers · 411 · h-index 10

Impact in

Papers in

Daniel Burbano

28 papers receiving 405 citations

Peers

Daniel Burbano
Comparison fields: 5 of 67
  • Computer Networks and Communications 255
  • Statistical and Nonlinear Physics 83
  • Control and Systems Engineering 105
  • Nature and Landscape Conservation 20
  • Behavioral Neuroscience 5
Replace Piotr Kowalczyk with:
Piotr Kowalczyk United Kingdom
Zahra Aminzare United States
Jonatán Peña Ramírez Mexico
Xiaole Liu China
Zigen Song China
Takayuki Niizato Japan
Yara Khaluf Belgium
Asja Jelić Italy
Jinming Luo China
Xiaokang Lei China
Daniel Burbano relative to Piotr Kowalczyk United Kingdom Piotr Kowalczyk's profile →
Citations per field
00.5×6.7×
Piotr Kowalczyk · 1×
Citations per year

Countries citing papers authored by Daniel Burbano

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Burbano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Daniel Burbano, 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 Daniel Burbano Line = papers co-authored together Daniel Burbano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201679
2 201473
3 201542
4 201931
5 201829
6 201214
7 201414
8 202213
9 201912
10 201710
11 20219
12 20219
13 20209
14 20199
15 20198
16 19998
17 20167
18 20215
19 20165
20 20234

About Daniel Burbano

Daniel Burbano is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Cell Biology, Control and Systems Engineering and Nature and Landscape Conservation, having authored 30 papers that have together received 411 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (11 papers), Neural Networks Stability and Synchronization (11 papers), Distributed Control Multi-Agent Systems (10 papers), Zebrafish Biomedical Research Applications (6 papers), Advanced DC-DC Converters (4 papers), Animal Behavior and Reproduction (4 papers), Fish Ecology and Management Studies (4 papers) and Microgrid Control and Optimization (3 papers). The work is most often cited by research in Computer Networks and Communications (255 citations), Statistical and Nonlinear Physics (83 citations), Control and Systems Engineering (105 citations), Nature and Landscape Conservation (20 citations) and Behavioral Neuroscience (5 citations). Daniel Burbano has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Mario di Bernardo, Maurizio Porfiri, Fabiola Angulo, Giovanni Russo, Randy A. Freeman, Kevin Lynch, M. de Magistris, Carlo Petrarca, S. H. Chung and Richard D. Braatz. Their work appears in journals such as IEEE Transactions on Control of Network Systems, Journal of Theoretical Biology, Chaos An Interdisciplinary Journal of Nonlinear Science, Behavioural Processes and Automatica.

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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