Sudarshan Nandy
Impact in
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- Artificial Intelligence in Healthcare
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- IoT and Edge/Fog Computing
- Distributed and Parallel Computing Systems
Papers in
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- Neural Networks and Applications 3
- Metaheuristic Optimization Algorithms Research 3
- Machine Learning in Healthcare 2
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- IoT and Edge/Fog Computing 4
- Co-authors
- Mainak Adhikari (9 shared papers)Tarachand Amgoth (1 shared paper)Varun G. Menon (3 shared papers)Venki Balasubramanian (1 shared paper)Muhammad Zakarya (1 shared paper)Xingwang Li (1 shared paper)Abhishek Hazra (4 shared papers)Achintya Das (4 shared papers)
In The Last Decade
Sudarshan Nandy
18 papers receiving 270 citations
Peers
Comparison fields: 5 of 57
- Health Information Management 73
- Computer Networks and Communications 119
- Information Systems 95
- Health Informatics 4
- Artificial Intelligence 82
Countries citing papers authored by Sudarshan Nandy
This map shows the geographic impact of Sudarshan Nandy'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 Sudarshan Nandy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sudarshan Nandy more than expected).
Fields of papers citing papers by Sudarshan Nandy
This network shows the impact of papers produced by Sudarshan Nandy. 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 Sudarshan Nandy. The network helps show where Sudarshan Nandy may publish in the future.
Co-authors
The 25 scholars most cited alongside Sudarshan Nandy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 90 | |
| 2 | 2018 | 66 | |
| 3 | 2022 | 17 | |
| 4 | 2021 | 16 | |
| 5 | 2022 | 14 | |
| 6 | 2022 | 14 | |
| 7 | 2015 | 11 | |
| 8 | 2022 | 10 | |
| 9 | Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training | 2012 | 10 |
| 10 | 2021 | 10 | |
| 11 | 2014 | 5 | |
| 12 | 2023 | 5 | |
| 13 | 2012 | 5 | |
| 14 | 2007 | 5 | |
| 15 | 2023 | 4 | |
| 16 | An Improved Gauss-Newtons Method based Back- propagation Algorithm for Fast Convergence | 2016 | 2 |
| 17 | 2020 | 2 | |
| 18 | 2020 | 1 | |
| 19 | 2016 | 0 |
About Sudarshan Nandy
Sudarshan Nandy is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 19 papers that have together received 287 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (4 papers), COVID-19 diagnosis using AI (3 papers), Neural Networks and Applications (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), Machine Learning in Healthcare (2 papers), Cloud Computing and Resource Management (2 papers), EEG and Brain-Computer Interfaces (2 papers) and Brain Tumor Detection and Classification (1 paper). The work is most often cited by research in Health Information Management (73 citations), Computer Networks and Communications (119 citations), Information Systems (95 citations), Health Informatics (4 citations) and Artificial Intelligence (82 citations). Sudarshan Nandy has collaborated with scholars based in India, Estonia and Australia. Frequent co-authors include Mainak Adhikari, Tarachand Amgoth, Varun G. Menon, Venki Balasubramanian, Muhammad Zakarya, Xingwang Li, Abhishek Hazra, Achintya Das, Partha Sarkar and Xin‐She Yang. Their work appears in journals such as IEEE Sensors Journal, Future Generation Computer Systems, IEEE Internet of Things Journal, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Neural Computing and Applications.
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.