Sudarsan Padhy

420 total citations
18 papers, 287 citations indexed

About

Sudarsan Padhy is a scholar working on Management Science and Operations Research, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Sudarsan Padhy has authored 18 papers receiving a total of 287 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Management Science and Operations Research, 6 papers in Artificial Intelligence and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Sudarsan Padhy's work include Stock Market Forecasting Methods (7 papers), Energy Load and Power Forecasting (6 papers) and Machine Learning in Bioinformatics (3 papers). Sudarsan Padhy is often cited by papers focused on Stock Market Forecasting Methods (7 papers), Energy Load and Power Forecasting (6 papers) and Machine Learning in Bioinformatics (3 papers). Sudarsan Padhy collaborates with scholars based in India and United States. Sudarsan Padhy's co-authors include Biswajit Sahoo, Bijan Bihari Misra, Satya N. Mishra, Ajit Kumar Nayak and Tripti Swarnkar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Soft Computing and Neural Computing and Applications.

In The Last Decade

Sudarsan Padhy

17 papers receiving 281 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sudarsan Padhy India 10 120 85 76 60 46 18 287
Jui-Yu Wu Taiwan 9 121 1.0× 106 1.2× 55 0.7× 27 0.5× 46 1.0× 26 268
Siqi Tang China 7 126 1.1× 34 0.4× 84 1.1× 38 0.6× 39 0.8× 12 253
Haolei Chen China 4 120 1.0× 80 0.9× 64 0.8× 64 1.1× 44 1.0× 13 273
Zehong Yang China 5 138 1.1× 159 1.9× 102 1.3× 38 0.6× 54 1.2× 11 321
Qianggang Ding China 6 121 1.0× 69 0.8× 58 0.8× 33 0.6× 40 0.9× 7 234
Tung‐Kuang Wu Taiwan 9 75 0.6× 80 0.9× 64 0.8× 12 0.2× 47 1.0× 25 277
Claus Aranha Japan 10 102 0.8× 174 2.0× 29 0.4× 35 0.6× 31 0.7× 37 337
Xiongwen Pang China 6 260 2.2× 76 0.9× 125 1.6× 65 1.1× 78 1.7× 7 369
Kumkum Garg India 9 96 0.8× 55 0.6× 104 1.4× 32 0.5× 47 1.0× 36 305
Haoyu Zhang China 4 256 2.1× 66 0.8× 136 1.8× 100 1.7× 77 1.7× 7 388

Countries citing papers authored by Sudarsan Padhy

Since Specialization
Citations

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

Fields of papers citing papers by Sudarsan Padhy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudarsan Padhy

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

All Works

18 of 18 papers shown
1.
Padhy, Sudarsan, et al.. (2024). A semi-supervised approach of short text topic modeling using embedded fuzzy clustering for Twitter hashtag recommendation. SHILAP Revista de lepidopterología. 5(1). 1 indexed citations
2.
3.
Padhy, Sudarsan, et al.. (2021). A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction. The North American Journal of Economics and Finance. 55. 101350–101350. 9 indexed citations
4.
Padhy, Sudarsan, et al.. (2021). Numerical study of entropy generation analysis for non-Newtonian MHD flow of blood in a porous channel with partial slip. International Journal of Computing Science and Mathematics. 13(4). 331–331. 1 indexed citations
5.
Sahoo, Biswajit, et al.. (2020). A multiclass SVM classifier with teaching learning based feature subset selection for enzyme subclass classification. Applied Soft Computing. 96. 106664–106664. 14 indexed citations
6.
Padhy, Sudarsan, et al.. (2019). An efficient portfolio construction model using stock price predicted by support vector regression. The North American Journal of Economics and Finance. 50. 101027–101027. 22 indexed citations
7.
Nayak, Ajit Kumar, et al.. (2018). Unsteady MHD Flow and Heat Transfer of Third-Grade Fluid with Variable Viscosity Between Two Porous Plates. International Journal of Mathematics Trends and Technology. 54(2). 146–155. 1 indexed citations
8.
Padhy, Sudarsan, et al.. (2018). Electro-osmotic flow of a third-grade fluid past a channel having stretching walls. Nonlinear Engineering. 8(1). 56–64. 25 indexed citations
9.
Padhy, Sudarsan, et al.. (2017). A novel OFS–TLBO–SVR hybrid model for optimal budget allocation of government schemes to maximize GVA at factor cost. Journal of Management Analytics. 5(1). 32–53. 7 indexed citations
10.
Padhy, Sudarsan, et al.. (2017). Enzyme classification using multiclass support vector machine and feature subset selection. Computational Biology and Chemistry. 70. 211–219. 12 indexed citations
11.
Nayak, Ajit Kumar, et al.. (2016). Implicit finite difference solution for the magneto-hydro-dynamic unsteady free convective flow and heat transfer of a third-grade fluid past a porous vertical plate. International Journal of Mathematical Modelling and Numerical Optimisation. 7(1). 4–4. 6 indexed citations
12.
Padhy, Sudarsan, et al.. (2016). A new hybrid parametric and machine learning model with homogeneity hint for European-style index option pricing. Neural Computing and Applications. 28(12). 4061–4077. 26 indexed citations
13.
Padhy, Sudarsan, et al.. (2016). Novel hybrid SVM-TLBO forecasting model incorporating dimensionality reduction techniques. Applied Intelligence. 45(4). 1148–1165. 16 indexed citations
14.
Padhy, Sudarsan, et al.. (2016). Unsupervised extreme learning machine and support vector regression hybrid model for predicting energy commodity futures index. Memetic Computing. 9(4). 333–346. 14 indexed citations
15.
Padhy, Sudarsan, et al.. (2015). A novel hybrid model using teaching–learning-based optimization and a support vector machine for commodity futures index forecasting. International Journal of Machine Learning and Cybernetics. 9(1). 97–111. 88 indexed citations
16.
Padhy, Sudarsan, et al.. (2012). Support Vector Machines for Prediction of Futures Prices in Indian Stock Market. International Journal of Computer Applications. 41(3). 22–26. 42 indexed citations
17.
Sahoo, Biswajit & Sudarsan Padhy. (2009). A Reconfigurable Accelerator for Parallel Longest Common Protein Subsequence Algorithm. 12. 260–265. 2 indexed citations
18.
Sahoo, Biswajit, Tripti Swarnkar, & Sudarsan Padhy. (2009). Implementation of parallel edit distance algorithm for protein sequences using reconfigurable accelerator. 26–29. 1 indexed citations

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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