P. Pramod Chakravarthy

598 citations
44 papers · 453 indexed · h-index 14
Topics
Differential Equations and Numerical Methods (44 papers)Numerical methods for differential equations (18 papers)Advanced Mathematical Modeling in Engineering (15 papers)
Partner nations
IndiaSpain

In The Last Decade

P. Pramod Chakravarthy

41 papers receiving 429 citations

Peers

P. Pramod Chakravarthy
Comparison fields: 5 of 34
  • Numerical Analysis 426
  • Computational Theory and Mathematics 159
  • Applied Mathematics 80
  • Mechanical Engineering 77
  • Modeling and Simulation 70
Replace S. Chandra Sekhara Rao with:
S. Chandra Sekhara Rao India
V. Shanthi India
Li‐Bin Liu China
J.C. Jorge Spain
Y. N. Reddy India
Gabil M. Amiraliyev Türkiye
N. Ramanujam India
Vikas Gupta India
Jugal Mohapatra India
P. Pramod Chakravarthy relative to S. Chandra Sekhara Rao India S. Chandra Sekhara Rao's profile →
Citations per field
00.5×2.8×
S. Chandra Sekhara Rao · 1×
Citations per year

Countries citing papers authored by P. Pramod Chakravarthy

Since Specialization
Citations

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

Fields of papers citing papers by P. Pramod Chakravarthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. Pramod Chakravarthy. 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 P. Pramod Chakravarthy. The network helps show where P. Pramod Chakravarthy may publish in the future.

Co-authorship network of co-authors of P. Pramod Chakravarthy

This figure shows the co-authorship network connecting the top 25 collaborators of P. Pramod Chakravarthy. A scholar is included among the top collaborators of P. Pramod Chakravarthy 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 P. Pramod Chakravarthy. P. Pramod Chakravarthy 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
1 0
2 1
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4 15
5 2
6 23
7 21
8 15
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11 1
12 13
13 1
14 1
15 18
16 5
17 11
18
A Fitted Numerov Method for Singular Perturbation Problems Exhibiting Twin Layers
9
19 5
20 16

About P. Pramod Chakravarthy

P. Pramod Chakravarthy is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Applied Mathematics, having authored 44 papers that have together received 453 indexed citations. Recurring topics across this work include Differential Equations and Numerical Methods (44 papers), Numerical methods for differential equations (18 papers) and Advanced Mathematical Modeling in Engineering (15 papers). The work is most often cited by research in Numerical Analysis (426 citations), Modeling and Simulation (70 citations) and Computational Theory and Mathematics (159 citations). P. Pramod Chakravarthy has collaborated with scholars based in India and Spain. Frequent co-authors include Y. N. Reddy, Higinio Ramos, Pratibhamoy Das, J. Vigo‐Aguiar, Devendra Kumar and Rahul Mishra. Their work appears in journals such as Applied Mathematics and Computation, Applied Mathematical Modelling and Journal of Computational and Applied Mathematics.

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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