David Sanz

1.1k citations
14 papers · 758 indexed · h-index 8
Topics
Robotics and Sensor-Based Localization (4 papers)Robotic Path Planning Algorithms (4 papers)Modular Robots and Swarm Intelligence (2 papers)
Partner nations
SpainColombiaFrance

In The Last Decade

David Sanz

14 papers receiving 728 citations

Peers

David Sanz
Comparison fields: 5 of 83
  • Aerospace Engineering 362
  • Computer Vision and Pattern Recognition 297
  • Computer Networks and Communications 169
  • Plant Science 125
  • Control and Systems Engineering 89
Replace Pratap Tokekar with:
Pratap Tokekar United States
Joshua Vander Hook United States
Florin Stoican Romania
Matthew Coombes United Kingdom
Nawaf Qasem Hamood Othman China
Dimosthenis C. Tsouros Greece
Tauã M. Cabreira Brazil
Riccardo Polvara United Kingdom
Emili Hernández Spain
Sean Campbell Ireland
David Sanz relative to Pratap Tokekar United States Pratap Tokekar's profile →
Citations per field
00.5×3.8×
Pratap Tokekar · 1×
Citations per year

Countries citing papers authored by David Sanz

Since Specialization
Citations

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

Fields of papers citing papers by David Sanz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Sanz

This figure shows the co-authorship network connecting the top 25 collaborators of David Sanz. A scholar is included among the top collaborators of David Sanz 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 David Sanz. David Sanz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 6
2 134
3 13
4 4
5 32
6 7
7 3
8 89
9 70
10 130
11 235
12 1
13 2
14 32

About David Sanz

David Sanz is a scholar working on Conservation, Safety, Risk, Reliability and Quality and Aerospace Engineering, having authored 14 papers that have together received 758 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Robotic Path Planning Algorithms (4 papers) and Modular Robots and Swarm Intelligence (2 papers). The work is most often cited by research in Aerospace Engineering (362 citations), Computer Vision and Pattern Recognition (297 citations) and Computer Networks and Communications (169 citations). David Sanz has collaborated with scholars based in Spain, Colombia and France. Frequent co-authors include Antonio Barrientos, Jaime del Cerro, João Valente, Cláudio Rossi, Julian D. Colorado, A. Martínez, Juan Jesús Roldán, Ángela Ribeiro, M.Á. Frutos and Jorge Barrientos Marín. Their work appears in journals such as IEEE Communications Magazine, Sensors and Desalination.

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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