B Divya
Impact in
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- Artificial Intelligence in Healthcare and Education
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- Multi-Agent Systems and Negotiation
- Adversarial Robustness in Machine Learning
- AI in Service Interactions
- Reinforcement Learning in Robotics
Papers in
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- Medical Image Segmentation Techniques 3
- Advanced Neural Network Applications 2
- Co-authors
- Deepak Bhaskar Acharya (4 shared papers)Pitchaiah Mandava (3 shared papers)Deepu Vijayasenan (3 shared papers)Rajesh Nair (4 shared papers)K Prakashini (4 shared papers)Girish Menon (3 shared papers)Rajesh Menon (1 shared paper)P. Deepa (1 shared paper)
- Journals
- IEEE Access (3 papers)F1000Research (1 paper)Biomedical Signal Processing and Control (1 paper)2021 IEEE 18th India Council International Conference (INDICON) (1 paper)AIP conference proceedings (2 papers)
- Partner nations
- IndiaUnited StatesNepal
In The Last Decade
B Divya
10 papers receiving 175 citations
B Divya's Hit Papers
Peers
Comparison fields: 5 of 56
- Health Informatics 10
- Artificial Intelligence 48
- Management Information Systems 10
- Safety Research 9
- Industrial and Manufacturing Engineering 10
Countries citing papers authored by B Divya
This map shows the geographic impact of B Divya'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 B Divya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B Divya more than expected).
Fields of papers citing papers by B Divya
This network shows the impact of papers produced by B Divya. 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 B Divya. The network helps show where B Divya may publish in the future.
Co-authors
The 10 scholars most cited alongside B Divya, 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 | Agentic AI: Autonomous Intelligence for Complex Goals—A Comprehensive Survey Hit paper breakdown → | 2025 | 156 |
| 2 | 2024 | 10 | |
| 3 | 2021 | 9 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 2 | |
| 6 | 2025 | 2 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2025 | 0 |
About B Divya
B Divya is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology, Information Systems and Management Science and Operations Research, having authored 12 papers that have together received 188 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (3 papers), Brain Tumor Detection and Classification (3 papers), Insurance and Financial Risk Management (2 papers), Medical Imaging and Analysis (2 papers), Advanced Neural Network Applications (2 papers), Stock Market Forecasting Methods (2 papers), Spam and Phishing Detection (1 paper) and Advanced Image Fusion Techniques (1 paper). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (48 citations), Management Information Systems (10 citations), Safety Research (9 citations) and Industrial and Manufacturing Engineering (10 citations). B Divya has collaborated with scholars based in India, United States and Nepal. Frequent co-authors include Deepak Bhaskar Acharya, Pitchaiah Mandava, Deepu Vijayasenan, Rajesh Nair, K Prakashini, Girish Menon, Rajesh Menon, P. Deepa, B. Saravana Balaji and Deepak Acharya. Their work appears in journals such as IEEE Access, F1000Research, Biomedical Signal Processing and Control, 2021 IEEE 18th India Council International Conference (INDICON) and AIP conference proceedings.
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.