Pradipta Kumar Das

1.9k total citations
44 papers, 1.3k citations indexed

About

Pradipta Kumar Das is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Pradipta Kumar Das has authored 44 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 11 papers in Control and Systems Engineering. Recurrent topics in Pradipta Kumar Das's work include Robotic Path Planning Algorithms (26 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Control and Dynamics of Mobile Robots (9 papers). Pradipta Kumar Das is often cited by papers focused on Robotic Path Planning Algorithms (26 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Control and Dynamics of Mobile Robots (9 papers). Pradipta Kumar Das collaborates with scholars based in India, Nepal and China. Pradipta Kumar Das's co-authors include H. S. Behera, Bijaya Ketan Panigrahi, Prabir Kumar Jena, Mukesh Bathre, Manas Ranjan Kabat, Saroj Kumar Pradhan, Binod Kumar Sahu, Hrudaya Kumar Tripathy, Swagatam Das and Raghvendra Kumar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Genome Research and Neurocomputing.

In The Last Decade

Pradipta Kumar Das

43 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pradipta Kumar Das India 17 638 339 318 283 217 44 1.3k
Xiaohong Su China 18 367 0.6× 212 0.6× 163 0.5× 157 0.6× 138 0.6× 117 1.4k
Farshad Arvin United Kingdom 26 640 1.0× 320 0.9× 863 2.7× 689 2.4× 451 2.1× 115 2.3k
Gerry Dozier United States 18 320 0.5× 454 1.3× 243 0.8× 127 0.4× 50 0.2× 142 1.3k
Zhaodan Kong United States 16 656 1.0× 320 0.9× 233 0.7× 307 1.1× 569 2.6× 73 1.5k
Hoda Zamani Iran 21 242 0.4× 1.3k 3.8× 147 0.5× 211 0.7× 79 0.4× 26 1.9k
Hongwei Mo China 14 335 0.5× 247 0.7× 141 0.4× 322 1.1× 210 1.0× 90 918
Ulrik Pagh Schultz Denmark 14 88 0.1× 407 1.2× 233 0.7× 155 0.5× 131 0.6× 102 1.1k
Alma Y. Alanís Mexico 19 242 0.4× 474 1.4× 149 0.5× 1.0k 3.6× 126 0.6× 193 1.8k
Lefteris Doitsidis Greece 16 325 0.5× 211 0.6× 219 0.7× 239 0.8× 237 1.1× 49 908
Lihua Dou China 22 392 0.6× 226 0.7× 513 1.6× 604 2.1× 561 2.6× 130 1.6k

Countries citing papers authored by Pradipta Kumar Das

Since Specialization
Citations

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

Fields of papers citing papers by Pradipta Kumar Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pradipta Kumar Das

This figure shows the co-authorship network connecting the top 25 collaborators of Pradipta Kumar Das. A scholar is included among the top collaborators of Pradipta Kumar Das 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 Pradipta Kumar Das. Pradipta Kumar Das 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.
2.
Das, Pradipta Kumar & Biman Jana. (2024). Registry alteration in Dynein's microtubule-binding domain: A AAA domain-guided event. Chemical Physics Impact. 9. 100702–100702.
3.
Sahu, Binod Kumar, Pradipta Kumar Das, & Raghvendra Kumar. (2023). A modified cuckoo search algorithm implemented with SCA and PSO for multi-robot cooperation and path planning. Cognitive Systems Research. 79. 24–42. 32 indexed citations
4.
Bathre, Mukesh & Pradipta Kumar Das. (2022). Smart dual battery management system for expanding lifespan of wireless sensor node. International Journal of Communication Systems. 36(3). 35 indexed citations
5.
Das, Pradipta Kumar, et al.. (2022). Optimal path planning of multi-robot in dynamic environment using hybridization of meta-heuristic algorithm. International Journal of Intelligent Robotics and Applications. 6(4). 625–667. 4 indexed citations
6.
Bathre, Mukesh & Pradipta Kumar Das. (2022). Water supply monitoring system with self-powered LoRa based wireless sensor system powered by solar and hydroelectric energy harvester. Computer Standards & Interfaces. 82. 103630–103630. 42 indexed citations
7.
Sahu, Binod Kumar, Pradipta Kumar Das, Manas Ranjan Kabat, & Raghvendra Kumar. (2021). Prevention of Covid-19 affected patient using multi robot cooperation and Q-learning approach: a solution. Quality & Quantity. 56(2). 793–821. 8 indexed citations
8.
Das, Pradipta Kumar, et al.. (2021). Improved Binary JAYA algorithm-based scheduling dynamic cloud requests for Cloud-based computing. 1–6. 1 indexed citations
9.
Das, Pradipta Kumar & Prabir Kumar Jena. (2020). Multi-robot path planning using improved particle swarm optimization algorithm through novel evolutionary operators. Applied Soft Computing. 92. 106312–106312. 126 indexed citations
10.
Das, Pradipta Kumar. (2019). Hybridization of Kidney-Inspired and Sine–Cosine Algorithm for Multi-robot Path Planning. Arabian Journal for Science and Engineering. 45(4). 2883–2900. 21 indexed citations
11.
Das, Pradipta Kumar, et al.. (2018). Optimal path planning for mobile robots using oppositional invasive weed optimization. Computational Intelligence. 34(4). 1072–1100. 17 indexed citations
12.
13.
Jena, Prabir Kumar, et al.. (2017). Improved real time A*-fuzzy controller for improving multi-robot navigation and its performance analysis. 2(2). 105–105. 1 indexed citations
14.
Das, Pradipta Kumar, et al.. (2016). An intelligent multi-robot path planning in a dynamic environment using improved gravitational search algorithm. International Journal of Automation and Computing. 18(6). 1032–1044. 12 indexed citations
15.
Das, Pradipta Kumar, H. S. Behera, Swagatam Das, et al.. (2016). A hybrid improved PSO-DV algorithm for multi-robot path planning in a clutter environment. Neurocomputing. 207. 735–753. 113 indexed citations
16.
Das, Pradipta Kumar, H. S. Behera, Prabir Kumar Jena, & Bijaya Ketan Panigrahi. (2016). Multi-robot path planning in a dynamic environment using improved gravitational search algorithm. SHILAP Revista de lepidopterología. 3(2). 295–313. 42 indexed citations
17.
18.
Wei, Lan‐Hai, et al.. (2015). A late Neolithic expansion of Y chromosomal haplogroup O2a1‐M95 from east to west. Journal of Systematics and Evolution. 53(6). 546–560. 12 indexed citations
19.
Das, Pradipta Kumar, et al.. (2010). Conditional Q-learning algorithm for path-planning of a mobile robot. 20. 23–27. 5 indexed citations
20.
Watkins, W. Scott, Alan R. Rogers, Christopher T. Ostler, et al.. (2003). Genetic Variation Among World Populations: Inferences From 100 Alu Insertion Polymorphisms. Genome Research. 13(7). 1607–1618. 168 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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