Peter Schöll

3.4k citations
29 papers · 369 indexed · h-index 9

Peter Schöll

29 papers receiving 346 citations

Peers

Peter Schöll
Comparison fields: 5 of 73
  • Artificial Intelligence 279
  • Otorhinolaryngology 26
  • Computational Theory and Mathematics 86
  • Information Systems 74
  • Computer Networks and Communications 38
Replace Neha Sharma with:
Neha Sharma India
David W. Archer United States
Guadalupe Canahuate United States
C. Gunavathi India
Shereen Fouad United Kingdom
Enoch Peserico Italy
Dong Wei China
Chenghong Wang United States
Baolin Li Mexico
Zhiqun Chen China
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Citations per field
00.5×8.6×
Neha Sharma · 1×
Citations per year

Countries citing papers authored by Peter Schöll

Since Specialization
Citations

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

Fields of papers citing papers by Peter Schöll

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Peter Schöll, 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 Peter Schöll Line = papers co-authored together Peter Schöll links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20231
2 20231
3 20221
4 20223
5 20217
6
Mac'n'Cheese: Zero-Knowledge Proofs for Boolean and Arithmetic Circuits with Nested Disjunctions
20201
7 202011
8 20195
9 201943
10 2016136
11
Cryptography and Coding - IMACC 2011
20115
12 201010
13 20101
14
GMD-Robots
20011
15
Quality Management for Mobile Robot Development
20003
16
Tools for Assessing RoboCup Behavior
20001
17
The Uses of Impersonation.
19861
18 19859
19
Tympanostomy tubes and liquids--an in vitro study.
198430
20 19721

About Peter Schöll

Peter Schöll is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, General Social Sciences, Computer Vision and Pattern Recognition and Otorhinolaryngology, having authored 29 papers that have together received 369 indexed citations. Recurring topics across this work include Cryptography and Data Security (11 papers), Complexity and Algorithms in Graphs (7 papers), Cryptography and Residue Arithmetic (4 papers), Cryptographic Implementations and Security (3 papers), Coding theory and cryptography (2 papers), Cancer and Skin Lesions (2 papers), Health, Medicine and Society (2 papers) and Metastasis and carcinoma case studies (2 papers). The work is most often cited by research in Artificial Intelligence (279 citations), Otorhinolaryngology (26 citations), Computational Theory and Mathematics (86 citations), Information Systems (74 citations) and Computer Networks and Communications (38 citations). Peter Schöll has collaborated with scholars based in Denmark, United States and Germany. Frequent co-authors include Marcel Keller, Emmanuela Orsini, Nigel P. Smart, Lisa Kohl, Yuval Ishai, Niv Gilboa, Geoffroy Couteau, Peter Rindal, Lorenzo Grassi and Dragos Rotaru. Their work appears in journals such as Journal of Cryptology, Otolaryngology, MTZ - Motortechnische Zeitschrift, Studies in American fiction and Information and Computation.

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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