Allon G. Percus

2.3k citations
38 papers · 1.1k indexed · h-index 18

Allon G. Percus

35 papers receiving 1.0k citations

Peers

Allon G. Percus
Comparison fields: 5 of 98
  • Statistical and Nonlinear Physics 301
  • Computational Theory and Mathematics 195
  • Artificial Intelligence 351
  • Condensed Matter Physics 117
  • Industrial and Manufacturing Engineering 94
Replace Ken A. Hawick with:
Ken A. Hawick New Zealand
T.J. Tarn United States
H.J. Sussmann United States
Nicola Santoro Canada
Thomas Laurent Japan
Zhiwen Zhang China
Edward R. Scheinerman United States
Jun Liu China
Paola Flocchini Canada
Allon G. Percus relative to Ken A. Hawick New Zealand Ken A. Hawick's profile →
Citations per field
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Ken A. Hawick · 1×
Citations per year

Countries citing papers authored by Allon G. Percus

Since Specialization
Citations

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

Fields of papers citing papers by Allon G. Percus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Allon G. Percus. 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 Allon G. Percus. The network helps show where Allon G. Percus may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20254
2 20253
3 20250
4 20241
5 20242
6 201964
7 201812
8 20179
9 20142
10 201430
11 201317
12
Parallel tempering for the traveling salesman problem
20080
13
Computational Complexity and Statistical Physics (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
20061
14
Spines of Random Constraint Satisfaction Problems: Definition and Impact on Computational Complexity.
20041
15 200447
16 2001230
17 2000176
18
Greedy algorithms for optimized DNA sequencing
19991
19 199819
20 199671

About Allon G. Percus

Allon G. Percus is a scholar working on Statistical and Nonlinear Physics, Signal Processing and Computer Networks and Communications, having authored 38 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Opinion Dynamics and Social Influence (7 papers), Constraint Satisfaction and Optimization (6 papers), Data Management and Algorithms (5 papers), Theoretical and Computational Physics (3 papers), Optimization and Search Problems (3 papers), Vehicle Routing Optimization Methods (3 papers) and Social Media and Politics (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (301 citations), Computational Theory and Mathematics (195 citations) and Artificial Intelligence (351 citations). Allon G. Percus has collaborated with scholars based in United States and France. Frequent co-authors include Stefan Boettcher, Olivier Martin, Cristina García–Cardona, Andrea L. Bertozzi, Arjuna Flenner, Ekaterina Merkurjev, Kristina Lerman, David Aldous, Aric Hagberg and Laura Mazzoli Smith. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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