Subir Das

4.1k citations
204 papers · 3.4k · h-index 31

Impact in

Papers in

Subir Das

196 papers receiving 3.3k citations

Peers

Subir Das
Comparison fields: 5 of 90
  • Modeling and Simulation 1.4k
  • Numerical Analysis 813
  • Statistical and Nonlinear Physics 1.4k
  • Computer Networks and Communications 996
  • Applied Mathematics 351
Replace R.F. Escobar-Jiménez with:
R.F. Escobar-Jiménez Mexico
HongGuang Sun China
Kourosh Parand Iran
E. H. Twizell United Kingdom
Ronald L. Bagley United States
Carl F. Lorenzo United States
Teodor M. Atanacković Serbia
Marina V. Shitikova Russia
P. Prakash India
Yury A. Rossikhin Russia
Subir Das relative to R.F. Escobar-Jiménez Mexico R.F. Escobar-Jiménez's profile →
Citations per field
00.5×6.5×
R.F. Escobar-Jiménez · 1×
Citations per year

Countries citing papers authored by Subir Das

Since Specialization
Citations

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

Fields of papers citing papers by Subir Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 204 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009205
2 2008175
3 2012163
4 2011143
5 201397
6 201172
7 201151
8 200950
9 201649
10 200849
11 201149
12 201948
13 201347
14 197244
15 201744
16 201044
17 201943
18 197142
19 202239
20 200939

About Subir Das

Subir Das is a scholar working on Modeling and Simulation, Mechanics of Materials, Statistical and Nonlinear Physics, Computer Networks and Communications and Numerical Analysis, having authored 204 papers that have together received 3.4k indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (69 papers), Numerical methods in engineering (51 papers), Nonlinear Dynamics and Pattern Formation (41 papers), Chaos control and synchronization (40 papers), Neural Networks Stability and Synchronization (36 papers), Differential Equations and Numerical Methods (31 papers), Iterative Methods for Nonlinear Equations (27 papers) and Fatigue and fracture mechanics (22 papers). The work is most often cited by research in Modeling and Simulation (1.4k citations), Numerical Analysis (813 citations), Statistical and Nonlinear Physics (1.4k citations), Computer Networks and Communications (996 citations) and Applied Mathematics (351 citations). Subir Das has collaborated with scholars based in India, Malaysia and Romania. Frequent co-authors include Praveen Kumar Gupta, Vijay K. Yadav, Saurabh Agrawal, Mayank Srivastava, Dharmendra Tripathi, Sanjay Kumar Pandey, Rakesh Kumar, Rajeev Rajeev, Hossein Jafari and S. H. Ong. Their work appears in journals such as Chaos Solitons & Fractals, International Journal of Engineering Science, International Journal of Fracture, Applied Mathematics and Computation and Communications in Nonlinear Science and Numerical Simulation.

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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