Subarna Chatterjee

1.1k total citations · 1 hit paper
31 papers, 832 citations indexed

About

Subarna Chatterjee is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Subarna Chatterjee has authored 31 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 10 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Subarna Chatterjee's work include Energy Efficient Wireless Sensor Networks (10 papers), IoT and Edge/Fog Computing (9 papers) and AI in cancer detection (5 papers). Subarna Chatterjee is often cited by papers focused on Energy Efficient Wireless Sensor Networks (10 papers), IoT and Edge/Fog Computing (9 papers) and AI in cancer detection (5 papers). Subarna Chatterjee collaborates with scholars based in India, United Kingdom and Saudi Arabia. Subarna Chatterjee's co-authors include Sudip Misra, Subhadeep Sarkar, Samee U. Khan, Amit Kumar Mandal, Rezaul Karim, Ajoy Kumar Ray, A.K. Ray, Surbhi Bhatia, Arindam Biswas and Ahlam Almusharraf and has published in prestigious journals such as IEEE Transactions on Communications, Information Sciences and IEEE Communications Letters.

In The Last Decade

Subarna Chatterjee

29 papers receiving 796 citations

Hit Papers

Assessment of the Suitability of Fog Computing in the Con... 2015 2026 2018 2022 2015 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Assessment of the Suitability of Fog Computing in the Context of Internet of Things
    2015 492 citations Subarna Chatterjee, Sudip Misra et al. IEEE Transactions on Cloud Computing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subarna Chatterjee India 11 667 257 238 130 118 31 832
Hailiang Zhao China 12 745 1.1× 357 1.4× 268 1.1× 166 1.3× 239 2.0× 20 1.1k
Rakesh Matam India 14 802 1.2× 309 1.2× 301 1.3× 138 1.1× 164 1.4× 69 966
Tam N. Nguyen United States 4 777 1.2× 392 1.5× 249 1.0× 172 1.3× 119 1.0× 6 955
Krishna Kadiyala United States 4 786 1.2× 375 1.5× 250 1.1× 163 1.3× 114 1.0× 5 934
Paola G. Vinueza Naranjo Italy 11 640 1.0× 186 0.7× 347 1.5× 106 0.8× 56 0.5× 27 818
Anwesha Mukherjee India 18 749 1.1× 268 1.0× 462 1.9× 142 1.1× 70 0.6× 78 986
Tianyi Song United States 12 393 0.6× 387 1.5× 197 0.8× 119 0.9× 261 2.2× 22 839
Yuan Xue China 9 565 0.8× 346 1.3× 278 1.2× 114 0.9× 207 1.8× 27 821
Ayoub Alsarhan Jordan 16 436 0.7× 233 0.9× 247 1.0× 77 0.6× 214 1.8× 98 829

Countries citing papers authored by Subarna Chatterjee

Since Specialization
Citations

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

Fields of papers citing papers by Subarna Chatterjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subarna Chatterjee

This figure shows the co-authorship network connecting the top 25 collaborators of Subarna Chatterjee. A scholar is included among the top collaborators of Subarna Chatterjee 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 Subarna Chatterjee. Subarna Chatterjee 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
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Chatterjee, Subarna, et al.. (2024). Etiology of Late-Onset Alzheimer’s Disease, Biomarker Efficacy, and the Role of Machine Learning in Stage Diagnosis. Diagnostics. 14(23). 2640–2640. 3 indexed citations
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Chatterjee, Subarna, et al.. (2023). Fusion of Graph and Tabular Deep Learning Models for Predicting Chronic Kidney Disease. Diagnostics. 13(12). 1981–1981. 10 indexed citations
5.
Chatterjee, Subarna, et al.. (2023). Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images. Diagnostics. 13(20). 3244–3244. 4 indexed citations
6.
Chatterjee, Subarna, et al.. (2023). Enhancing the diagnosis of autism spectrum disorder using phenotypic, structural, and functional MRI data. Innovations in Systems and Software Engineering. 21(3). 813–824. 1 indexed citations
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Chatterjee, Subarna, et al.. (2022). Weight Pruning-UNet. Journal of Medical Signals & Sensors. 12(2). 108–113. 6 indexed citations
9.
Chatterjee, Subarna, et al.. (2019). Diabot: A Predictive Medical Chatbot using Ensemble Learning. International Journal of Recent Technology and Engineering (IJRTE). 8(2). 6334–6340. 23 indexed citations
10.
Chatterjee, Subarna, et al.. (2017). Link-Quality Aware Path Selection in the Presence of Proactive Jamming in Fallible Wireless Sensor Networks. IEEE Transactions on Communications. 66(4). 1689–1704. 19 indexed citations
11.
Chatterjee, Subarna & Sudip Misra. (2016). QoS estimation and selection of CSP in oligopoly environment for Internet of Things. 3. 1–6. 4 indexed citations
12.
Chatterjee, Subarna, Sudip Misra, & Samee U. Khan. (2015). Optimal Data Center Scheduling for Quality of Service Management in Sensor-Cloud. IEEE Transactions on Cloud Computing. 7(1). 89–101. 31 indexed citations
13.
Misra, Sudip, et al.. (2015). QoS-aware sensor allocation for target tracking in sensor-cloud. Ad Hoc Networks. 33. 140–153. 18 indexed citations
14.
Chatterjee, Subarna, et al.. (2015). Two-level mapping to mitigate congestion in machine to machine (M2M) cloud. 104–108. 7 indexed citations
15.
Misra, Sudip & Subarna Chatterjee. (2014). Social choice considerations in cloud-assisted WBAN architecture for post-disaster healthcare: Data aggregation and channelization. Information Sciences. 284. 95–117. 50 indexed citations
16.
Chatterjee, Subarna & Sudip Misra. (2014). Target Tracking Using Sensor-Cloud: Sensor-Target Mapping in Presence of Overlapping Coverage. IEEE Communications Letters. 18(8). 1435–1438. 31 indexed citations
17.
Chatterjee, Subarna, et al.. (2012). Color Doppler to Characterize Malignant Breast Lesion. 2(2). 24–27. 5 indexed citations
18.
Chatterjee, Subarna, Ajoy Kumar Ray, Rezaul Karim, & Arindam Biswas. (2011). Architecture Design for Median Filter. 9. 247–250. 2 indexed citations
19.
Chatterjee, Subarna, Ajoy Kumar Ray, Rezaul Karim, & Arindam Biswas. (2011). Micro-calcification detection to characterize malignant breast lesion. 1. 1–4. 1 indexed citations
20.
Chatterjee, Subarna, Rezaul Karim, & A.K. Ray. (2010). Identification. 9. 202–205. 5 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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