Chiara Marcolla

411 citations
14 papers · 177 · h-index 5

Impact in

Papers in

Chiara Marcolla

13 papers receiving 171 citations

Peers

Chiara Marcolla
Comparison fields: 5 of 33
  • Discrete Mathematics and Combinatorics 19
  • Artificial Intelligence 139
  • Information Systems 51
  • Computer Networks and Communications 37
  • Computer Vision and Pattern Recognition 24
Replace Carlos Aguilar Melchor with:
Carlos Aguilar Melchor France
Chungen Xu China
Siyi Lv China
Liang Feng Zhang China
Ivan Visconti Italy
Yury Lifshits United States
Vishal Saraswat India
Yanmin Shang China
Jérémy Jean France
Mayank Rathee United States
Chiara Marcolla relative to Carlos Aguilar Melchor France Carlos Aguilar Melchor's profile →
Citations per field
00.5×10.2×
Carlos Aguilar Melchor · 1×
Citations per year

Countries citing papers authored by Chiara Marcolla

Since Specialization
Citations

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

Fields of papers citing papers by Chiara Marcolla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Chiara Marcolla, 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 Chiara Marcolla Line = papers co-authored together Chiara Marcolla links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2022122
2 201217
3 20147
4 20167
5 20156
6 20184
7 20213
8 20213
9
On the weights of affine-variety codes and some Hermitian codes
20113
10 20192
11 20241
12 20141
13 20191
14 20240

About Chiara Marcolla

Chiara Marcolla is a scholar working on Artificial Intelligence, Discrete Mathematics and Combinatorics, Computational Theory and Mathematics, Information Systems and Electrical and Electronic Engineering, having authored 14 papers that have together received 177 indexed citations. Recurring topics across this work include Coding theory and cryptography (11 papers), Cryptography and Data Security (6 papers), Finite Group Theory Research (5 papers), Cryptography and Residue Arithmetic (3 papers), Algebraic Geometry and Number Theory (2 papers), Complexity and Algorithms in Graphs (2 papers), Cryptographic Implementations and Security (2 papers) and graph theory and CDMA systems (2 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (19 citations), Artificial Intelligence (139 citations), Information Systems (51 citations), Computer Networks and Communications (37 citations) and Computer Vision and Pattern Recognition (24 citations). Chiara Marcolla has collaborated with scholars based in Italy, United Arab Emirates and Germany. Frequent co-authors include Frank H. P. Fitzek, Victor Sucasas, Marc Manzano, Riccardo Bassoli, Najwa Aaraj, Massimiliano Sala, Emmanuela Orsini, Edoardo Ballico, Emanuele Bellini and Nadir Murru. Their work appears in journals such as Finite Fields and Their Applications, Journal of Pure and Applied Algebra, Proceedings of the IEEE, IACR Transactions on Cryptographic Hardware and Embedded Systems and Designs Codes and Cryptography.

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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