Pradyumna Kumar Mohapatra

612 total citations
20 papers, 366 citations indexed

About

Pradyumna Kumar Mohapatra is a scholar working on Electrical and Electronic Engineering, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Pradyumna Kumar Mohapatra has authored 20 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Electrical and Electronic Engineering, 7 papers in Signal Processing and 6 papers in Computer Networks and Communications. Recurrent topics in Pradyumna Kumar Mohapatra's work include Blind Source Separation Techniques (7 papers), Energy Efficient Wireless Sensor Networks (6 papers) and Neural Networks and Applications (4 papers). Pradyumna Kumar Mohapatra is often cited by papers focused on Blind Source Separation Techniques (7 papers), Energy Efficient Wireless Sensor Networks (6 papers) and Neural Networks and Applications (4 papers). Pradyumna Kumar Mohapatra collaborates with scholars based in India, Malaysia and Egypt. Pradyumna Kumar Mohapatra's co-authors include Jian Li, M.K. Nayak, V. S. Pandey, Bibhuti Bhusan Sahoo, D.N. Thatoi, Nimai C. Nayak, Saroja Kumar Rout, Chao Gui, Sukant Kishoro Bisoy and Amiya Kumar Rath and has published in prestigious journals such as Scientific Reports, IEEE Access and Applied Soft Computing.

In The Last Decade

Pradyumna Kumar Mohapatra

14 papers receiving 339 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pradyumna Kumar Mohapatra India 8 203 194 67 30 30 20 366
Sunhee Yang South Korea 10 509 2.5× 267 1.4× 17 0.3× 3 0.1× 33 1.1× 29 757
Jayendra Kumar India 16 453 2.2× 45 0.2× 24 0.4× 54 1.8× 9 0.3× 75 703
Can Liu China 10 188 0.9× 36 0.2× 16 0.2× 7 0.2× 46 1.5× 39 339
Jeong-Wook Kim South Korea 8 147 0.7× 25 0.1× 25 0.4× 11 0.4× 15 0.5× 58 274
Meena Malik India 9 89 0.4× 24 0.1× 159 2.4× 17 0.6× 223 7.4× 36 411
Arun Kumar Singh India 9 201 1.0× 26 0.1× 15 0.2× 5 0.2× 17 0.6× 51 344
Min Guo China 11 197 1.0× 94 0.5× 18 0.3× 12 0.4× 42 1.4× 72 472
Junhee Lee South Korea 12 209 1.0× 135 0.7× 29 0.4× 93 3.1× 30 328

Countries citing papers authored by Pradyumna Kumar Mohapatra

Since Specialization
Citations

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

Fields of papers citing papers by Pradyumna Kumar Mohapatra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pradyumna Kumar Mohapatra. 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 Pradyumna Kumar Mohapatra. The network helps show where Pradyumna Kumar Mohapatra may publish in the future.

