Luca Sciullo

531 citations
36 papers · 378 · h-index 13

Impact in

Papers in

Luca Sciullo

30 papers receiving 363 citations

Peers

Luca Sciullo
Comparison fields: 5 of 58
  • Computer Networks and Communications 235
  • Industrial and Manufacturing Engineering 48
  • Computer Vision and Pattern Recognition 63
  • Information Systems 57
  • Electrical and Electronic Engineering 114
Replace Gabriel Mujica with:
Gabriel Mujica Spain
Alan McGibney Ireland
Riccardo Tomasi Italy
Boon-Yaik Ooi Malaysia
Azza Allouch Saudi Arabia
Guoqing Tu China
Biswajeeban Mishra Hungary
Hong Min South Korea
Cheng Zeng China
Tianping Deng China
Luca Sciullo relative to Gabriel Mujica Spain Gabriel Mujica's profile →
Citations per field
00.5×2.8×
Gabriel Mujica · 1×
Citations per year

Countries citing papers authored by Luca Sciullo

Since Specialization
Citations

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

Fields of papers citing papers by Luca Sciullo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Luca Sciullo, 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 Luca Sciullo Line = papers co-authored together Luca Sciullo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202047
2 201946
3 201826
4 201925
5 202223
6 202021
7 202218
8 202018
9 202117
10 201915
11 202315
12 202415
13 202212
14 202012
15 202111
16 202210
17 20239
18 20227
19 20197
20 20206

About Luca Sciullo

Luca Sciullo is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Information Systems and Civil and Structural Engineering, having authored 36 papers that have together received 378 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (19 papers), IoT Networks and Protocols (9 papers), Context-Aware Activity Recognition Systems (7 papers), Opportunistic and Delay-Tolerant Networks (4 papers), Structural Health Monitoring Techniques (4 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Infrastructure Maintenance and Monitoring (3 papers) and Digital Transformation in Industry (3 papers). The work is most often cited by research in Computer Networks and Communications (235 citations), Industrial and Manufacturing Engineering (48 citations), Computer Vision and Pattern Recognition (63 citations), Information Systems (57 citations) and Electrical and Electronic Engineering (114 citations). Luca Sciullo has collaborated with scholars based in Italy, Brazil and Germany. Frequent co-authors include Marco Di Felice, Angelo Trotta, Lorenzo Gigli, Federico Montori, Tullio Salmon Cinotti, Ivan Zyrianoff, Alessandro Marzani, Luca De Marchi, Federica Zonzini and Nicola Testoni. Their work appears in journals such as IEEE Access, Ad Hoc Networks, Internet of Things, Future Generation Computer Systems and IEEE Internet of Things Journal.

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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