Daniel Kales

410 citations
18 papers · 272 · h-index 10

Impact in

Papers in

Daniel Kales

18 papers receiving 266 citations

Peers

Daniel Kales
Comparison fields: 5 of 28
  • Artificial Intelligence 247
  • Computer Vision and Pattern Recognition 69
  • Information Systems 69
  • Computational Theory and Mathematics 42
  • Hardware and Architecture 16
Replace Emanuele Bellini with:
Emanuele Bellini United Arab Emirates
Chan Fook Mun Singapore
Benjamin Hong Meng Tan Singapore
Fabian Boemer United States
Jieun Eom South Korea
Jean-Philippe Bossuat Switzerland
Tomasz Kazana Poland
Daniel Apon United States
Chitchanok Chuengsatiansup Australia
Guénaël Renault France
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Citations per field
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Emanuele Bellini · 1×
Citations per year

Countries citing papers authored by Daniel Kales

Since Specialization
Citations

This map shows the geographic impact of Daniel Kales'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 Kales with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kales more than expected).

Fields of papers citing papers by Daniel Kales

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Kales. 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 Kales. The network helps show where Daniel Kales may publish in the future.

Co-authors

The 18 scholars most cited alongside Daniel Kales, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Kales Line = papers co-authored together Daniel Kales links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 202137
2 202036
3 202030
4 202227
5
Mobile Private Contact Discovery at Scale
201927
6 201719
7 201916
8 201915
9 202014
10 202012
11 20189
12 20179
13 20217
14 20226
15 20193
16 20213
17 20251
18 20221

About Daniel Kales

Daniel Kales is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Computational Theory and Mathematics, having authored 18 papers that have together received 272 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (11 papers), Cryptography and Data Security (8 papers), Coding theory and cryptography (8 papers), Chaos-based Image/Signal Encryption (6 papers), Privacy-Preserving Technologies in Data (4 papers), Quantum Computing Algorithms and Architecture (2 papers), User Authentication and Security Systems (2 papers) and Cryptography and Residue Arithmetic (1 paper). The work is most often cited by research in Artificial Intelligence (247 citations), Computer Vision and Pattern Recognition (69 citations), Information Systems (69 citations), Computational Theory and Mathematics (42 citations) and Hardware and Architecture (16 citations). Daniel Kales has collaborated with scholars based in Austria, United States and Belgium. Frequent co-authors include Greg Zaverucha, Christian Rechberger, Maria Eichlseder, Sebastian Ramacher, Christoph Dobraunig, Markus Schofnegger, Florian Mendel, Peter Schöll, Emmanuela Orsini and Carsten Baum. Their work appears in journals such as IACR Transactions on Symmetric Cryptology, IACR Transactions on Cryptographic Hardware and Embedded Systems, Designs Codes and Cryptography, Lecture notes in computer science and Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security.

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.

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