Soumya Banerjee
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education 4
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies 6
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- COVID-19 and Mental Health 3
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- Machine Learning in Healthcare 6
- Reinforcement Learning in Robotics 3
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- Monoclonal and Polyclonal Antibodies Research 4
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- Artificial Immune Systems Applications 4
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- Ethics and Social Impacts of AI 3
- Co-authors
- Melanie E. MosesRudolf N. CardinalHera VlamakisRamnik J. XavierHimel MallickAleksandar D. KosticClary B. ClishCurtis Huttenhower
- Journals
- Angewandte Chemie International Edition (1 paper)Nature Communications (1 paper)SHILAP Revista de lepidopterología (11 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Soumya Banerjee
53 papers receiving 803 citations
Peers
Comparison fields: 5 of 140
- Health Informatics 43
- Modeling and Simulation 52
- Cell Biology 82
- Clinical Psychology 86
- Molecular Biology 264
Countries citing papers authored by Soumya Banerjee
This map shows the geographic impact of Soumya Banerjee'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 Soumya Banerjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soumya Banerjee more than expected).
Fields of papers citing papers by Soumya Banerjee
This network shows the impact of papers produced by Soumya Banerjee. 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 Soumya Banerjee. The network helps show where Soumya Banerjee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Soumya Banerjee, 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 | 2024 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 4 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 8 | |
| 8 | 2022 | 37 | |
| 9 | 2021 | 0 | |
| 10 | 2021 | 2 | |
| 11 | 2021 | 9 | |
| 12 | 2021 | 3 | |
| 13 | 2020 | 94 | |
| 14 | 2020 | 68 | |
| 15 | 2020 | 2 | |
| 16 | 2017 | 3 | |
| 17 | 2016 | 20 | |
| 18 | 2014 | 45 | |
| 19 | Digital Watermarking using Ant Colony Optimization in Fractional Fourier Domain. | 2010 | 29 |
| 20 | OptiTest: Optimizing Test Case Using Hybrid Intelligence | 2007 | 3 |
About Soumya Banerjee
Soumya Banerjee is a scholar working on Health Informatics, Modeling and Simulation and Artificial Intelligence, having authored 59 papers that have together received 833 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Machine Learning in Healthcare (6 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Artificial Immune Systems Applications (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Ethics and Social Impacts of AI (3 papers), Reinforcement Learning in Robotics (3 papers) and COVID-19 and Mental Health (3 papers). The work is most often cited by research in Health Informatics (43 citations), Modeling and Simulation (52 citations) and Cell Biology (82 citations). Soumya Banerjee has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Melanie E. Moses, Rudolf N. Cardinal, Hera Vlamakis, Ramnik J. Xavier, Himel Mallick, Aleksandar D. Kostic, Clary B. Clish, Curtis Huttenhower, Eric A. Franzosa and Alexandra Sirota‐Madi. Their work appears in journals such as Angewandte Chemie International Edition, Nature Communications and SHILAP Revista de lepidopterología.
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.