Sujit Bebortta

970 total citations
49 papers, 474 citations indexed

About

Sujit Bebortta is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Sujit Bebortta has authored 49 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Networks and Communications, 15 papers in Artificial Intelligence and 15 papers in Electrical and Electronic Engineering. Recurrent topics in Sujit Bebortta's work include IoT and Edge/Fog Computing (23 papers), Age of Information Optimization (6 papers) and Network Security and Intrusion Detection (5 papers). Sujit Bebortta is often cited by papers focused on IoT and Edge/Fog Computing (23 papers), Age of Information Optimization (6 papers) and Network Security and Intrusion Detection (5 papers). Sujit Bebortta collaborates with scholars based in India, Saudi Arabia and Nigeria. Sujit Bebortta's co-authors include Subhranshu Sekhar Tripathy, Dilip Senapati, Bibudhendu Pati, Chhabi Rani Panigrahi, Chiranji Lal Chowdhary, Shakila Basheer, Amit Kumar Singh, Irfan Ali, Umar Muhammad Modibbo and Thippa Reddy Gadekallu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sustainability.

In The Last Decade

Sujit Bebortta

44 papers receiving 454 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujit Bebortta India 14 272 128 102 101 81 49 474
Chhabi Rani Panigrahi India 15 311 1.1× 130 1.0× 205 2.0× 113 1.1× 91 1.1× 72 612
Rustem Dautov Norway 12 306 1.1× 68 0.5× 170 1.7× 107 1.1× 80 1.0× 39 473
Mohammad Ahsan Chishti India 15 287 1.1× 88 0.7× 154 1.5× 147 1.5× 82 1.0× 59 565
Manmath Narayan Sahoo India 13 272 1.0× 108 0.8× 137 1.3× 93 0.9× 79 1.0× 37 485
Vijay Kumar Chaurasiya India 13 287 1.1× 181 1.4× 150 1.5× 124 1.2× 48 0.6× 70 545
Paulo Roberto de Lira Gondim Brazil 14 310 1.1× 209 1.6× 137 1.3× 62 0.6× 52 0.6× 42 544
Yaoqi Yang China 12 187 0.7× 101 0.8× 76 0.7× 120 1.2× 68 0.8× 29 431
Aram M. Ahmed Iraq 10 141 0.5× 39 0.3× 105 1.0× 120 1.2× 51 0.6× 20 379
Elijah Blessing Rajsingh India 12 279 1.0× 77 0.6× 237 2.3× 129 1.3× 165 2.0× 62 671
Deepraj Chowdhury India 11 245 0.9× 41 0.3× 184 1.8× 147 1.5× 62 0.8× 25 458

Countries citing papers authored by Sujit Bebortta

Since Specialization
Citations

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

Fields of papers citing papers by Sujit Bebortta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sujit Bebortta

This figure shows the co-authorship network connecting the top 25 collaborators of Sujit Bebortta. A scholar is included among the top collaborators of Sujit Bebortta 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 Sujit Bebortta. Sujit Bebortta 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.
Bebortta, Sujit, et al.. (2024). TinyDeepUAV: A Tiny Deep Reinforcement Learning Framework for UAV Task Offloading in Edge-Based Consumer Electronics. IEEE Transactions on Consumer Electronics. 70(4). 7357–7364. 7 indexed citations
2.
Tripathy, Subhranshu Sekhar, Sujit Bebortta, Mazin Abed Mohammed, et al.. (2024). A secure mist-fog-assisted cooperative offloading framework for sustainable smart city development. Digital Communications and Networks. 12(1). 165–179. 1 indexed citations
3.
Tripathy, Subhranshu Sekhar, et al.. (2024). Toward Multi-Modal Deep Learning-Assisted Task Offloading for Consumer Electronic Devices Over an IoT-Fog Architecture. IEEE Transactions on Consumer Electronics. 70(1). 1656–1663. 12 indexed citations
4.
Tripathy, Subhranshu Sekhar, Sujit Bebortta, Mazin Abed Mohammed, et al.. (2024). An SDN-enabled fog computing framework for wban applications in the healthcare sector. Internet of Things. 26. 101150–101150. 12 indexed citations
5.
Tripathy, Subhranshu Sekhar, Sujit Bebortta, Chiranji Lal Chowdhary, et al.. (2024). FedHealthFog: A federated learning-enabled approach towards healthcare analytics over fog computing platform. Heliyon. 10(5). e26416–e26416. 15 indexed citations
6.
Bebortta, Sujit, et al.. (2024). Mist–fog-assisted real-time emotion recognition using deep transfer learning framework for smart city 4.0. Internet of Things. 27. 101237–101237. 2 indexed citations
7.
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9.
Tripathy, Subhranshu Sekhar, Manisha Guduri, Chinmay Chakraborty, et al.. (2024). An Adaptive Explainable AI Framework for Securing Consumer Electronics-Based IoT Applications in Fog-Cloud Infrastructure. IEEE Transactions on Consumer Electronics. 71(1). 1889–1896. 6 indexed citations
10.
Bebortta, Sujit, Bibudhendu Pati, Chhabi Rani Panigrahi, & Dilip Senapati. (2024). Dynamic performance modeling framework for QoS-aware 5G-based IoT-edge systems. International Journal of Information Technology. 16(4). 2149–2160. 8 indexed citations
11.
Padhy, Manjog, Umar Muhammad Modibbo, Rasmita Rautray, Subhranshu Sekhar Tripathy, & Sujit Bebortta. (2024). Application of Machine Learning Techniques to Classify Twitter Sentiments Using Vectorization Techniques. Algorithms. 17(11). 486–486.
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13.
Tripathy, Subhranshu Sekhar, Sujit Bebortta, & Thippa Reddy Gadekallu. (2023). Sustainable Fog-Assisted Intelligent Monitoring Framework for Consumer Electronics in Industry 5.0 Applications. IEEE Transactions on Consumer Electronics. 70(1). 1501–1510. 14 indexed citations
14.
Tripathy, Subhranshu Sekhar, et al.. (2023). An Intelligent Health Care System in Fog Platform with Optimized Performance. Sustainability. 15(3). 1862–1862. 26 indexed citations
15.
Bebortta, Sujit, Subhranshu Sekhar Tripathy, Shakila Basheer, & Chiranji Lal Chowdhary. (2023). FedEHR: A Federated Learning Approach towards the Prediction of Heart Diseases in IoT-Based Electronic Health Records. Diagnostics. 13(20). 3166–3166. 26 indexed citations
16.
Bebortta, Sujit, et al.. (2023). Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs. International Journal of Systems Control and Communications. 15(1). 79–94. 3 indexed citations
17.
Bebortta, Sujit, et al.. (2023). Dynamic framework towards sustainable and energy-efficient routing in delay tolerant IoT-based WSNs. International Journal of Systems Control and Communications. 15(1). 79–94. 4 indexed citations
18.
Tripathy, Subhranshu Sekhar, Agbotiname Lucky Imoize, Sujit Bebortta, et al.. (2022). A Novel Edge-Computing-Based Framework for an Intelligent Smart Healthcare System in Smart Cities. Sustainability. 15(1). 735–735. 22 indexed citations
19.
Bebortta, Sujit, et al.. (2022). An intelligent spatial stream processing framework for digital forensics amid the COVID-19 outbreak. Smart Health. 26. 100308–100308. 5 indexed citations
20.
Bebortta, Sujit, et al.. (2021). An Adaptive Machine Learning-based Threat Detection Framework for Industrial Communication Networks. 527–532. 7 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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