Daniel Wichs
- Artificial Intelligence top 2%
- Information Systems top 5%
- Computational Theory and Mathematics top 2%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Craig GentryYevgeniy DodisVinod VaikuntanathanS. GorbunovAdriana López-AltKristiyan HaralambievDavid M. CashAlpteki̇n Küpçü
- Topics
- Cryptography and Data Security (26 papers)Complexity and Algorithms in Graphs (12 papers)Cryptographic Implementations and Security (12 papers)
- Partner nations
- United StatesIsraelMexico
In The Last Decade
Daniel Wichs
30 papers receiving 626 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 608
- Information Systems 205
- Computational Theory and Mathematics 197
- Computer Vision and Pattern Recognition 98
- Computer Networks and Communications 68
Countries citing papers authored by Daniel Wichs
This map shows the geographic impact of Daniel Wichs'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 Daniel Wichs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Wichs more than expected).
Fields of papers citing papers by Daniel Wichs
This network shows the impact of papers produced by Daniel Wichs. 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 Daniel Wichs. The network helps show where Daniel Wichs may publish in the future.
Co-authorship network of co-authors of Daniel Wichs
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Wichs. A scholar is included among the top collaborators of Daniel Wichs 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 Daniel Wichs. Daniel Wichs 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 | 3 | |
| 4 | 8 | |
| 5 | 34 | |
| 6 | 5 | |
| 7 | 8 | |
| 8 | 10 | |
| 9 | 18 | |
| 10 | Anonymous Traitor Tracing: How to Embed Arbitrary Information in a Key (from Eurocrypt 2016) | 1 |
| 11 | 5 | |
| 12 | Onion ORAM: A Constant Bandwidth Blowup Oblivious RAM | 2 |
| 13 | 19 | |
| 14 | 60 | |
| 15 | 14 | |
| 16 | Learning with Rounding, Revisited - New Reduction, Properties and Applications. | 14 |
| 17 | 8 | |
| 18 | 102 | |
| 19 | Non-Malleable Codes. | 30 |
| 20 | 43 |
About Daniel Wichs
Daniel Wichs is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 651 indexed citations. Recurring topics across this work include Cryptography and Data Security (26 papers), Complexity and Algorithms in Graphs (12 papers) and Cryptographic Implementations and Security (12 papers). The work is most often cited by research in Artificial Intelligence (608 citations), Computational Theory and Mathematics (197 citations) and Information Systems (205 citations). Daniel Wichs has collaborated with scholars based in United States, Israel and Mexico. Frequent co-authors include Craig Gentry, Yevgeniy Dodis, Vinod Vaikuntanathan, S. Gorbunov, Adriana López-Alt, Kristiyan Haralambiev, David M. Cash, Alpteki̇n Küpçü, Krzysztof Pietrzak and Stefan Dziembowski. Their work appears in journals such as IEEE Transactions on Information Theory, Journal of the ACM and SIAM Journal on Computing.
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.