Laxmidhar Behera

6.1k citations
313 papers · 4.2k · h-index 33

Impact in

Papers in

Laxmidhar Behera

294 papers receiving 4.1k citations

Peers

Laxmidhar Behera
Comparison fields: 5 of 154
  • Control and Systems Engineering 1.7k
  • Computer Vision and Pattern Recognition 1000
  • Computer Networks and Communications 803
  • Human-Computer Interaction 173
  • Cognitive Neuroscience 507
Replace Aiguo Song with:
Aiguo Song China
Naoyuki Kubota Japan
Péter Bárányi Hungary
Hang Su China
Yibin Li China
Hajime Asama Japan
Sethu Vijayakumar United Kingdom
Sandra Hirche Germany
Nicholas Roy United States
Jorge Dias Portugal
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Citations per field
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Citations per year

Countries citing papers authored by Laxmidhar Behera

Since Specialization
Citations

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

Fields of papers citing papers by Laxmidhar Behera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 313 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017202
2 2016143
3 2006116
4 2016110
5 201394
6 201483
7 201482
8 201380
9 201776
10 201774
11 202174
12 201471
13
Intelligent Systems and Control Principles and Applications
201071
14 201467
15 200460
16 200258
17 201753
18 200852
19 201150
20 201847

About Laxmidhar Behera

Laxmidhar Behera is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Aerospace Engineering, having authored 313 papers that have together received 4.2k indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (69 papers), Distributed Control Multi-Agent Systems (42 papers), Robotic Path Planning Algorithms (34 papers), EEG and Brain-Computer Interfaces (28 papers), Advanced Vision and Imaging (27 papers), Control and Dynamics of Mobile Robots (27 papers), Adaptive Dynamic Programming Control (24 papers) and Neural Networks and Applications (24 papers). The work is most often cited by research in Control and Systems Engineering (1.7k citations), Computer Vision and Pattern Recognition (1000 citations), Computer Networks and Communications (803 citations), Human-Computer Interaction (173 citations) and Cognitive Neuroscience (507 citations). Laxmidhar Behera has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Swagat Kumar, Ranjith Ravindranathan Nair, Venkatesh K. Subramanian, T.M. McGinnity, Nishchal K. Verma, Anima Majumder, Mo Jamshidi, Tharun Kumar Reddy, Frank Schweitzer and Vipul Arora. Their work appears in journals such as IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Robotics and Automation Letters and Robotica.

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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