Abhijit Sarkar

1.8k citations
93 papers · 1.3k indexed · h-index 22
Topics
Probabilistic and Robust Engineering Design (36 papers)Structural Health Monitoring Techniques (19 papers)Model Reduction and Neural Networks (18 papers)
Journals
Physical Review LettersSHILAP Revista de lepidopterologíaJournal of Computational Physics
Partner nations
CanadaUnited StatesIndia

In The Last Decade

Abhijit Sarkar

90 papers receiving 1.3k citations

Peers

Abhijit Sarkar
Comparison fields: 5 of 83
  • Civil and Structural Engineering 489
  • Statistics, Probability and Uncertainty 439
  • Statistical and Nonlinear Physics 325
  • Computational Mechanics 300
  • Control and Systems Engineering 288
Replace Chris L. Pettit with:
Chris L. Pettit United States
N. Sri Namachchivaya United States
Brian F. Feeny United States
Wen‐Juan Lin China
Akil Narayan United States
Hüseyin Akçay Türkiye
John Red-Horse United States
Xiaoliang Wan United States
Francisco Palacios Spain
W. Gawroński United States
Abhijit Sarkar relative to Chris L. Pettit United States Chris L. Pettit's profile →
Citations per field
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Chris L. Pettit · 1×
Citations per year

Countries citing papers authored by Abhijit Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Abhijit Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhijit Sarkar

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

All Works

20 of 20 papers shown
#WorkIndexed citations
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5 13
6 5
7 32
8 1
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10 43
11 1
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13 3
14
2-Peak and 3-Peak Optimal Complex Networks
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15 2
16 23
17 5
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19 3
20 28

About Abhijit Sarkar

Abhijit Sarkar is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Computational Mechanics, having authored 93 papers that have together received 1.3k indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (36 papers), Structural Health Monitoring Techniques (19 papers) and Model Reduction and Neural Networks (18 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (439 citations), Statistical and Nonlinear Physics (325 citations) and Civil and Structural Engineering (489 citations). Abhijit Sarkar has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Roger Ghanem, Michael P. Paı̈doussis, Mohammad Khalil, Sondipon Adhikari, Marco Amabili, C.S. Manohar, Dominique Poirel, André Valente, Howard A. Stone and R. Eatock Taylor. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Journal of Computational Physics.

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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