Payman Shakouri

420 total citations
11 papers, 322 citations indexed

About

Payman Shakouri is a scholar working on Control and Systems Engineering, Automotive Engineering and Artificial Intelligence. According to data from OpenAlex, Payman Shakouri has authored 11 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Control and Systems Engineering, 9 papers in Automotive Engineering and 1 paper in Artificial Intelligence. Recurrent topics in Payman Shakouri's work include Vehicle Dynamics and Control Systems (8 papers), Traffic control and management (6 papers) and Autonomous Vehicle Technology and Safety (4 papers). Payman Shakouri is often cited by papers focused on Vehicle Dynamics and Control Systems (8 papers), Traffic control and management (6 papers) and Autonomous Vehicle Technology and Safety (4 papers). Payman Shakouri collaborates with scholars based in United Kingdom, Poland and United States. Payman Shakouri's co-authors include Andrzej Ordys, Dina Shona Laila, Jacek Czeczot and Olga Duran and has published in prestigious journals such as Control Engineering Practice, ISA Transactions and Journal of Intelligent & Robotic Systems.

In The Last Decade

Payman Shakouri

11 papers receiving 306 citations

Peers

Payman Shakouri
Comparison fields: 5 of 40
  • Control and Systems Engineering 253
  • Automotive Engineering 248
  • Mechanical Engineering 38
  • Transportation 34
  • Electrical and Electronic Engineering 30
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Stefan Solyom Sweden
V. K. Narendran United States
Ilki Moon South Korea
James Fleming United Kingdom
Yugong Luo China
Mümin Tolga Emirler Türkiye
Anca Maxim Romania
Chentong Bian China
Alexander Katriniok Germany
Feng Ding China
Stefan Solyom Sweden View profile →
Citations per field, relative to Payman Shakouri
Payman Shakouri · 1×
Citations per year, relative to Payman Shakouri
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Countries citing papers authored by Payman Shakouri

Since Specialization
Citations

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

Fields of papers citing papers by Payman Shakouri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Payman Shakouri

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

All Works

11 of 11 papers shown
# Work Indexed citations
1 25
2 82
3 3
4 18
5 9
6 6
7 52
8 1
9 84
10 10
11 32

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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