Jacob C. N. Schuldt
- Artificial Intelligence top 10%
- Information Systems
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Signal Processing
- Co-authors
- Bertram PoetteringDaniel J. BernsteinKenneth G. PatersonGoichiro HanaokaNuttapong AttrapadungTakashi NishideYusuke SakaiKazumasa Shinagawa
- Topics
- Cryptography and Data Security (21 papers)Complexity and Algorithms in Graphs (10 papers)Cryptographic Implementations and Security (8 papers)
- Partner nations
- JapanSwitzerlandUnited Kingdom
In The Last Decade
Jacob C. N. Schuldt
21 papers receiving 143 citations
Peers
Comparison fields: 5 of 28
- Artificial Intelligence 129
- Information Systems 44
- Computer Networks and Communications 33
- Computer Vision and Pattern Recognition 28
- Signal Processing 28
Countries citing papers authored by Jacob C. N. Schuldt
This map shows the geographic impact of Jacob C. N. Schuldt'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 Jacob C. N. Schuldt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob C. N. Schuldt more than expected).
Fields of papers citing papers by Jacob C. N. Schuldt
This network shows the impact of papers produced by Jacob C. N. Schuldt. 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 Jacob C. N. Schuldt. The network helps show where Jacob C. N. Schuldt may publish in the future.
Co-authorship network of co-authors of Jacob C. N. Schuldt
This figure shows the co-authorship network connecting the top 25 collaborators of Jacob C. N. Schuldt. A scholar is included among the top collaborators of Jacob C. N. Schuldt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jacob C. N. Schuldt. Jacob C. N. Schuldt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | On signatures with tight security in the multi-user setting | 0 |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 6 | |
| 17 | On the security of RC4 in TLS | 75 |
| 18 | 8 | |
| 19 | 3 | |
| 20 | 10 |
About Jacob C. N. Schuldt
Jacob C. N. Schuldt is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 23 papers that have together received 158 indexed citations. Recurring topics across this work include Cryptography and Data Security (21 papers), Complexity and Algorithms in Graphs (10 papers) and Cryptographic Implementations and Security (8 papers). The work is most often cited by research in Artificial Intelligence (129 citations), Signal Processing (28 citations) and Information Systems (44 citations). Jacob C. N. Schuldt has collaborated with scholars based in Japan, Switzerland and United Kingdom. Frequent co-authors include Bertram Poettering, Daniel J. Bernstein, Kenneth G. Paterson, Goichiro Hanaoka, Nuttapong Attrapadung, Takashi Nishide, Yusuke Sakai, Kazumasa Shinagawa, Takahiro Matsuda and Keita Emura. Their work appears in journals such as Theoretical Computer Science, Journal of Cryptology and Designs Codes and Cryptography.
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.