Raja Das

2.4k total citations
93 papers, 1.3k citations indexed

About

Raja Das is a scholar working on Hardware and Architecture, Computer Networks and Communications and Mechanical Engineering. According to data from OpenAlex, Raja Das has authored 93 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Hardware and Architecture, 24 papers in Computer Networks and Communications and 22 papers in Mechanical Engineering. Recurrent topics in Raja Das's work include Parallel Computing and Optimization Techniques (29 papers), Advanced Data Storage Technologies (15 papers) and Distributed and Parallel Computing Systems (13 papers). Raja Das is often cited by papers focused on Parallel Computing and Optimization Techniques (29 papers), Advanced Data Storage Technologies (15 papers) and Distributed and Parallel Computing Systems (13 papers). Raja Das collaborates with scholars based in India, United States and Netherlands. Raja Das's co-authors include Joel Saltz, Mustafa Uysal, R. Ponnusamy, M. K. Pradhan, J. Saltz, Y. S. Hwang, P. Bala Anki Reddy, Dimitri J. Mavriplis, Joel Saltz and Yuan‐Shin Hwang and has published in prestigious journals such as Chemosphere, Expert Systems with Applications and IEEE Access.

In The Last Decade

Raja Das

88 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raja Das India 21 525 519 240 231 227 93 1.3k
Jianjun Chen China 21 156 0.3× 255 0.5× 96 0.4× 710 3.1× 244 1.1× 176 1.7k
Bing Shi China 17 317 0.6× 85 0.2× 107 0.4× 287 1.2× 93 0.4× 91 1.2k
Dong‐Ho Lee South Korea 20 536 1.0× 230 0.4× 259 1.1× 62 0.3× 60 0.3× 122 1.6k
Dong Chen China 24 519 1.0× 87 0.2× 130 0.5× 810 3.5× 59 0.3× 109 2.0k
Siting Liu China 20 313 0.6× 132 0.3× 125 0.5× 438 1.9× 15 0.1× 88 1.3k
Wei Zou China 18 83 0.2× 173 0.3× 31 0.1× 264 1.1× 108 0.5× 76 1.1k
Wei Ye China 18 1.3k 2.5× 61 0.1× 206 0.9× 924 4.0× 59 0.3× 82 2.0k
Yu‐Long Wang China 32 1.9k 3.5× 41 0.1× 128 0.5× 883 3.8× 226 1.0× 194 4.5k

Countries citing papers authored by Raja Das

Since Specialization
Citations

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

Fields of papers citing papers by Raja Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raja Das

This figure shows the co-authorship network connecting the top 25 collaborators of Raja Das. A scholar is included among the top collaborators of Raja 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 Raja Das. Raja 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, Raja, et al.. (2024). A hybridized LSTM-ANN-RSA based deep learning models for prediction of COVID-19 cases in Eastern European countries. Expert Systems with Applications. 256. 124977–124977. 6 indexed citations
3.
Das, Raja, et al.. (2024). Design of a unified physics-informed neural network using interior point algorithm to study the bioconvection nanofluid flow via stretching surface. Engineering Applications of Artificial Intelligence. 133. 108647–108647. 7 indexed citations
4.
Khan, Mohammad Zubair, et al.. (2024). A Novel QoS Prediction Model for Web Services Based on an Adaptive Neuro-Fuzzy Inference System Using COOT Optimization. IEEE Access. 12. 6993–7008. 6 indexed citations
5.
Das, Raja, et al.. (2024). Modelling atmospheric pressure through the hybridization of an ANFIS using IOWA and a snake optimizer. Modeling Earth Systems and Environment. 10(3). 4475–4495. 1 indexed citations
6.
Behera, Shishir Kumar, S. Karthika, Biswanath Mahanty, et al.. (2024). Application of artificial intelligence tools in wastewater and waste gas treatment systems: Recent advances and prospects. Journal of Environmental Management. 370. 122386–122386. 14 indexed citations
7.
Das, Raja, et al.. (2023). Modeling and optimization of WEDM of monel 400 alloy using ANFIS and snake optimizer: A comparative study. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science. 238(5). 1573–1589. 8 indexed citations
8.
Das, Raja, et al.. (2023). Entropy generation on MHD flow of second-grade hybrid nanofluid flow over a converging/diverging channel: an application in hyperthermia therapeutic aspects. The European Physical Journal Special Topics. 233(6). 1233–1249. 19 indexed citations
9.
Das, Raja, et al.. (2023). Performance evaluation of CNN-based crack detection for electrical discharge machined steel surfaces. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 238(2). 738–751. 6 indexed citations
10.
Lakshmi, M. & Raja Das. (2023). Classification of Monkeypox Images Using LIME-Enabled Investigation of Deep Convolutional Neural Network. Diagnostics. 13(9). 1639–1639. 20 indexed citations
11.
Pradhan, M. K., et al.. (2023). Measurement of EDMed surfaces roughness using convolutional neural network. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 239(2). 877–887. 1 indexed citations
12.
Vickram, Sundaram, Raja Das, Rameshpathy Manian, et al.. (2022). Bioprospecting of novel peroxidase from Streptomyces coelicolor strain SPR7 for carcinogenic azo dyes decolorization. Chemosphere. 310. 136836–136836. 22 indexed citations
13.
Das, Raja, et al.. (2022). Artificial neural networks for prediction of COVID‐19 in India by using backpropagation. Expert Systems. 40(5). e13105–e13105. 18 indexed citations
14.
Sahoo, Sarat Kumar, et al.. (2016). Control and Analysis of MPPT Techniques for Maximizing Power Extraction and Eliminating Oscillations in PV System. International Energy Journal. 16(3). 9 indexed citations
15.
Luo, Zongwei, et al.. (2002). Web Services Gateway: The Building Block for Business Connections and Dynamic e-Business.. International Conference on Internet Computing. 24(38). 779–785. 1 indexed citations
16.
Bryant, Kelvin, et al.. (2002). Jovian: a framework for optimizing parallel I/O. 21. 10–20. 20 indexed citations
17.
Das, Raja, et al.. (1997). Future Branches -- Beyond Speculative Execution. SMARTech Repository (Georgia Institute of Technology). 3 indexed citations
18.
Das, Raja & Joel Saltz. (1993). Parallelizing Molecular Dynamics Codes using the Parti Software Primitives.. PPSC. 187–192. 5 indexed citations
19.
Das, Raja, Joel Saltz, Dimitri J. Mavriplis, & R. Ponnusamy. (1992). The incremental scheduler. MIT Press eBooks. 81–105. 1 indexed citations
20.
Das, Raja, et al.. (1991). Unstructured Mesh Problems, PARTI Primitives, and the ARF Compiler. 570–572. 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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