Mayank Rathee
Impact in
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Stochastic Gradient Optimization Techniques
- Adversarial Robustness in Machine Learning
- Internet Traffic Analysis and Secure E-voting
Papers in
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- Cryptography and Data Security 7
- Privacy-Preserving Technologies in Data 5
- Adversarial Robustness in Machine Learning 2
- Internet Traffic Analysis and Secure E-voting 1
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- Advanced Data Storage Technologies 1
- Co-authors
- Divya Gupta (2 shared papers)Nishanth Chandran (2 shared papers)Deevashwer Rathee (2 shared papers)Nishant Kumar (1 shared paper)Rahul Sharma (1 shared paper)Aseem Rastogi (1 shared paper)Raluca Ada Popa (3 shared papers)Sameer Wagh (1 shared paper)
- Journals
- Journal of Information Security and Applications (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- IndiaUnited StatesBangladesh
In The Last Decade
Mayank Rathee
6 papers receiving 301 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 273
- Health Informatics 3
- Information Systems 47
- Computer Science Applications 9
- Computational Theory and Mathematics 23
Countries citing papers authored by Mayank Rathee
This map shows the geographic impact of Mayank Rathee'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 Mayank Rathee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayank Rathee more than expected).
Fields of papers citing papers by Mayank Rathee
This network shows the impact of papers produced by Mayank Rathee. 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 Mayank Rathee. The network helps show where Mayank Rathee may publish in the future.
Co-authors
The 14 scholars most cited alongside Mayank Rathee, 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 | 2020 | 163 | |
| 2 | 2023 | 56 | |
| 3 | 2021 | 43 | |
| 4 | 2022 | 36 | |
| 5 | 2019 | 6 | |
| 6 | 2018 | 4 | |
| 7 | 2024 | 0 |
About Mayank Rathee
Mayank Rathee is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 7 papers that have together received 308 indexed citations. Recurring topics across this work include Cryptography and Data Security (7 papers), Privacy-Preserving Technologies in Data (5 papers), Adversarial Robustness in Machine Learning (2 papers), Complexity and Algorithms in Graphs (1 paper), Advanced Data Storage Technologies (1 paper), Advanced Malware Detection Techniques (1 paper), Internet Traffic Analysis and Secure E-voting (1 paper) and Blockchain Technology Applications and Security (1 paper). The work is most often cited by research in Artificial Intelligence (273 citations), Health Informatics (3 citations), Information Systems (47 citations), Computer Science Applications (9 citations) and Computational Theory and Mathematics (23 citations). Mayank Rathee has collaborated with scholars based in India, United States and Bangladesh. Frequent co-authors include Divya Gupta, Nishanth Chandran, Deevashwer Rathee, Nishant Kumar, Rahul Sharma, Aseem Rastogi, Raluca Ada Popa, Sameer Wagh, Ion Stoica and Rahul Sharma. Their work appears in journals such as Journal of Information Security and Applications and arXiv (Cornell University).
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.