Daniel S. Roche

576 citations
30 papers · 259 · h-index 10

Impact in

Papers in

Daniel S. Roche

26 papers receiving 254 citations

Peers

Daniel S. Roche
Comparison fields: 5 of 27
  • Computational Mathematics 5
  • Computational Theory and Mathematics 132
  • Artificial Intelligence 192
  • Information Systems 94
  • Discrete Mathematics and Combinatorics 7
Replace Jean‐François Biasse with:
Jean‐François Biasse United States
Clément Pernet France
Simona Samardjiska Netherlands
A. L. Chistov Russia
Ludovic Perret France
Noah Stephens-Davidowitz United States
John Abbott Italy
Pritish Kamath United States
Tsutomu Matsumoto Japan
Youming Qiao Australia
Daniel S. Roche relative to Jean‐François Biasse United States Jean‐François Biasse's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel S. Roche

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Roche

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Daniel S. Roche, 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 S. Roche Line = papers co-authored together Daniel S. Roche links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201651
2 201639
3 201120
4 201517
5 201917
6 200915
7 201013
8 201413
9 201512
10 201411
11 20108
12 20217
13 20165
14 20195
15 20084
16 20104
17 20113
18 20193
19
Faster sparse polynomial interpolation of straight-line programs over finite fields.
20142
20 20202

About Daniel S. Roche

Daniel S. Roche is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computational Mathematics and Signal Processing, having authored 30 papers that have together received 259 indexed citations. Recurring topics across this work include Polynomial and algebraic computation (16 papers), Coding theory and cryptography (11 papers), Cryptography and Residue Arithmetic (10 papers), Cryptography and Data Security (9 papers), Numerical Methods and Algorithms (5 papers), Tensor decomposition and applications (4 papers), Privacy-Preserving Technologies in Data (3 papers) and Cloud Data Security Solutions (3 papers). The work is most often cited by research in Computational Mathematics (5 citations), Computational Theory and Mathematics (132 citations), Artificial Intelligence (192 citations), Information Systems (94 citations) and Discrete Mathematics and Combinatorics (7 citations). Daniel S. Roche has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Mark Giesbrecht, Seung Geol Choi, Adam J. Aviv, Daniel Apon, Arkady Yerukhimovich, David Harvey, Radu Sion, Travis Mayberry, Clément Pernet and Tim Finin. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, Computational Complexity, Algorithmica, Journal of Symbolic Computation 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.

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