Karn Seth
Impact in
- Artificial Intelligence top 0.5%
- 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
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- Mobile Crowdsensing and Crowdsourcing
Papers in
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- Cryptography and Data Security 13
- Privacy-Preserving Technologies in Data 6
- Cryptographic Implementations and Security 6
- Internet Traffic Analysis and Secure E-voting 3
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- Complexity and Algorithms in Graphs 4
- Computability, Logic, AI Algorithms 2
- Co-authors
- Sarvar Patel (4 shared papers)Ben Kreuter (2 shared papers)Keith Bonawitz (1 shared paper)Daniel Ramage (1 shared paper)Antonio Marcedone (1 shared paper)Vladimir Ivanov (1 shared paper)Aaron Segal (1 shared paper)H. Brendan McMahan (1 shared paper)
- Journals
- Algorithmica (1 paper)SIAM Journal on Computing (1 paper)Lecture notes in computer science (8 papers)
- Partner nations
- United StatesSwedenTaiwan
In The Last Decade
Karn Seth
13 papers receiving 2.4k citations
Karn Seth's Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 2.3k
- Computer Science Applications 253
- Health Informatics 47
- Information Systems 311
- Computational Theory and Mathematics 177
Countries citing papers authored by Karn Seth
This map shows the geographic impact of Karn Seth'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 Karn Seth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karn Seth more than expected).
Fields of papers citing papers by Karn Seth
This network shows the impact of papers produced by Karn Seth. 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 Karn Seth. The network helps show where Karn Seth may publish in the future.
Co-authors
The 24 scholars most cited alongside Karn Seth, 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 | Practical Secure Aggregation for Privacy-Preserving Machine Learning Hit paper breakdown → | 2017 | 2141 |
| 2 | 2014 | 107 | |
| 3 | 2020 | 74 | |
| 4 | 2020 | 38 | |
| 5 | 2016 | 35 | |
| 6 | 2015 | 31 | |
| 7 | 2014 | 19 | |
| 8 | 2013 | 18 | |
| 9 | 2021 | 14 | |
| 10 | 2016 | 7 | |
| 11 | 2016 | 5 | |
| 12 | 2023 | 4 | |
| 13 | 2024 | 2 | |
| 14 | 2014 | 0 | |
| 15 | Block Sensitivity versus Sensitivity | 2010 | 0 |
About Karn Seth
Karn Seth is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Information Systems, having authored 15 papers that have together received 2.5k indexed citations. Recurring topics across this work include Cryptography and Data Security (13 papers), Privacy-Preserving Technologies in Data (6 papers), Cryptographic Implementations and Security (6 papers), Complexity and Algorithms in Graphs (4 papers), Internet Traffic Analysis and Secure E-voting (3 papers), Computability, Logic, AI Algorithms (2 papers), Chaos-based Image/Signal Encryption (2 papers) and Consumer Market Behavior and Pricing (1 paper). The work is most often cited by research in Artificial Intelligence (2.3k citations), Computer Science Applications (253 citations), Health Informatics (47 citations), Information Systems (311 citations) and Computational Theory and Mathematics (177 citations). Karn Seth has collaborated with scholars based in United States, Sweden and Taiwan. Frequent co-authors include Sarvar Patel, Ben Kreuter, Keith Bonawitz, Daniel Ramage, Antonio Marcedone, Vladimir Ivanov, Aaron Segal, H. Brendan McMahan, Rafael Pass and Sidharth Telang. Their work appears in journals such as Algorithmica, SIAM Journal on Computing and Lecture notes in computer science.
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.