Rohit Kundu
- Artificial Intelligence top 2%
- AI in cancer detection 7
- Anomaly Detection Techniques and Applications 5
- Metaheuristic Optimization Algorithms Research 4
- Evolutionary Algorithms and Applications 3
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- COVID-19 diagnosis using AI 5
- Radiomics and Machine Learning in Medical Imaging 3
- Health Informatics top 10%
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- Advanced Neural Network Applications 3
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- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- Ram SarkarHritam BasakPawan Kumar SinghZong Woo GeemGi-Tae HanSoham ChattopadhyayDmitrii KaplunМассимилиано Феррара
- Partner nations
- IndiaSouth KoreaUnited States
In The Last Decade
Rohit Kundu
19 papers receiving 927 citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 565
- Radiology, Nuclear Medicine and Imaging 390
- Health Informatics 19
- Computer Vision and Pattern Recognition 246
- Health Information Management 49
Countries citing papers authored by Rohit Kundu
This map shows the geographic impact of Rohit Kundu'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 Rohit Kundu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohit Kundu more than expected).
Fields of papers citing papers by Rohit Kundu
This network shows the impact of papers produced by Rohit Kundu. 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 Rohit Kundu. The network helps show where Rohit Kundu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rohit Kundu, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 25 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 15 | |
| 8 | 2022 | 81 | |
| 9 | 2022 | 65 | |
| 10 | 2022 | 20 | |
| 11 | 2022 | 27 | |
| 12 | 2021 | 39 | |
| 13 | 2021 | 118 | |
| 14 | 2021 | 73 | |
| 15 | Pneumonia detection in chest X-ray images using an ensemble of deep learning modelsbreakdown → | 2021 | 199 |
| 16 | 2021 | 60 | |
| 17 | 2021 | 24 | |
| 18 | 2021 | 65 | |
| 19 | 2021 | 37 | |
| 20 | 2020 | 11 |
About Rohit Kundu
Rohit Kundu is a scholar working on Health Informatics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 954 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), COVID-19 diagnosis using AI (5 papers), Anomaly Detection Techniques and Applications (5 papers), Metaheuristic Optimization Algorithms Research (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Advanced Neural Network Applications (3 papers) and Evolutionary Algorithms and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (565 citations), Radiology, Nuclear Medicine and Imaging (390 citations) and Health Informatics (19 citations). Rohit Kundu has collaborated with scholars based in India, South Korea and United States. Frequent co-authors include Ram Sarkar, Hritam Basak, Pawan Kumar Singh, Zong Woo Geem, Gi-Tae Han, Soham Chattopadhyay, Dmitrii Kaplun, Массимилиано Феррара, Ali Ahmadian and Aleksandr Sinitca. Their work appears in journals such as PLoS ONE, Scientific Reports and Pattern Recognition.
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.