Co-authorship network of co-authors of Pradyumna Kumar Mohapatra

This figure shows the co-authorship network connecting the top 25 collaborators of Pradyumna Kumar Mohapatra. A scholar is included among the top collaborators of Pradyumna Kumar Mohapatra 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 Pradyumna Kumar Mohapatra. Pradyumna Kumar Mohapatra 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
1.
Das, Santosh Kumar, Pradyumna Kumar Mohapatra, Saroja Kumar Rout, et al.. (2025). Equalizer Design: HBOA-DE-trained radial basis function neural networks. Egyptian Informatics Journal. 29. 100617–100617.
2.
Rout, Saroja Kumar, et al.. (2025). CLUSTER HEAD SELECTION FOR ENERGY EFFICIENCY IN WIRELESS SENSOR NETWORKS: A GRASSHOPPER OPTIMIZATION APPROACH. Proceedings on Engineering Sciences. 7(1). 555–564.
3.
Mohapatra, Pradyumna Kumar, et al.. (2025). HYBRID FIREFLY AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DESIGN OF NON-LINEAR CHANNEL EQUALIZER. Proceedings on Engineering Sciences. 7(1). 565–576.
4.
Rout, Saroja Kumar, et al.. (2024). RSSI-based optimization of static and mobile node combinations for dynamic node localization in wireless sensor networks. Telecommunication Systems. 87(1). 137–149. 3 indexed citations
5.
Rout, Saroja Kumar, Pradyumna Kumar Mohapatra, Abdulaziz S. Almazyad, et al.. (2024). Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images. Computer Modeling in Engineering & Sciences. 141(1). 893–916.
6.
Sahoo, Bibhuti Bhusan, V. S. Pandey, Pradyumna Kumar Mohapatra, et al.. (2023). A state-of-art review on 2D material-boosted metal oxide nanoparticle electrodes: Supercapacitor applications. Journal of Energy Storage. 65. 107335–107335. 86 indexed citations
7.
Mohapatra, Pradyumna Kumar, Saroja Kumar Rout, & M.K. Nayak. (2023). Development of a novel RBFNN‐trained nonlinear channel equalizer based on GDEBOA technique. International Journal of Adaptive Control and Signal Processing. 37(9). 2522–2544. 1 indexed citations
8.
Mohapatra, Pradyumna Kumar, Saroja Kumar Rout, Sukant Kishoro Bisoy, et al.. (2022). Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization. Symmetry. 14(10). 2078–2078. 16 indexed citations
9.
Rout, Saroja Kumar, Pradyumna Kumar Mohapatra, Amiya Kumar Rath, & Bibhuprasad Sahu. (2022). Node Localization in Wireless Sensor Networks using Dynamic Genetic Algorithm. Journal of Applied Research and Technology. 20(5). 520–528. 7 indexed citations
10.
Mohapatra, Pradyumna Kumar, et al.. (2022). Multi-Objective Optimization Approach in Channel Equalization Problems. 428–432. 1 indexed citations
11.
Parida, Priyadarsan, et al.. (2022). A novel approach for BOA trained ANN for channel equalization problems. Journal of Information and Optimization Sciences. 43(8). 2121–2130. 1 indexed citations
12.
Mohapatra, Pradyumna Kumar, Saroja Kumar Rout, Sukant Kishoro Bisoy, & Mangal Sain. (2022). Training Strategy of Fuzzy-Firefly Based ANN in Non-Linear Channel Equalization. IEEE Access. 10. 51229–51241. 11 indexed citations
13.
Sarma, Kishore, Nandan Bhattacharyya, Devojit Kumar Sarma, et al.. (2019). Characterization of drug resistance and genetic diversity of Plasmodium falciparum parasites from Tripura, Northeast India. Scientific Reports. 9(1). 13704–13704. 20 indexed citations
14.
Mohapatra, Pradyumna Kumar, et al.. (2016). Channel equalization as an optimization problem. 1158–1163. 4 indexed citations
15.
Rout, Saroja Kumar, et al.. (2016). Node localization by using fuzzy optimization technique in wireless sensor networks. 3. 176–181. 3 indexed citations
16.
Mohapatra, Pradyumna Kumar, et al.. (2014). A new training scheme for neural networks and application in non-linear channel equalization. Applied Soft Computing. 27. 47–52. 17 indexed citations
17.
Mohapatra, Pradyumna Kumar, et al.. (2009). Blood Pressure Modeling using Statistical and Computational Intelligence Approaches. 130. 1026–1030. 5 indexed citations
18.
Li, Jian & Pradyumna Kumar Mohapatra. (2006). An analytical model for the energy hole problem in many-to-one sensor networks. 4. 2721–2725. 160 indexed citations
19.
Gui, Chao, et al.. (2006). Exploiting Multi-Channel Clustering for Power Efficiency in Sensor Networks. 1–10. 20 indexed citations
20.
Mohapatra, Pradyumna Kumar, et al.. (1996). Haemorrhagic manifestations associated with dengue virus infection in Nagaland.. PubMed. 28(4). 301–3. 11 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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