Adit Goyal
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Information Systems top 5%
- Blockchain Technology Applications and Security
Papers in
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- Blockchain Technology Applications and Security 4
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- Antifungal resistance and susceptibility 2
- Co-authors
- Vinay Chamola (7 shared papers)Mohsen Guizani (2 shared papers)Vikas Hassija (4 shared papers)Biplab Sikdar (3 shared papers)Nishad Sahu (1 shared paper)Tejasvi Alladi (1 shared paper)Tilak Agerwala (1 shared paper)Huynh Thi Thanh Binh (1 shared paper)
- Journals
- IEEE Transactions on Computational Social Systems (2 papers)European Annals of Otorhinolaryngology Head and Neck Diseases (1 paper)IEEE Internet of Things Journal (1 paper)IBM Journal of Research and Development (1 paper)Neural Computing and Applications (1 paper)
- Partner nations
- IndiaSingaporeUnited Arab Emirates
In The Last Decade
Adit Goyal
10 papers receiving 317 citations
Peers
Comparison fields: 5 of 80
- Health Informatics 16
- Information Systems 147
- Computer Networks and Communications 110
- Artificial Intelligence 93
- Management Information Systems 22
Countries citing papers authored by Adit Goyal
This map shows the geographic impact of Adit Goyal'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 Adit Goyal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adit Goyal more than expected).
Fields of papers citing papers by Adit Goyal
This network shows the impact of papers produced by Adit Goyal. 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 Adit Goyal. The network helps show where Adit Goyal may publish in the future.
Co-authors
The 25 scholars most cited alongside Adit Goyal, 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 | 2022 | 101 | |
| 2 | 2020 | 101 | |
| 3 | 2022 | 58 | |
| 4 | 1984 | 28 | |
| 5 | 2022 | 15 | |
| 6 | 2023 | 12 | |
| 7 | 2021 | 10 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 3 | |
| 10 | 2021 | 2 |
About Adit Goyal
Adit Goyal is a scholar working on Information Systems, Infectious Diseases, Artificial Intelligence, Computer Networks and Communications and Hardware and Architecture, having authored 10 papers that have together received 340 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (4 papers), Anomaly Detection Techniques and Applications (2 papers), Antifungal resistance and susceptibility (2 papers), Advanced Data Storage Technologies (1 paper), Fungal Infections and Studies (1 paper), Data-Driven Disease Surveillance (1 paper), IoT and Edge/Fog Computing (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (16 citations), Information Systems (147 citations), Computer Networks and Communications (110 citations), Artificial Intelligence (93 citations) and Management Information Systems (22 citations). Adit Goyal has collaborated with scholars based in India, Singapore and United Arab Emirates. Frequent co-authors include Vinay Chamola, Mohsen Guizani, Vikas Hassija, Biplab Sikdar, Nishad Sahu, Tejasvi Alladi, Tilak Agerwala, Huynh Thi Thanh Binh, Vikas Saxena and Murari Mandal. Their work appears in journals such as IEEE Transactions on Computational Social Systems, European Annals of Otorhinolaryngology Head and Neck Diseases, IEEE Internet of Things Journal, IBM Journal of Research and Development 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.