Atul Rawal
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
Papers in
-
- Adversarial Robustness in Machine Learning 3
- Explainable Artificial Intelligence (XAI) 3
- Anomaly Detection Techniques and Applications 2
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- Silk-based biomaterials and applications 3
- Collagen: Extraction and Characterization 3
- Co-authors
- Danda B. Rawat (9 shared papers)Brian M. Sadler (6 shared papers)James McCoy (1 shared paper)Robert St. Amant (1 shared paper)Zuben E. Sauna (3 shared papers)Adrienne Raglin (4 shared papers)Ram Mohan (4 shared papers)Qianlong Wang (1 shared paper)
- Journals
- IEEE Transactions on Artificial Intelligence (1 paper)Nature Communications (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)ACM Computing Surveys (1 paper)Journal of Biomechanical Engineering (1 paper)
- Partner nations
- United States
In The Last Decade
Atul Rawal
17 papers receiving 238 citations
Peers
Comparison fields: 5 of 69
- Health Informatics 17
- Artificial Intelligence 121
- Signal Processing 21
- Computer Networks and Communications 41
- Health Information Management 7
Countries citing papers authored by Atul Rawal
This map shows the geographic impact of Atul Rawal'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 Atul Rawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Atul Rawal more than expected).
Fields of papers citing papers by Atul Rawal
This network shows the impact of papers produced by Atul Rawal. 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 Atul Rawal. The network helps show where Atul Rawal may publish in the future.
Co-authors
The 14 scholars most cited alongside Atul Rawal, 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 | 120 | |
| 2 | 2022 | 50 | |
| 3 | 2022 | 29 | |
| 4 | 2021 | 13 | |
| 5 | 2024 | 6 | |
| 6 | 2023 | 6 | |
| 7 | 2024 | 5 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 3 | |
| 10 | 2022 | 3 | |
| 11 | 2022 | 2 | |
| 12 | 2023 | 2 | |
| 13 | 2019 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2020 | 1 | |
| 18 | 2024 | 0 |
About Atul Rawal
Atul Rawal is a scholar working on Artificial Intelligence, Biomaterials, Molecular Biology, Computer Vision and Pattern Recognition and Hematology, having authored 18 papers that have together received 247 indexed citations. Recurring topics across this work include Silk-based biomaterials and applications (3 papers), Adversarial Robustness in Machine Learning (3 papers), Collagen: Extraction and Characterization (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Hemophilia Treatment and Research (2 papers), Anomaly Detection Techniques and Applications (2 papers), Advanced Neural Network Applications (2 papers) and IoT and Edge/Fog Computing (2 papers). The work is most often cited by research in Health Informatics (17 citations), Artificial Intelligence (121 citations), Signal Processing (21 citations), Computer Networks and Communications (41 citations) and Health Information Management (7 citations). Atul Rawal has collaborated with scholars based in United States. Frequent co-authors include Danda B. Rawat, Brian M. Sadler, James McCoy, Robert St. Amant, Zuben E. Sauna, Adrienne Raglin, Ram Mohan, Qianlong Wang, Osman N. Yoğurtçu and Hong Yang. Their work appears in journals such as IEEE Transactions on Artificial Intelligence, Nature Communications, IEEE Transactions on Intelligent Transportation Systems, ACM Computing Surveys and Journal of Biomechanical Engineering.
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.